SOCIAL CAPITAL AND INEQUALITY IN SINGAPORE

by

Vincent Kynn Hong Chua

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Department of Sociology University of Toronto

© Copyright by Vincent Chua 2010

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Social Capital and Inequality in Singapore

Vincent Chua

Degree of Doctor of Philosophy

Department of Sociology University of Toronto

2010

Abstract

Written as three publishable papers, this dissertation examines the sources of several

forms of social capital in Singapore, and the effects of social capital on occupational

success.

Using representative survey data from Singapore, these papers make several important

theoretical contributions:

The first paper examines how and why categorical forms of stratification such as gender

and ethnicity tend to produce distinctive forms of network inequalities: for example,

whereas Chinese (relative to Malays and Indians) tend to have greater access to well-

educated, wealthy, Chinese and weak tie social capital (but not non-kin), men (relative

to women) tend to have greater access to men, non-kin and weak ties (but not well-

educated, wealthy and Chinese). The key to understanding such distinctive patterns of

network inequalities (by gender and ethnicity) is to understand the distinctive ways in

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which gender and ethnic groups are distributed in routine organizations such as

schools, paid work and voluntary associations.

The second paper examines the significance of personal contacts in job searches, in the

context of Singapore’s meritocratic system. I show that in certain sectors such as the

state bureaucracy, social networking brings no distinct advantages as appointments are

made exclusively on the basis of the credentials of the candidates. Thus, personal

contacts are not always useful, especially in labour markets that rely heavily on the

signalling role of academic credentials to match people to jobs. In contrast, personal

contacts are more useful among less qualified job searches in the private sector.

The third paper shows that while job contacts (i.e. ‘mobilized’ social capital) may not

always pay off in meritocratic labour markets, ‘accessed’ social capital remains

extremely important. The leveraging power of social capital in meritocratic markets is

not the active mobilization of job contacts per se, but more subtly, the result of

embedded social resources such as knowing many university graduates and wealthy

people.

Together, these papers illustrate how socio-structural factors such as meritocracy,

gender and racialization form important predictors of the distribution, role and value of

social capital in everyday life and labour markets.

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“The life of an individual cannot be adequately understood without references to the institutions

within which his biography is enacted.”

C. Wright Mills

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ACKNOWLEDGEMENTS

I owe a unique debt of gratitude to the chair of my dissertation committee: Professor

Bonnie Erickson, who introduced me to the fascinating world of social capital and

through her close mentoring, helped me be a better researcher. I have gained much

from her intellectual agility and her very incisive feedback of my work.

I am indebted to Professor Barry Wellman, who imparted many important lessons

concerning the art (and science) of scholarly writing and who gave me several

opportunities to co-author book chapters and journal publications. I have learned much

from these collaborations and will strive to be just as supportive of my own students in

the future.

My sincere thanks go to Professor Zaheer Baber, who was a continual source of

friendship and support during my PhD years. It is interesting how our paths have

converged twice -– first in Singapore (during Sociology 101) and later in Toronto.

I am grateful for the support of Professor Eric Fong and Professor Bob Andersen, both

of whom kindly agreed to be part of this dissertation committee.

As statistical analyses are an integral part of this dissertation, I acknowledge my

mentors in social statistics: Professor Ann Sorenson and Professor Blair Wheaton, who

through their excellent teaching, enlightened my understanding concerning the role of

‘numbers’ in Sociology. My active interest in teaching social statistics today is a direct

result of being in those classes.

I thank Professor John Myles and Professor Shyon Baumann for being so supportive of

my work during the doctoral research practicum. Their generous comments and

insights helped me win the Daniel Grafton Hill Best Graduate Paper Prize, but more

importantly, they taught me how to write and angle a scholarly paper. This paper was

subsequently accepted for publication in Social Networks.

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Deep thanks go to Jeannette Wright, our indispensible graduate coordinator, who

during the five years, managed my file, and made sure that I (along with other graduate

students) met our administrative deadlines. I thank Kai-Lii Veer, our new graduate

coordinator, for her additional administrative help with the PhD oral defense.

Many friends in graduate school have made my journey a memorable one. Omar

Faruque and Jing Shen were reliable dinner companions. We talked about many things,

often in melodramatic terms: the chaos (but homeliness) of Bangladesh, the vibrancy

(but messiness) of contemporary China, the neatness (but restrictions) of Singapore and

of course, the enviable “quality of life” in Canada.

Chia Yeow Tong, a PhD student at OISE and fellow Singaporean, taught me the value

of an entrepreneurial outlook amid seemingly insurmountable challenges.

My office mates, Rochelle Coté and Phillipa Chong, were supportive co-runners in the

PhD journey. Rochelle (together with Jennifer Kayahara) organized dissertation

brainstorming sessions. Phillipa always made sure we had our afternoon tea and

arranged dinners and parties on several occasions, the most memorable of which was

(of course) the post PhD defense and farewell party she kindly put together for me.

A number of people including my committee read all or parts of the manuscript: John

Myles, Shyon Baumann, Paul Glavin, Deanna Pikkov, Mark Easton, Bader Araj, Naoko

Shida, Roxanna Waterson, Lim Chih Yang, Lim Weida, Julia Wong, Stephen Appold

and Elizabeth Thompson. Their comments were very valuable.

I thank Paul Glavin and Paul Armstrong for being such caring colleagues, as well as

Lisa Kaida and Stella Park for providing such strong peer support throughout the years.

I thank members of the Critical Sociology Book Review Collective, in particular Nadine

Blumer for steering the collective, and for allowing me to contribute ‘Notebooks’. To

the rest of the Collective: Michal Bodemann, Zaheer Baber, Paul Armstrong, Norah

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MacHendrick, Tara Hahmann, Sarah Knudson and Agata Piekosz, I will certainly miss

our meetings and friendship.

NETLAB has become an important part of my life: besides Professor Barry Wellman, I

thank, in particular, Julia Madej and Natalie Zinko for their partnership in our writing

projects.

Rubens Rahim and Stacey Westwell gave me warm hospitality both in Toronto and

Vancouver. They were always welcoming and concerned about my welfare and

progress.

Danny and Lauren Teh were very close companions. The dinners (with Peter and

Halle) were like family gatherings.

The Salvadors (Joseph, Evelyn, and Mamy) were very warm people. The Wongs: Uncle

Wong, Aunty Emily, Fiona, Nicholas, Aaron and Camille were, like the Tehs and

Salvadors, very gracious.

Roy Abraham was a close friend and confidant. Victor and Sue Kasenda, Tracy Qin,

Zhao Yanfei, Grace So, Kim Larsen and Suzyo Chilongo were close buddies.

I thank the National University of Singapore, in particular Professors Lian Kwen Fee,

Hing Ai Yun, Paulin Straughan, Tong Chee Kiong, Ho Kong Chong, Tan Ern Ser and

Chua Beng Huat, for believing I could get the job done, and for their encouragements

along the way.

This dissertation is dedicated to my parents, Chua Cheow Hwa and Lee Kwee Mildred.

This PhD is a reflection of their unconditional love all these years.

My eldest brother, Justin Chua and sister-in-law, Lynn Tan (and their children Joshua

and Ariane) were especially kind. They were like angels guiding me, paving my

journey, turning my PhD from crucible to sweet waters.

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My second brother Leonard Chua and his wife Tricilia Tang (and their children Josthan

and Tenessa) were very supportive. My two visits to Boston (Harvard) in the summer

and winter of 2009 were heartwarming experiences.

My twin brother Victor Chua and his wife Grace Yong were likewise extremely

supportive, particularly in helping me transition back into Singapore. They have

always gone that extra mile.

Above all, I would like to thank God for opening the door to Toronto, and for blessing

me with such wonderful social networks -- family, friends, colleagues, and professors

alike.

Vincent Chua, University of Toronto, August 2010

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Table of Contents

Chapter 1: Analyzing Social Capital in Context ……………………………….……….…...…………... 1 Chapter 2: The Human Capital Society ……………………………………………………..…………... 18 Chapter 3 (Paper 1): Categorical Sources of Varieties of Network Inequalities ……………………………...… 44 Chapter 4 (Paper 2): Social Networks and Labour Market Outcomes in a Meritocracy ...……….………….... 85 Chapter 5 (Paper 3): The Invisible Hand of Social Capital ……………………..……………………………….. 128 Chapter 6: Conclusion …………………………….………………………………………....................... 164 Appendices: Name Generator and Questionnaire …………………………………………………….... 175

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List of Tables

Chapter 3 (Paper 1)

Table 1: Number of Types of Social Capital by Gender and Ethnicity 58 Table 2: Categorical Inequality in Social Capital 63 Table 3: Education and Inequality in Social Capital 65 Table 4: Work and Inequality in Social Capital 66 Table 5: Household Income and Inequality in Social Capital 67 Table 6: Family Formation and Inequality in Social Capital 68 Table 7: Voluntary Associations and Inequality in Social Capital 70 Table 8: Summary of Interaction Effects 75

Chapter 4 (Paper 2)

Table 1: Descriptive Statistics of Sample of Singapore Citizens and Permanent Residents 100 Table 2: Binary Logistic Regression estimating the Effect of Education on Contact Use 105 Table 3: OLS Regression estimating the Effect of Contact Use on Earnings 108

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Table 4: Job Sector Differences in Education, Earnings, Proportion of Job Contact Users 109 Table 5a: OLS Regression estimating the Effect of Contact Use on Earnings by Job Sector 110 Table 5b: OLS Regression estimating the Effect of Contact Use on Earnings by Job Sector 111 Table 6: OLS Regression estimating the Effect of High-Status Job Contact on Earnings by Respondent’s Education 114 Chapter 5 (Paper 3)

Table 1: Sample Characteristics 142 Table 2: Multinomial Logistic Regression estimating the Effects of Accessed (# of University Graduates) and Mobilized Social Capital (Contact Use) on Job Sectors 147 Table 3: Multinomial Logistic Regression estimating the Effects of Accessed (# of Private Housing Dwellers) and Mobilized Social Capital (Contact Use) on Job Sectors 149 Table 4: Multinomial Logistic Regression estimating the Effects of Accessed (# of Chinese) and Mobilized Social Capital (Contact Use) on Job Sectors 150 Table 5: OLS Regression estimating the Effects of Accessed (# of University Graduates) and Mobilized Social Capital (Contact Use) on Earnings 152 Table 6: OLS Regression estimating the Effects of Accessed (# of Private Housing Dwellers) and Mobilized Social Capital (Contact Use) on Earnings 153 Table 7: OLS Regression estimating the Effects of Accessed (# of Chinese) and Mobilized Social Capital (Contact Use) on Earnings 154

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List of Figures

Chapter 4 (Paper 2)

Figure 1: Rate of Job Contact Use by Industry 112

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List of Appendices

Appendix A: Name Generator 175 Appendix B: Project Network Questionnaire 176

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Chapter 1 Analyzing Social Capital in Context

Social capital in context

Social capital scholars tell us that job success entails much more than formal skills,

training and credentials. They show that even as formal qualifications are important,

interpersonal networks are absolutely pivotal for job success (Burt, 1992; Lai, Lin and

Leung, 1998; Erickson, 2001; Lin, 2001).

I take an even broader view. Social networks are interpersonal relations which have

their more fundamental basis in macro-level structures such as state, economy,

education, labour markets and culture. It is these macro-level structures that affect the

distribution, role and value of social capital, and subsequently individuals’ job success

(Hsung, Lin and Breiger, 2009).

This dissertation is presented in the form of three publishable papers, aimed at

advancing our understanding concerning how aspects of social organization affect

individuals’ access to and payoffs from social capital in the context of contemporary

Singapore. These papers are united by the sociological axiom that while individuals

have free-will, they are also constrained by structural forces which affect their

experiences with social capital. Indeed, people are not just social networkers

manipulating networks for some future advantage. They are networkers operating

within realms of social structure: politics and economy, state ideology, bureaucratic

administration and other relevant structures of power (Granovetter, 2002).

These stand-alone but interconnected papers may be thought of as addressing two

broad research questions. The first concerns the sources of network inequalities: How is

social capital distributed among individuals/social groups and why? The second

concerns the consequences of network inequalities: What is the impact of network

inequalities on job success in different kinds of labour markets? While I have focused

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on the Singapore context, these questions are more broadly relevant for advancing our

understanding concerning how organizations and other institutional arrangements

affect the distribution, role and value of social capital in contemporary societies other

than Singapore.

Need to examine institutional contexts

Formal skills and credentials constitute critical explanations for how and why some

individuals are more successful than others in labour markets (Becker, 1964; Blau and

Duncan, 1967; Schofer and Meyer, 2005). And yet, a singular focus on human capital

implies a utopian world of meritocracy, whereby educational ‘effort’ and ‘ability’ are

the only key ingredients in the social mobility process (Young, 1958). From the

viewpoint of a strictly human capital model, social mobility depends mainly on an

individual’s ability and determination to make good in an implied Hobbesian struggle

for skills and credentials (Baptiste, 2001). But are things that simple?

The theoretical value-added aspect of social capital research is the opportunity it

provides for considering the role and impact of interpersonal structures on status

attainment. Here, the focus moves beyond economic actors’ accumulation of skills and

qualifications, and evokes the interpersonal environments within which economic

actors engage one another (Granovetter, 1985; Burt, 1992). Social networks are often a

“final arbiter” of competitive success, after human capital elements have all been

considered (Burt, 1992:67). Vouching or putting in a good word for someone is an

important way of matching seekers to jobs, because it provides more nuanced

information than credentials (Granovetter, 1974; Burt, 1992; Bian, 1997). That social

capital so often precipitates educational success (Coleman, 1988), matches people to jobs

(Granovetter, 1974) and enhances status attainment (Lin, 2001), makes it an extremely

important contextual element in social stratification research.

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But this begs the question: is analyzing networks on their own sufficient for

understanding the full nature of economic action? While social capital is an important

structural concept, it does not, by itself, increase our understanding concerning the

interrelationship between social capital and the larger institutional environments within

which social capital is embedded. We need certainly to expand our knowledge

concerning the interplay between social capital and social institutions, organizations,

and social history, and not settle for ‘structure’ taking the form of network nodes and

edges only (Granovetter, 2002).

Social capital and the problem of individualism

Generally defined, social capital refers to the resources that people have potential access

to from being connected to others possessing those resources (Lin, 2001). Social capital

is not just a social “relation” binding individuals together, but more strategically, it is a

social “resource” that can be mobilized for some expressive and/or instrumental

purpose (Lin, 2001). The focal individual (or central node) is here assumed to be an

autonomous manager of his/her own personal network: he/she is a network strategist

who “invests” in social capital and mobilizes them with an eye to future rewards (Lin,

2001; Wellman, 2007).

Such an autonomous approach may be too instrumentalist however -- as it fails to

consider two further aspects of social organization. First, people are not always at

liberty to choose their network members: kinship networks are an example of the often

ascriptive nature of human relations (Fischer, 1982). Beyond family, social relations

often arise from social contexts, rather than from a person’s free-will alone (Feld, 1981).

Therefore, it is appropriate to think of individuals not only as managers of their own

personal networks, but also as individuals who are tied to networks in less strategic,

conscious or intentional ways (Lin and Ao, 2008; Small, 2009).

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Second, an instrumentalist viewpoint falls short of addressing the question of how

social capital may integrate with larger aspects of social organization. Using the

example of Burt’s theory of structural holes (1992), Granovetter (2002) argues that while

strategists may often manipulate networks for personal gain, that is, by positioning

themselves between unique clusters of information (and preventing others from filling

the gaps), focusing on network structures alone often obscures the nature of the

relationship between social institutions and the networks themselves.

On this point, Feenstra and Hamilton (2006:22-23) have paraphrased Granovetter well:

Granovetter has warned repeatedly that simply evoking network structure (that

is, centrality or structural holes) is causally insufficient without a more

developed sociological understanding of the historical context... Instead, he

argues that network analysis should be less formal and methodological and more

linked to standard sociological concerns with power, social structure and

institutions than is now the case... In calling for a sociological understanding of

context, he wants to move an embeddedness perspective away from the

structural arrangement of networks to institutional foundations of economic

action.

The intended contribution of this dissertation is therefore to specify in a systematic

manner, the “institutional foundations” that surround structures of network ties. More

directly, the intended aim is to demonstrate how macro-level factors such as 1) state

rule and their attendant systems of categorical administration and domination, 2)

specific aspects of political economy such as the nature of the link between education

and labour market systems, and 3) the persistence of class, gender and race as social

divisions (rather than merely innate attributes), produce consequences such as 1) the

unequal distribution of social capital between gender and ethnic groups, and 2) the

unequal role and payoffs to social capital for different kinds of individuals in different

kinds of labour markets.

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Culture as institutional rather than internal

Whereas culture is often interpreted as representing values or preferences, culture is in

fact, very much structural in nature. According to Swidler’s (1986) “toolkit” metaphor,

culture is not so much a “strategy in the conventional sense of a plan consciously

devised to attain a goal”, but rather, “a general way of organizing action” (Swidler,

1986:277). Indeed, “people do not build lines of action from scratch, choosing actions

one at a time as efficient means to given ends... instead, they construct chains of action

beginning with at least some pre-fabricated links... culture influences action through the

shape and organization of those links, not by determining the ends to which they are

put” (Swidler, 1986:277).

Culture is routinized and institutionalized in everyday life. It is, as White (2002:131)

puts it: ...a process of actors “finding footing in interactions with other actors who are

also seeking footings in what thereby becomes a sustained course of action”. The

persistence of pathways and sustained lines of action working through culture is an

important aspect of the reproduction of inequalities in everyday life and needs to be

considered alongside more obviously institutional mechanisms.

As far as culture is treated as a set of values or preferences, this dissertation adopts a

clearly anti-culturalist stance, but to the degree that culture is not just about intentional

preferences but unconscious “strategies, styles and habits” (Swidler, 1986:277), then

culture has an institutional side to it, and should be incorporated in the analysis of

economic life, social capital and social stratification (Hamilton and Biggart, 1988).

The point is not to claim that culture is “everywhere”, or even to say that everything is

eventually reducible to culture (Zelizer, 2002:109). Rather, we need, more carefully, to

underscore that culture is a set of beliefs, shared understandings and practices that

often reflect constraints which clearly have an institutional basis. For example, the

prevalence of social networking among Chinese economic actors (in the form of

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‘guanxi’), may not be due primarily to the fact that Chinese value or prefer social

networking more than any other ethnic group, but more structurally, because Chinese

have for a long time now, been concentrated in private sector jobs within the Chinese

diaspora, and these jobs require the active mobilization of networks (Xin and Pearce,

1996). On the surface, social networking may often be misrecognized as a purely

cultural form, when in fact institutional factors undergird those cultural forms (Bian,

1997).

Social capital in the context of Singapore

The societal context being analyzed is contemporary Singapore. All three papers utilize

representative data from the 2005 Project Network Survey, which contains detailed

information about the personal networks of a representative set of Singapore citizens

and permanent residents aged between 25 and 55. The original sample size is 1043 (but

the valid sample sizes will vary according to the paper). Each paper has its own data

and methods section so I will not go into the details of source and methodology at this

juncture. The data was collected with the help of a professional survey research

company, AC Nielsen, based on a research grant (R-111-000-051-112) from the National

University of Singapore (NUS).

Singapore serves as an excellent fieldsite for exploring the role and impact of

institutional factors on social capital, for various reasons. First, Singapore is a racially-

stratified society. That is, despite the ethnically-heterogeneous composition of

Singapore, the powerful state deals with its people in terms of racial categories:

Chinese, Malay, Indian, Others or ‘CMIO’ for short. ‘CMIO’ is a deliberate highlighting

of racial divisions by a highly technocratic, managerial and administrative state

(Clammer, 1998). Beyond innate attributes, ‘CMIO’ is a racial principle with real

consequences for people’s life chances (Hechter, 1978; Rahim, 1998). The question of

how racial principles operate in everyday life and of how they subsequently affect the

distribution of social capital, is an important one that this dissertation aims to address.

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Second, Singapore, despite its modernity, remains a rather strong patriarchal society

(Chan, 2000). This patriarchy is seen most clearly in the work-family interface, where

gender-segregated roles prevail, mainly in the form of women still playing a much

more active role in the home despite their simultaneously active engagement in paid

work (Straughan, 1997). Ironically, while Singapore women have outpaced men in their

educational attainment, women are still much more likely to remain at home because of

family and childcare. Hence, like race, gender is an important organizing principle

which we can expect, will significantly impact the distribution of social capital.

Third, Singapore is a decidedly meritocratic island city-state, where formal credentials

are highly emphasized at every stage of a student’s and worker’s life (MacDougall and

Chew, 1976; Evans and Rauch, 1999). The strong emphasis on human capital in many

Singapore labour markets makes it an excellent context within which to explore the

interrelationship between meritocratic constraints and social capital. We can ask for

example: to what extent do credentials and other kinds of meritocratic requirements

suppress the role and value of social capital in job matching and remuneration? Can

human capital and social capital be simultaneously important even in highly-

meritocratic labour markets? If yes how?

My theoretical opportunity resides in the fact that while Singapore is a broadly

meritocratic society, there are substantial variations in the extent to which this

meritocracy is enforced in the various labour markets. The state sector, comprising the

civil service, statutory boards and government-linked companies (GLCs), is clearly the

most meritocratic of the job sectors, followed by the multinational companies (MNCs),

and the small business sector (SMEs). While the powerful state sector exerts significant

pressure on the other sectors to adopt similarly meritocratic practices (DiMaggio and

Powell, 1983), this pressure is by no means totalizing. Variations in levels of

meritocracy across different types of job sectors afford an opportunity to measure how

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meritocratic constraints affect the role and value of social capital in different kinds of

labour markets.

The following sections provide a brief summary of the contents of each paper. Many of

the details are in the papers themselves, so my summaries will not pretend to be

exhaustive. My aim is more general: to sketch the broad arguments and highlight some

of the role and impact of macro-level factors on the distribution, role and value of social

capital in Singapore, and thereby contribute to broader concerns about how social

capital operates in institutional contexts that are racialized, patriarchal, and

meritocratic.

Categorical sources of varieties of network inequalities

The first paper examines the categorical sources of several forms of social capital. While

research indicates that social capital tends to be unequally distributed along gender and

ethnic lines (e.g. see Lin’s 2000 review), what remains less clear is how gender and

ethnicity: as organizing principles rather than as individual innate attributes (Omi and

Winant, 1994; West and Fenstermaker, 1995; Tilly, 1998), affect the distribution of social

capital in everyday life.

There is another issue. Examining the literature on social capital, it is not hard to notice

that gender inequalities in social capital tend to be discussed in terms of men’s and

women’s unequal access to forms of social capital such as non-kin (Moore, 1990), weak

ties (McPherson and Smith-Lovin, 1982) and men (Erickson, 2004), while ethnic

inequalities in social capital tend to be discussed in terms of ethnic groups’ unequal

access to social capital such as occupations (e.g. doctor, lawyer, teacher) (Moren-Cross

and Lin, 2008), the well-educated (Wilson, 1987) and dominant ethnic groups (Moren-

Cross and Lin, 2008). And yet this – the fact that gender and ethnicity often produce

characteristic forms of social capital is seldom pointed out, problematized or further

theorized.

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My data highlights that powerful gender and ethnic groups are not only more likely to

have more social capital, they also tend to control distinctive bundles of social capital

respectively. For example, I find that whereas Chinese (relative to Malays and Indians)

tend to have greater access to well-educated, wealthy and Chinese social capital (but not

non-kin), men (relative to women) tend to have greater access to men, non-kin and

weak ties (but not well-educated, wealthy and Chinese social capital). How can we

explain these distinctive patterns of network inequalities?

As social capital often arises from organizational settings (Feld, 1981), one way of

addressing the above question is to ask how gender and ethnic groups are distributed in

settings that matter for social capital formation. The way that gender and ethnic groups

are distributed in places such as schools, paid work and voluntary associations will

provide important clues as to the kinds of contextual mechanisms driving gender and

ethnic inequalities in social capital.

My analysis shows that ethnic groups’ unequal access to high education (but equal

access to paid work) and gender groups’ unequal access to paid work and voluntary

associations (but equal access to high education) account for much of why gender and

ethnic groups tend to access distinctive forms of social capital.

Institutions tend to add social capital equally to individuals, regardless of their gender

or ethnicity, suggesting a persisting logic of meritocracy governing how institutions add

social capital to members. The problem of network inequality in Singapore is therefore

not so much the issue of unequal increments in social capital (arising from

organizations), but more primarily, the issue of unequal entry into those organizations.

The paper delves into some socio-historical details concerning how specific

organizational gatekeepers have disadvantaged less powerful gender and ethnic

categories/groups.

Meritocratic constraints and the role and value of job contacts

10

From sources of social capital, I move on to examining the consequences of social

capital. In the second paper, I ask: what is the role and impact of job contacts on status

attainment (i.e. monthly earnings) in labour markets varying by levels of meritocracy?

While studies have established the generally useful and leveraging role of job contacts

(e.g. Granovetter, 1995 [1974]; Bian, 1994; Coverdill, 1998; Fernandez, Castilla and

Moore, 2000), can we expect job contacts to work the same way in all kinds of labour

markets? This seems a logical question, but the relative role and usefulness of job

contacts within and between labour market contexts remain relatively unexplored in the

literature. This paper will demonstrate that the role and payoffs to job contacts are

often not uniform, but contingent upon the characteristics of labour markets: for

example, I show that in labour markets that emphasize meritocracy, job contacts tend to

be less useful and leveraging.

Using previous research drawn from the United States as a reference point, but

comparing it with Singapore data, I ask: why is the use of job contacts is more prevalent

in America than Singapore? Rather than rely on cultural explanations, I argue that

contextual factors such as national variations in the relationship between education and

labour market systems in both countries are important determinants of contact use (Hall

and Soskice, 2001; Allmendinger, 1989).

I distinguish between two concepts in the varieties of capitalism literature: ‘liberal

market economies’ (LMEs) and ‘coordinated market economies’ (CMEs). In LMEs, of

which the United States is an exemplar, the supply and demand sides of the labour

market are ‘loosely-coupled’, that is, education systems send only weak signals to

employers about prospective workers. In CMEs by contrast (e.g. Singapore), the supply

and demand sides of the labour market are ‘tightly-coupled’, meaning that education

systems send strong signals to employers about prospective workers.

My general argument is: the more loosely-coupled the education and labour market

systems, the more job contacts are needed to fill informational gaps in job matching.

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The more tightly-coupled the education and labour market systems, the less job contacts

can influence the job allocation and remuneration process as formal qualifications are

overwhelmingly important. My data demonstrates that in CME environments such as

the state bureaucracy, job contacts bring no distinct advantages as appointments are

made exclusively on the basis of the academic credentials of the candidates. In LME

environments, on the other hand, job contacts are more useful among less qualified job

searchers in the private sector (which is an LME environment).

The Chinese are especially likely to use job contacts, not so much because they are

‘Chinese’ (i.e. culturally idiosyncratic), but more structurally, because of their historical

role in the small business sector. Today, Chinese in Singapore continue to hoard private

sector jobs, and they do so by evoking job contacts.

In the state sector, credentialing requirements tend to suppress the role and value of job

contacts. Well-educated job-seekers are significantly less likely than less well-educated

job-seekers to rely on job contacts. Those seeking entry into formal industries, such as

education, health and social work, are much less likely to rely on job contacts than those

seeking entry into less formal industries such as retail, wholesale and construction.

Beyond job contacts: Meritocratic constraints and the more subtle importance of social capital

If job contacts are often ineffective in meritocratic labour markets as the second paper

suggests, then the third paper asks: does it mean therefore that social capital is

consigned to play a marginal role in meritocratic recruitment and remuneration? The

answer is a definitive ‘No’: social capital continues to be important even in labour

markets that emphasize meritocracy, but in ways other than the active mobilization of

job contacts.

By distinguishing between accessed social capital and mobilized social capital (as in Lin,

2001), the third paper argues that whereas job contacts (i.e. mobilized social capital)

may often be ineffective in meritocratic labour markets, broader forms of social capital

12

other than job contacts (i.e. accessed social capital) remain extremely useful and

leveraging.

The distinction between accessed and mobilized social capital is an important one

because job contacts represent only a subset of the total capacity of a person’s network,

and are therefore an inadequate representation of the total potential of his/her social

resources (Lai, Lin and Leung, 1998; Lin and Ao, 2008). By examining the role and

value of accessed and mobilized social capital in tandem, this paper contributes to

research concerning the role of intentional and less intentional modes of network

utilization and their associated payoffs in labour markets. In view of the embedded

nature of accessed social capital (here contrasted with mobilized social capital), I have

used the terms ‘invisible hand’ and ‘visible hand’ of social capital to designate them

respectively (as Lin and Ao, 2008 had also done).

Much of the material benefits that people experience in meritocratic societies are really

the result of more incidental and unconscious pathways of networking: the gains that

people get from social capital are not always due to the networks they activate, but the

networks they have. While education may be extremely important in a meritocracy,

social capital in the form of the invisible hand is shown in this essay to be critical for job

success.

Strong accessed social capital effects suggest that status attainment in a meritocracy is

never about educational performance alone, but access to social capital as well. The

allocation of rewards in meritocracies is not just about effort and ability, but about

categorical processes such as race, gender and access to segregated networks. In

practice, inheritances, cultural capital and human capital are often channelled from

person-to-person, situation-to-situation through networks -- institutions and

bureaucratic structures notwithstanding.

Strengthening contextual foundations

13

Taken together, this dissertation, whether discussing sources or consequences of social

capital, seeks conscientiously for explanations at the level of structure and institutions.

The broad strategy is, as C. Wright Mills recommends in the Sociological Imagination

(1959): to let the macro explain the micro. The macro elements are the political

economy, social administration and power structures constituting Singapore society.

The micro elements are the biographical elements, namely Singaporeans’ experiences

with social capital and job success.

In adopting an institutionally-focused perspective, this dissertation elucidates the

inextricable link between the “public issues” of powerful social structures and the

“private troubles” of social capital management (Mills, 1959:8). As Granovetter (2002)

recently notes, there is a real need to link network analysis to standard sociological

concerns with power, social structure and institutions.

The next chapter will provide, appropriately, a brief introduction and account of the

Singapore context. The background information provided will help situate our study of

social capital in a broader contextual, institutional and socio-historical framework.

14

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18

Chapter 2 The Human Capital Society

Charlie Rose: You seem to be sensitive to the issue of what’s called nepotism. Lee Hsien Loong: We are very sensitive. Charlie Rose: Tell me about this sensitivity. Lee Hsien Loong: The whole of our system is founded on a basic concept of meritocracy. You are where you are because you are the best man for the job, and not because of your connections or your parents or your relatives... Charlie Rose: So if some journalist writes about nepotism and you think it’s not true... Lee Hsien Loong: Well, then we sue him, as we did recently.

Straits Times, 16 April 2010

Singapore is an intransigently meritocratic state. If as Hobsbawm and Ranger (1983)

note: nations are built upon “invented traditions”, then for the Singaporean nation, the

tradition of meritocracy is one well-versed mantra: “you are where you are because you

are the best man for the job and not because of your connections...”

The enshrining of ‘best man’ policies in Singapore, particularly in education and

employment has created a palpably human capital society, whereby cohorts of students

have for decades now, competed aggressively for the best schools, grades, scholarships

and jobs (Gopinathan, 1996; Tan, forthcoming). A culture of academic examinations

buttressed by a rigorous private tuition regime has become so entrenched among

students that the Ministry of Education has more recently sought to shift the curriculum

away from rote learning and introduce the teaching of soft/creative skills alongside a

continued emphasis on technical subjects (Straits Times, 9 March 2010).

A recent survey conducted in 2004 indicated that Singaporeans are most likely to deem

education as being most important for social mobility, followed by hard work, ability,

social connections and luck (Tan, 2004). The fact that social connections was ranked

fourth (only after education, hard work and ability) implies the great extent to which

meritocratic values have become widespread in Singapore. And yet more than a set of

values, meritocracy has become institutionalized. For generations now, Singaporeans

19

have imbibed the message that educational achievements are alone sufficient for job

success. The result is a school system that cultivates a love for academic grades rather

than a love for learning (Dore, 1976). It has been argued that university graduates in

Singapore may be over-educated but under-skilled (Appold, 2005).

Meritocracy as a social system with contradictions

Meritocracy is a social system that allocates rewards to individuals based on the

principle of educational merit (Goldthorpe and Jackson, 2008). As noted by Michael

Young (1958), merit is the combination of “ability” and “effort”. The ideological appeal

of meritocracy lies in its -- at first glance -- impeachable logic: people are rewarded

based on some measure of how naturally gifted they are and how much effort they have

been willing to put in. Success is individualized, and if failure occurs, the fault is

implied to be wholly personal as well.

Indeed, the individualism implied in meritocracy leaves no conceptual space for some

rather pertinent questions: can we rightly assume that ability is entirely biological, and

unaffected by social factors? Do class resources such as family background, private

tutors and personal networks compensate for personal lack in ability and effort? Do

unit increases in ability and effort pay off equally well for different groups of people?

A meritocracy is most fair and impartial when starting lines are approximately equal

(e.g. everyone is poor or rich). However, when applied to advanced societies,

meritocracy becomes but a fortuitous agent for elitism and social reproduction.

Meritocracies have an important hand in alleviating family background inequalities, but

they do not by any means, eliminate it. For one, children from wealthier backgrounds

inadvertently get a head start in life as they get to go to better schools (Gillis, 2005).

Pre-existing class divisions combined with a highly-meritocratic education system have

enabled wealthy families to consolidate durable bases of material and symbolic power

20

in Singapore (Tremewan, 1994). While almost all Singaporean children have basic

access to elementary school, wealthier children are exposed to better resources and thus

stand a better chance of doing well at school (Barr, 2006). Examinations are meritocratic

(and in this regard, many less fortunate children have done admirably well), but family

resources spread a safety net for the less academically inclined children of wealthy

families (see Lareau, 2000).

Because class factors are so important to academic achievement, homogeneously poor

groups such as ethnic minority Malays in Singapore are particularly disadvantaged.

While there are many Chinese and Indians who are not wealthy, the Malay community

stands apart as a group that is almost uniformly disadvantaged (Li, 1989; Rahim, 1998).

Like blacks in the United States (Wilson, 1987; Omi and Winant, 1994), Malays in

Singapore are more likely than the other ethnic groups to have to contend with poverty

and stigmatizing attributes such as ‘poor’ and ‘lazy’ (Hirschman, 1986; Rahim, 1998). In

the discourse of meritocracy, ethnic minorities’ poorer performance in school is often

attributed to factors such as lack of motivation rather than more accurately their lack of

class resources (Rahim, 1998).

While women are less likely to experience the kinds of family background

disadvantages that Malays do, they are disadvantaged in other ways. For example,

although gender inequalities have narrowed substantially in education (Chang, 1995),

Singaporean women continue to be significantly disadvantaged at work and at home.

Many well-educated women are engaged in paid labour markets, but the PMT

(professional, managerial and technical) ranks are still dominated by men (Chan, 2000).

At home, many working women are expected to shoulder the bulk of childcare, despite

their already stressful work lives. Meanwhile, males, particularly traditional males,

remain generally reluctant to contribute more actively to domestic tasks. When

childcare becomes urgent, it is usually the woman who leaves the workplace

(sometimes temporarily) rather than the breadwinner male (Straughan, 1997).

21

Meritocratic societies are unequal societies. A meritocratic society will not guarantee an

absence of gender or racial biases. In fact, as meritocracies cannot eliminate family

background inequalities (for example, by abolishing inheritances and other

intergenerational transfers), ethnic boundaries operating through class mechanisms

continue to be salient (Hechter, 1978). Meritocracies do not eliminate patriarchy either.

Indeed, the gender script (that work is the place of men and home is the place of

women) remains a durable force in contemporary societies. While meritocratic norms

may be expected to eventually remove gender biases in a distant future (Blau and Kahn,

2006), notions of patriarchy still cling on, if not in the minds of individuals, then in the

practices of institutions (England, 1994; Tilly, 1998).

In Singapore, Confucianism and patriarchal themes such as choosing the ‘best man for

the job’ continue to enforce gendered, racialized (namely Chinese) and class-based (elite

versus not) notions of society, even as meritocracy is being emphasized. In the rest of

this essay, I discuss various aspects of the reproduction of class, racial and gender

relations by describing relevant aspects of Singapore’s historical, political and socio-

economic development.

Educating labour for foreign capital in a merit-based survivalist environment

The eviction of Singapore from Malaysia in August 1965 (due primarily to Singapore’s

insistent stand on meritocracy and its subsequent refusal to accede to Malaysia’s Malay-

first or ‘Bumiputra’ policy), provided occasion for the ruling People’s Action Party

(PAP) to play on public insecurities and propagate an ideology of survivalism (Chan,

1971; Tremewan, 1994). This rhetoric of survivalism was based on the sudden and

anguishing fact that Singapore was now independent from Malaya with no hinterland

to build a viable economy from (Lau, 1998).

It was in the context of such emergency conditions that the ruling PAP legitimated their

right to rule with an indomitable iron fist (Tremewan, 1994). On the premise that a

22

materially-deprived economy demanded close and urgent attention, Singaporeans were

exhorted to work hard and not be side-tracked by political concerns (Chua, 1995). The

lack of natural resources in the island city-state, coupled with its geographical realities

(particularly its small size), have enabled the Singapore state to generate a discourse

underscoring the redemptive role of an important substitute --- human capital.

Unlike the other East Asian economies (e.g. Japan, South Korea and Taiwan) which

built their post World War II economies on the strength of entrepreneurial ventures

initiated by local capitalists (hence the rise of economic giants such as Toyota, Honda

and Samsung), Singapore had chosen (rightly or wrongly) the path of MNC-led growth

(Schuman, 2009). To stem the tide of growing unemployment, Singapore was promoted

by its state elites as a low-cost manufacturing base for foreign capital (Castells, 1988). It

so happened that during the 1960s and 1970s, American and European companies were

looking for offshore manufacturing bases for their electronics sector, and Singapore was

fortunate enough to have had, at that time, an attractive mix of developed

infrastructure, tax incentives, and educated labour (Tremewan, 1994).

While Lee Kuan Yew and the Economic Development Board (EDB) have often been

accredited for bringing Singapore from “Third World to First World” (Lee, 2000),

fortuitous events and circumstances in the 1960s and 1970s such as the outsourcing of

manufacturing jobs by American and European corporations (such as Texas

Instruments, Hewlett Packard and Philips), along with the much slower rate of

development in the rest of Southeast Asia, and most significantly, the closed-door-

policy of China, afforded Singapore a thirty year window of opportunity to grow its

economy. Without this window, Singapore would not have survived.

Today, multi-national companies (MNCs) continue to be an important part of

Singapore’s economic landscape, but competition has certainly intensified as MNCs

constantly seek out cheaper locations (Ngiam, 2006). To remain competitive, Singapore

has had to re-invent itself, that is, to upgrade its human capital and technological base

23

while keeping wages in high-end industries relatively low. The latest direct foreign

investments (FDIs) have been in the areas of pharmaceuticals, biotechnology and

intellectual property (Pereira, 2008).

Although Singapore will never again be competitive in low-cost manufacturing because

of China’s expansion, its competitive advantages lie in mid-level production and

servicing the Asian-Pacific region on behalf of foreign capital (Tremewan, 1994). In the

same way that the Chinese merchants of old mediated transactions between locals and

Europeans during the colonial era, modern Singapore continues to play a brokering role

on behalf of foreign capital. In network terms, Singapore fills a “structural hole”

between East and West (Burt, 1992). The fundamental role of Singapore has, for a long

time, been the provision of affordable but good quality products and services for

foreign capital in order that, on the domestic front, Singaporeans may keep their jobs

and experience social mobility. The implicit contract between ruler and ruled in

Singapore (or more aptly ‘Singapore Inc.’) is: grow the economy, and we will vote you

in (Ho, 2006).

Manuel Castells has called Singapore the “quintessential developmental state” and for

good reason (Castells, 1988:4). A developmental state is an economic system where

economic growth is assigned top priority and used to legitimate political rule. It is a

state which selects political leaders based on a rigorous system of academic evaluations

(Loriaux, 1999). Even though most developmental states operate on open and free-

market principles, political elites are de facto chairpersons in what are essentially state

enterprises. In a developmental state, the rulers are entrusted with the mandate of

growing the economy on behalf of the ruled. The ruled are in turn willing to exchange

political rights for economic growth (Woo-Cummings, 1999; Ho, 2006).

Educating the masses in order to elicit the best for the state sector

24

Education is a critical mechanism through which the powerful state identifies, selects

and grooms its future elites and leaders (Barr, 2006). Singapore is like a Confucian

Mandarinate. The winners of the rigorous education race are appointed as important

officials such as “mandarins” in the state sector (see Weber, 1983). In a Mandarinate

system, intellectual achievement is seen not only as a mark of mental acuity, but also a

reflection of character, strength of purpose, dedication, and moral virtue (Straits Times,

10 November 2006). In Confucianism, the state is more than a bureaucratic apparatus.

It is a moral authority that governs the people in a paternalistic manner (Chua, 1995).

In Singapore, examination stalwarts are brought into elite government with state-

sponsored scholarships to prestigious universities abroad in exchange for some years of

bonded service. While the scholarship system has paved the way for many bright but

less well-off students (Barr, 2006), recent evidence points to the fact that an increasing

number of scholars are from upper-middle class backgrounds, and that educational

resources are skewed in the direction of elite families (Barr and Skrbis, 2008).

The scholarship system has created a situation whereby talent concentrates in the state

sector, leaving the MNCs and small business sector with less talented individuals (Chan

and Ng, 2000). As the state hoards the national talent, the other labour markets have

had to settle for an academically less talented pool (Ngiam, 2006). The state’s

justification is that without a competent public sector, the rest of society would crumble

(Lee, 2000). Although examination-based hiring may not (in retrospect) always select

the best people (afterall, academic ability is only one aspect of ability), the signalling

role of educational credentials remains highly treasured in the state sector.

Mandarins in the small but very powerful state sector

The state sector, which comprises 1) the civil service, 2) statutory boards and 3)

government-linked companies (GLCs), is a highly formal social system (Quah, 1998;

Neo and Chen, 2007). Arguably, the state sector ceases to be meritocratic when job

25

rewards are allocated based on past performance, but a meritocratic system gains its

legitimacy by rewarding educational tangibles (Collins, 1979).

While the meritocracy in Singapore was the brainchild of Lee Kuan Yew, its

implementation in the context of the civil service was (particularly in the early days)

entrusted to his very able Finance Minister, Dr Goh Keng Swee. Being a PhD holder in

Economics from the London School of Economics (LSE), Goh Keng Swee “placed a high

premium on intellectual ability and academic brilliance, rather than experience… and as

Goh had carte blanche to hire anyone from the list of government scholars given to him,

he paved the careers of many young officers” (Neo and Chen, 2007:163).

Singapore’s educational tracking system extends into the military service that all 18 year

old Singaporean men undergo. Typically, those with the most excellent GCE ‘A’ level

grades are assigned to scholar or “white-horse” platoons where they do officer cadet

training (OCS) and are considered for prestigious government scholarships to Ivy-

League type universities abroad (Barr, 2006). After their three to four year stints

abroad, these officer-cadets return to Singapore to serve their bond for their state sector

employer (Barr, 2006). The scholar can break the bond if he/she wishes, but is morally

obligated to fulfill it.

Some of these scholars are assigned to government-linked companies (GLCs) upon

graduation. As GLCs are state enterprises run on a commercial logic, the prevailing

personnel policy is, as in the civil service, to “recruit in the open market, both at home

and abroad on competitive terms” (Krause, 1989). GLCs often have access to the civil

service’s pool of talented human resources. Indeed, some high-ranking civil servants sit

on the boards of GLCs and several are seconded to them full time (Krause, 1989:443).

Although run on free-market principles, GLCs have the support of state capitalization.

One Singapore study found that although GLCs “are no more or less liquidity-

constrained in their investment decisions than their private sector counterparts”, they

26

are nevertheless, “rewarded in financial markets with a premium of more than 20

percent” (RamÃrez and Tan, 2003:20). The authors posit that this has to do with the

market’s perception of government companies being extremely reliable. The good

economic performance of GLCs ensures dividends for investors and good salaries for

workers. As salaries in state sector jobs are about 10 percent higher than wages in

comparable private sector jobs (Evans, 1995), many graduates from the local universities

and polytechnics have striven to enter the state sector (MacDougall and Chew, 1976:309;

Neo and Chen, 2007).

Merchants in the large but relatively powerless small business sector (or ‘SME’ sector)

Along with the MNCs, the private sector comprises some 126,000 small and medium

sized business enterprises (SMEs). Many of these businesses are in industries such as

finance, retail and wholesale, construction and light manufacturing (Chan and Ng,

2000). While SMEs value good education, they do not enforce it to the same exacting

degree as the state sector. The SME sector is on some level less formal than the state

sector, that is, job contacts are important channels of job matching, even as credentials

are valuable. The SME sector is dominated by Chinese employers and workers who

rely heavily on networks (‘guanxi’) to recruit and get their work done. Anecdotally, in

Singapore’s high-end banking sector, recruitment is based on ‘old boy’ networks. Here,

job candidates from prestigious predominantly Chinese and mission schools are

especially advantaged.

The small business and financial sectors have their origins in the colonial era. During

that time, Singapore was used by the British as a trading post for goods flowing

between the continents. Its strategic location and naturally deep harbour made

Singapore a good stop-over location for ships travelling between eastern and western

trade routes. The British brought their merchandise to the region (e.g. tea and spices

from India), and sold them to the natives through Chinese merchants who had intimate

knowledge of the local markets. Chinese labourers came to Singapore via a patronage

27

system called credit-ticket, whereby wealthy Chinese merchants paid for the tickets of

Chinese immigrants in exchange for some future labour and subservience (Visscher,

2007).

Before 1867, the British did not play an active role in the day-to-day running of

Singapore, but ruled from their administrative base in Calcutta. They wielded

administrative control from afar through a system known as Kapitan, which is a

decentralized system of control that appoints local headmen over each racial group.

Given their strong links with clan associations and secret societies, the rich Chinese

merchants were rulers over the Chinese community.

Arguably, the use of networks within the private sector started with the secret societies

and clan associations. Trade networks between the Malayan interior and the port cities

(Singapore and Penang), and migration networks between China and the port cities

were organized along regional, dialectical and clan lines, partly because of ethnic

occupational specialization, but most times because of secret society territorial and

labour control. The history of Singapore/Malaysia is really the history of Chinese secret

societies versus foreign/colonial capital. On one hand, Chinese middlemen and

labourers hoarded work opportunities in the trading, retail and construction sectors.

On the other hand, foreign capital exploited cheap labour to boost their entrepreneurial

ventures.

Some secret societies engaged in criminal activity. The colonial authorities had tried to

decimate them and they succeeded to some extent, but ‘guanxi’ as a culture survived

well in the form of the legitimate secret societies: the clan associations! In fact, between

the 1960s and 1980s, there arose, with the help of a group of Chinese-educated elites, a

state-supported institutional revival of ‘guanxi’ which saw the increased role of Chinese

clan associations within the small business sector (Visscher, 2007).

State sector and small business sector as two very different cultural worlds

28

From the early days of British rule, a number of Straits Chinese (i.e. Chinese with Malay

ancestry) and Indian immigrants were co-opted by their colonial masters into the civil

service. Having been educated in English schools and having a relatively strong

command of the English language, these immigrants were of valuable use to the British.

At the same time, large groups of Chinese immigrants had already settled in Singapore

(from the conflict-ridden mainland) and were eking out a living. These were coolies

and labourers, who spoke a variety of Chinese dialects and had no knowledge of the

English language, but who were desperate for work in order that they may support

their families back home. The bulk of colonial attention went towards ensuring

superior rights and privileges for the landed Malay aristocracy, Straits Chinese

merchants, and a small group of elite Indian administrators, but relatively little

attention was paid to poorer Chinese (indentured) labour (Visscher, 2007) or Indian

plantation workers (Jain, 1970). These workers were supervised by co-ethnics of higher

status, who acted as middlemen and assistants for the Europeans.

Interestingly, the cultural divide between English and ethnic (or more specifically,

Chinese) would continue to persist in post-colonial and contemporary Singapore. Lee

Kuan Yew (otherwise known by close friends as Harry) was himself a Straits-born

Chinese educated in premier English schools such as Cambridge and the London

School of Economics (LSE). Along with a mostly English-educated group of nationalists

and some Chinese-speaking pro-communists, Lee Kuan Yew’s People’s Action Party

(PAP) wrestled control from the Labour Front movement and won the 1959 General

elections on the back of huge support from the Chinese-educated masses (Bloodworth,

1986).

However, after the elections, ideological tensions began to surface between the English-

educated Lee faction and the Chinese-educated communist faction over Chinese

sympathies for the Cultural Revolution. This culminated in a party split in 1961, with

Chinese-educated PAP members eventually leaving to form a separate party, the

29

Barisan Socialis (Bloodworth, 1961). Communal politics expressed and framed in terms

of ‘English versus Chinese’ were the order of the day (Huang, 2008). While Lee was

preparing the nation for merger with Malaya and thus was anxious to downplay the

Chinese element, the Chinese-educated badgered for greater institutional recognition of

their culture and education (Wong and Apple, 2002).

In 1966, the Barisan Socialis walked out of parliament, thus relinquishing to the PAP

total state power. All seats in Parliament were henceforth PAP seats -- until 1981, when

J. B. Jeyaratnam won an opposition party seat in the Chinese-educated ward of the

Anson constituency. This loss of a single seat devastated the PAP and fostered a gulf

between the predominantly English-educated state and a segment of the Chinese-

educated population (Jones and Brown, 1994).

As Singapore embarked on its MNC-led industrialization program, English quickly

became the key language of public administration, international business and higher

education. The Chinese language alongside other mother tongues namely Malay and

Tamil were retained but their role was more symbolic than instrumental. The mother

tongues were not official working languages but languages to be used and cultivated at

home. They were taught in schools as second languages and promoted as a form of

Asian tradition to balance the tide and perceived threat of western influence (Goh

Report, 1979).

The rise of English was met with some resistance. During the 1991 General Elections

(with Goh Chok Tong as Prime Minister), four parliamentary seats were lost to the

Chinese-educated opposition. Interestingly, it was not the ostensibly democracy-

hungry middle classes that voted against the PAP, but the Chinese-educated working

classes (Jones and Brown, 1994). With state resources working in favour of foreign

capital and a wealthy English-centered state, the Chinese-educated have increasingly

felt alienated and powerless. Although many among the Chinese-speaking have jobs

30

within the SME sector, their salaries pale in comparison with salaries in the much more

prestigious state and MNC sectors (Evans, 1995).

The cultural divide between English and Chinese has surfaced again in much more

recent times. The state is currently in the process of tweaking its elementary school

education system, and one proposed measure has been the assigning of lower weights

to the Chinese language (and other mother tongues) while subsequently increasing the

weights to English, Mathematics and Science (Straits Times, 4 May 2010).

For several years, a group of English-speaking parents have argued that maintaining

equivalent weightings would disadvantage children from English-speaking homes and

penalize their performance in the other three subjects, namely English, Mathematics

and Science (Straits Times, 4 May 2010). Predictably, several influential Chinese

individuals and clan associations spoke out against the proposal. One perceptive writer

(to the Straits Times on 8 May 2010) had noted that such a policy would inadvertently

disadvantage the less privileged Chinese-educated masses:

This is not just an educational issue. It’s a socio-economic issue. Children from

disadvantaged families who may be strong in Mother Tongue will be kept out of

the best secondary schools!

Due to pressures from Chinese (and other mother tongue)-educated groups, the state

had most recently, decided not to implement the proposed change in weighting, but

instead, to change the manner in which mother tongue languages are taught in schools

(Straits Times, 12 May 2010).

Malay marginality in an English-focused and elitist education system

The rise of English in the Singapore education system has been particularly

disadvantageous for lower-class individuals, most of whom grew up speaking the

mother tongue at home (whether Mandarin, Malay or Tamil) (PuruShotam, 1989). As

31

Malays are over-represented in poor families, they have been disadvantaged by the

emphasis on English (Rahim, 1998).

By evoking education as the only in-principle legitimate source of social mobility,

political elites have been able to account for Malays’ school and job underachievement

in terms of the latter’s supposed lack of motivation rather than more structurally, their

disadvantaged family backgrounds or linguistic disadvantages (Rahim, 1998). The

same discourse is applied to less academically-inclined Chinese: those that

underachieve are assumed to be ill-motivated, rather than have lower access to class

resources and/or English cultural capital.

The overlapping of ethnic boundaries with class boundaries in Singapore causes race to

be an especially salient social division (Hechter, 1978). In Singapore, ethnicity is an

exercise in political administration (Vasil, 1995). Singapore comprises some 42 ethnic

groups distinguishable along finer racial and linguistic dimensions, but because ethnic

identities are often too cumbersome to be administratively useful, the state relies on

racial categories to manage the population (Goldberg, 2002). The result is a

multicultural population thus simplified into four administratively convenient racial

categories: Chinese, Malay, Indian and Others (or ‘CMIO’ for short) (Benjamin, 1976).

The Malays and Indians are relatively homogeneous groups. Malays in Singapore are

united by the Malay language, their common position of disadvantage and most of all,

their common faith in Islam. The Indians are also united by language and religion.

Many Indians speak English and Tamil, and are often Christians, Hindus or Muslims.

The Chinese on the other hand are the biggest, most varied and most fragmented group.

They are English speakers, Mandarin speakers, Christians, Buddhists, Taoists, free

thinkers, rich, poor, middle class, in all sorts of occupations and speakers of various

Chinese dialects besides Mandarin. Such heterogeneity ensures that the Chinese are not

as close knit as a group as compared with Malays and Indians, and hence many of their

ties to community are weaker ties.

32

‘CMIO’ is not a purely Singaporean invention, but a product of colonial policy. In

Singapore, race is not just a sociological myth to be debunked, but a reality that

continues to structure society in tangible ways beyond colonialism (Clammer, 1998). In

Singapore, every child is racially-typed at birth. Administratively, the child is assigned

the father’s race, with all ethnic ambiguities generated by intermarriage or family

history conveniently discarded in favour of a single racial identification (Chua, 2003).

For official purposes, these single racial classifications are indicated on the child’s

identity card and become a permanent part of his/her ascribed identity for the rest of

his/her life.

The ideal Singaporean is upheld as one who successfully blends both Asian and

western identities but who privileges the former in his/her identity. Indeed,

Singapore’s society and industrialization is a rigid form of rational education which

refuses to acknowledge its compellingly western roots (Clammer, 1998). The result is

scientifically rational workers who are trained in western technology, but who are at the

same time, ethnic (i.e. interpreted Asian). To the state, ethnicity, particularly in the

form of rarefied Mandarin, is perceived to be especially important for economic

development even as western principles are actively used in the management of work

systems. Confucian values are perceived in the eyes of a developmental state to

encourage virtues such as diligence, thriftiness and honesty. Like the Protestant Ethic,

these virtues are believed to aid capital accumulation (i.e. savings and investing) and

generate capitalistic expansion on a larger scale (Ong, 1997). It is ironic that Confucian

values should be invoked as a factor for economic growth in contemporary Asia, given

that those same Confucian values were invoked by Weber to explain the decline of Asia

in ancient times.

On the education front, the developmental state has built several Special Assistance

Plan (SAP) schools which deliberately uphold a rarefied and standardized form of the

Chinese language and culture. In these schools, English and Mandarin are examined as

33

first languages. These schools have impressive infrastructure and are staffed with

competent teachers and administrators. Given the Chinese emphasis in these schools,

only a few Malays and Indians attend.

The presence of several highly-influential mission schools in Singapore adds to the

salience of racial boundaries. As these mission schools maintain upper-class traditions

and have large endowment funds supported by influential ‘old boy’ and ‘old girl’

networks, students attending these schools are exposed to better resources. Moreover,

as Christianity is emphasized in these schools, Malays (who are predominantly

Muslims) get inadvertently excluded.

In Singapore, primary school students are matched to schools based on an allocation

system that is sometimes biased. In a 1972 exercise, for example, students were

admitted according to three phases. In order of priority, Phase One gave preference to

children who already had siblings in the same school. Phase Two gave priority to

students whose parents were either alumni or members of the school board. Phase

Three opened the competition to the rest through balloting.

When siblings and children of alumni of mission schools are given priority admission,

educational privileges and disadvantages are transmitted across generations along both

class and ethnic lines. Disadvantaged Singaporeans have often raised concerns about

such priority admissions. In July 1983, one perceptive reader going by the pseudonym

“Fair Play” wrote to The Straits Times, with following comment:

I believe this is an unfair way of according priority. It will create a situation

whereby generations upon generations will monopolize the elite schools and

deny outsiders the chance to register.

The government’s response was rather evasive:

34

It is useful for a school to maintain close ties with its former students in building

up an identity and tradition of its own… thus, priority for registration is given to

a child whose parent(s) or elder sibling was a former student of the school.

There was tellingly, no attempt by the state to address the more pertinent issues of class

and ethnic stratification.

Unfortunately, class and ethnic inequalities originating in the education system often

carry forward into subsequent life domains such as the military, where conscripted

soldiers are typically assigned to vocations corresponding with their educational

attainment. Enlistees with lower levels of education are often assigned to service

vocations such as technicians, drivers or cooks. If they are combat-fit, they may end up

as foot soldiers or rifleman within the infantry units. Higher-educated Chinese are

over-represented in command positions. Malays usually end up as truck drivers (or get

assigned to the Civil Defence Force). Lower-educated Chinese and Indians usually

become storemen, foot soldiers or armskote men (looking after and cleaning weapons).

In sum, ethnic minorities in Singapore are disadvantaged in at least two ways. On one

hand, ethnic groups are unequally treated because of differences in their initial class

standing (hence their subsequently unequal access to education), but on the other hand,

the class standing of ethnic minorities is itself evidence of unequal treatment and

prejudice based on their ethnicity.

Patriarchal relations as distinct from race/ethnic relations

Although women and ethnic minorities are both disadvantaged in terms of their

respective locations in gender and ethnic stratification systems, the kinds of structural

hurdles faced by women are not necessarily the same as those faced by ethnic

minorities. An example is access to tertiary education, where ethnic minorities

(particularly blacks in the United States and Malays in Singapore) continue to be

severely disadvantaged, while women have made great advances (Gamoran, 2001).

35

In Singapore, gaining a tertiary education used to be a highly gendered phenomenon:

boys were more likely than girls to be highly educated as it was assumed that men went

out to work, while women stayed at home (Low, 1993). But this trend has changed over

time. Women are now as educated as men, and many have gone into paid work. The

introduction of the Women’s Charter in 1961, the growth of the industrial and service

sectors in Singapore, the giving of generous state subsidies for tertiary education and

the growing wealth of families, have all resulted in women having greater access to

education today.

The disadvantages of women in Singapore lie in other areas -- most significantly in the

domains of work and home. Despite substantial increases in female labour force

participation over the past decades, gender role expectations continue to ensure that

working women with young children bear the bulk of family duties and household

chores. Women are less likely than men to be in paid work and when they work, are

less likely to be in professional, managerial and technical (PMT) occupations.

The patriarchal state in Singapore has endorsed the reproduction of the gender script to

a great extent. For example, the state has for some time in its history, placed a cap on

the number of females in its local medical school, so that women comprised only a third

of all medical students. The state reasons that it is less worthwhile to train women

doctors as it assumes that they would, sooner or later, drop out of the paid workforce

due to childcare. Such policies reflect gender discrimination not only because potential

women doctors are excluded from training, but also because it reinforces the message

that women should not aim their sights on such a good career (Lazar, 2001).

The state stipulates that men should be heads of their household and women should be

supporters of the family. This belief is translated into policy. The allocation of medical

benefits in the state sector serves as an appropriate example: male employees in the

state sector may claim benefits for their families, while family members of female

employees do not have access to similar benefits (Lazar, 2001). The point (of such a

36

policy) is with reinforcing the notion that it is the husband’s responsibility to look after

the family’s economic needs. The husband-as-breadwinner model has made it more

culturally acceptable for wives to stay at home (as homemakers) than it is for husbands

to do so.

Elitism, racialization and patriarchy despite meritocracy

Meritocracy gives the impression that opportunities are equal across the board and that

differences are only post-competition differences. However, in practice, pre-

competition opportunities are seldom ever equal in the first place. Indeed, a

meritocracy dispenses rewards based on personal achievement, but it cannot ensure

that starting lines are equal for everyone.

As education is so essential to meritocracies, and as educational resources are so closely

linked with class resources, the winners in an advanced merit-based system are

increasingly individuals from the upper classes (Lareau, 2000). The logical end of

meritocracy is elitism (Young, 1958). Elitism underscores the plight of homogeneously

poor social groups such as the minority Malays in Singapore. Of course, ethnic

inequalities do not operate through class mechanisms alone, but race is an important

variable in its own right and a salient principle that continues to structure societies

independent of class (Omi and Winant, 1994).

Concerning gender, women continue to experience substantial disadvantages in the

realms of home and work, where the segregation of gender roles is pertinent. As noted

by Hans Rosling, a noted Swedish international health professor and public statistics

advocate who spoke recently at the UBS Philanthropy Forum (held in Singapore), the

low fertility rate in Singapore (currently at 1.23 babies per woman) may not be due to

the alleged lack of financial resources among young people, but because of “the not

very advanced state of Singapore’s gender relations, which lags behind its economic

and social development”. That is, “fathers... are not rising to the task of child-rearing,

37

and state support for equal parenting roles is not adequate.” As a result, “women have

been saying “no” to babies.” (Straits Times, 12 May 2010).

To sum up, one could say that while the main disadvantages faced by ethnic minorities

(e.g. Malays) are in family background inequalities and subsequently educational

inequalities, the main disadvantages faced by women are in the realm of gender roles,

reflected thus in women’s over-involvement in family and under-engagement in more

prestigious forms of paid work. Gender groups may divide along class lines, but

arguably more so in later stages of the life course than in earlier parts: that is, in careers

rather than in class-at-birth (Smith-Lovin and McPherson, 1993; England, 1994; James,

2008). The nature of gender and ethnic inequalities may be expected to differ across

societies, and each society’s gender and ethnic relations will have to be studied in detail.

The arguments made in this paper apply strictly to Singapore.

Next chapters

The following chapters will illustrate how the aforementioned structural conditions of

meritocracy, elitism, patriarchy and racialization affect the distribution, role and value

of social capital in Singapore. Having provided a brief history of Singapore society, I

now proceed to demonstrate, through each of my three papers, the inextricable link

between contextual factors, social capital and job success more broadly.

38

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44

Chapter 3 (Paper 1) Categorical Sources of Varieties of Network Inequalities

Gender and ethnic groups do not just have unequal access to social capital; they have unequal access to ‘distinctive forms of’ social capital. Using survey data from Singapore, I show that whereas Chinese (relative to Malays and Indians) tend to have greater access to forms of social capital such as well-educated, wealthy, Chinese and weak tie social capital (but not male or non-kin social capital), men (relative to women) tend to have greater access to forms of social capital such as male, non-kin and weak tie social capital (but not well-educated, wealthy and Chinese social capital). These distinctive patterns of network inequalities may be explained by the distinctive patterns of access that gender and ethnic groups have to organizations such as schools, paid work and voluntary associations. Broadly, this paper draws attention to why and how ascriptive categorical forms of stratification (such as gender and ethnicity) produce such characteristic forms of network inequalities. INTRODUCTION

The idea of social capital is that people have potential access to important resources

based on their ties to others who have such resources (Lin, 2001). While it is widely

recognized that social capital tends to be unevenly distributed in populations, along

categorical lines such as gender and ethnicity (Lin, 2000), what is less clear is how

gender and ethnicity -- as social categories rather than as individual attributes (or innate

dispositions) bring about network inequalities.

Whereas biological explanations have been offered for gender and ethnic stratification

(which some see as being natural and immutable), sociologists have generally sought to

replace genetic interpretations of gender and ethnicity with social and categorical

explanations (e.g. Shibutani and Kwan, 1965; Omi and Winant, 1994; West and

Fenstermaker, 1995). While the study of gender and ethnicity as categorical processes is

not new, the study of how gender and ethnic divisions bring about distinctive patterns

of network inequalities remains relatively unexplored.

45

It is not hard to notice in the literature, that whereas gender inequalities in social capital

tend to be discussed in terms of men’s and women’s unequal access to forms of social

capital such as non-kin (Moore, 1990), weak ties (McPherson and Smith-Lovin, 1982)

and men (Erickson, 2004), ethnic inequalities in social capital tend to be discussed in

terms of ethnic groups’ unequal access to forms of social capital such as occupations

(e.g. doctor, lawyer, cashier) (Moren-Cross and Lin, 2008), well-educated contacts

(Wilson, 1987) and dominant ethnic groups (also Moren-Cross and Lin, 2008). And yet

this –- the fact that gender and ethnicity tend to be associated with distinctive types of

social capital is seldom pointed out, problematized or further theorized.

Using the case of a gender and ethnically-stratified society, Singapore, this paper

demonstrates an instance of distinctive patterns of network inequalities by gender and

ethnicity. Its task is to explain why -- whereas Chinese (relative to Malays and Indians)

tend to have greater access to forms of social capital such as well-educated, wealthy and

Chinese networks (but not men or non-kin), men tend to have greater access to forms of

social capital such as men, non-kin and weak ties (but not well-educated, wealthy and

Chinese networks). Or to pose the question more formally: Why and how do ascriptive

categorical forms of stratification (such as gender and ethnicity in this case) produce

such characteristic forms of network inequalities?

GENDER AND ETHNICITY AS SOCIAL CATEGORIES

More than individual attributes, sociologists have emphasized the role of gender and

ethnicity as social divisions that organize everyday life. Already at birth, gender and

ethnic categories form important bases for stratification because people believe them to

be natural divisions of mankind (Shibutani and Kwan, 1965:46). While a person may

acquire the culture or behaviour of an alternative group, he/she usually continues to

carry the physical marks of his/her sex and ancestry and these become the basis of

46

further social distinctions and resource allocations (Shibutani and Kwan, 1965:51; Tilly,

1998; Ridgeway, 2006; Wimmer, 2008).

Gender and ethnicity are unique stratification systems in their own right, which are not

ultimately reducible to class (Blumer, 1958; Grabb, 1984; West and Fenstermaker, 1995;

Ridgeway, 2006). Certainly, while gender and ethnicity may be correlated with

achieved characteristics such as educational attainment, job experience and skills, the

persistence of pure gender and ethnic effects after controls testifies to the independent

effects of social categories (England, 1994; Downey, 2008).

Gender and ethnicity are, as Tilly (1998:83) notes, “exterior categories” that constitute

independent bases for discrimination practices. “Almost everywhere on earth... exterior

categories such as male versus female, white versus black or citizen versus foreigner

“provide scripts so pervasive that they modify interactions within all sorts of

organizations...” (Tilly, 1998:79) These scripts refer to the common understandings,

meanings, practices, relations and memories that are tied to categories. Durable

inequalities occur when exterior categories such as “male” and “female” are imported

and unquestioningly conjoined with interior categories such as “boss” and “secretary”

by powerful organizational gatekeepers. Over time, the “male boss” and “female

secretary” combination get adopted as an organizational template and repeated from

office to office.

Using Tilly’s ideas, this paper presents an opportunity to think about how gender and

ethnicity, as exterior categories, affect gender and ethnic groups’ access to organizations

such as schools, paid work and voluntary associations, and how this subsequently

affects their access to social capital.

The life course as a framing device

47

The life course serves as an excellent starting point for thinking about issues of gender

and ethnic inequalities in social capital. To begin, the life course can be perceived as a

path or road on which people travel. With time, these paths and roads form structured

patternings of life course events, life transitions, turning points, and trajectories

(Wheaton and Gotlib, 1997). An important aspect of categorical stratification and the

life course is social groups’ uneven access to important organizations and life

experiences such as school, work, marriage, parenthood, privileged households and

voluntary associations (Macmillan, 2005). Depending on the class, gender and ethnic

category, a person’s rate of participation in such organizations and life events may be

expected to vary (Levy, 1996; Jackson and Berkowitz, 2005; Mayer, 2005).

At birth, the family organization is a pivotal site of intense early socialization and

nurturing. This early socialization is typically followed by schooling (which itself

consists a range of formal educational sequences: kindergarten, elementary school, high

school, technical schools, college, etc). Schooling is typically followed by being in paid

work, setting up a new family unit (i.e. marriage and parenting), joining voluntary

associations, entering retirement, raising grandchildren, and so on. Most life courses

are organized around more or less clearly established patterns of modal sequences with

a tendency towards life course standardization amidst some de-standardization,

especially in the area of family formation (Levy, 1996; Shanahan, 2000; Bruckner and

Mayer, 2005).

Throughout the life course, organizational settings are not just places to accomplish

tasks (e.g. get a university degree or get paid for work), but also places that supply

multiple opportunities to form social capital. Schools, workplaces and voluntary

associations are all contexts that facilitate social encounters and interactions, which

potentially develop into relationships (Feld, 1981). The formation of social capital is

often an iterative process: as people move through the life course, networks evolve as

48

new members are added and as others move away (Bidart and Lavenu, 2005). Often,

networks become bigger and more diverse with time and experience (Fischer, 1982;

Erickson, 1996).

Organizations employ gatekeepers to assess personal biographies in accordance with

normative and institutionalized standards (Heinz, 1992). These gatekeepers (e.g. state,

teachers, employers and other authority figures) act on behalf of organizations and are

agents, whether conscious or not, of the reproduction of unequal life chances among

social groups (Omi and Winant, 1994; West and Fenstermaker, 1995).

In North American schools, teachers reproduce ethnic inequalities by relying on racial

categories in the allocation of rewards. Some ethnic groups do better, not because of

their coursework mastery per se, but because teachers perceive the racial group to be

diligent (Farkas et al., 1990). Concerning gender, bosses (who often are males), have

relied upon gender stereotypes to allocate work: for example, let the “men” (who are

assumed to leaders) be “managers” and let the “women” (who are assumed to be

nurturers) be “secretaries”. This practice of matching exterior gender categories with

interior rankings gets replicated across many work organizations (Tilly, 1998).

In general, we may think of organizations and their gatekeepers as upholding two

broad kinds of inequality mechanisms: 1) unequal access to organizations and 2)

unequal benefits for those who gain access to those organizations. The first implies

mechanisms which result in individuals’ differential access to organizations. The

second implies mechanisms which cause organizations to add resources unevenly to

individuals and social groups. While several studies have looked at organizational

sources of social capital (e.g. Erickson, 2004; Bian, 2008; Small, 2009), few have enquired

into the extent to which organizations generate social capital unequally among

categories of individuals.

49

Gender and ethnicity as unique categorical systems

Gender and ethnicity are unique categorical processes. Take contemporary changes in

education for example: studies in the United States show that whereas gender

inequalities in educational attainment have narrowed substantially over time, ethnic

inequalities in educational attainment (especially between blacks and whites) have

continued to be extremely salient (Gamoran, 2001). The question is why ethnicity has

not followed the same progressive path of gender. A broad answer is that gender and

ethnicity are governed by different dynamics (see Gamoran, 2001:140). In this paper,

the unique dynamics of gender and ethnicity are reflected in gender and ethnic groups

accessing distinctive forms of organizations and thereby accessing distinctive forms of

social capital.

An instance of gender dynamics

The post World War II era of economic consolidation and the feminist movement in the

United States created an atmosphere urging for greater gender egalitarianism in access

to education and jobs. By the 1970s, girls were outclassing boys at school (Abbott,

2006), and women were actively engaging in paid labour markets (Blau and Kahn,

2006). But growing gender egalitarianism did not, by any means, eradicate gender

inequalities.

While labour force participation rates among women are high, women still have much

lower access to professional and managerial jobs compared to men, and tend to

concentrate in female occupations such as clerical and non-commission retail sales,

manufacturing jobs in non-durable goods and domestic and child-care work (England,

2006:246). Also, while the gender wage gap has closed considerably over the past three

decades, men still earn more than women (Blau and Kahn, 2006).

50

Despite the modern era, the cultural mandate of “home” being the domain of “women”,

and “work” being the domain of “men”, remains strong (Coser, 1991). Women’s

significantly greater involvement in child-rearing has often led to many women leaving

the workplace temporarily and losing out on opportunities to build up work experience

and skills (Blau and Kahn, 2006). Unfortunately, whereas many women have gone out

to the workplace, men have not gone domestic at an equivalently fast pace, resulting in

working mothers having to cope with a second shift of unpaid work (Hochschild, 1989).

The bottleneck in gender inequality is thus driven by the fact that families continue to

organize along the lines of gender (especially the assignment of child-rearing

responsibilities to women), as well as the general resistance of men to taking on

traditionally female activities in the household (England, 2006). The result is that while

modern women are well-educated, many have, because of gendered expectations,

stayed at home, particularly during the child-rearing years.

An instance of ethnic dynamics

Ethnicity is a different sort of inequality mechanism from gender. As Tilly (1998:82)

notes: “...in much of our world, race and class overlap far more than gender and class,

with the result that importing a gender boundary line has different consequences than

importing racial frontiers.”

A major aspect of ethnic inequalities in modern societies such as the United States is

ethnic minorities’ persisting disadvantages in the field of education. While the civil

rights movement in the United States has certainly caused a dramatic reduction in overt

racial discrimination, the gap in educational achievement between whites, blacks and

Hispanics (but not Asians) continues to be obvious (Kao, 1995). Whereas educational

inequalities have narrowed considerably between boys and girls, they remain persistent

among ethnic groups, especially between blacks and whites (Gamoran, 2001).

51

It is not that blacks are opposed to education. Indeed, blacks value education as much

as whites. The disadvantages of blacks in education are substantially due to the fact

that “black youth’s strategy for success is less detailed, less complemented by daily

routines”... and their route to success may often “be overwhelmed by skills, habits and

styles” which do not match with the dominant culture (Downey, 2008:121). As family

background is a strong predictor of educational resources (Lareau, 2000), poverty

among blacks strongly limits their academic success (Downey, 2008).

In sum, contemporary societies have been characterized by two general trends

reflecting the unique dynamics of gender and ethnicity. The first is the narrowing of

gender but not ethnic differences in educational opportunities and attainment. The

second is the substantial narrowing of gender differences in educational attainment, but

not in the areas of family and paid work (Gamoran, 2001). Both these trends point to

the distinctive categorical work of gender and ethnicity and can be meaningfully

evoked to account for why gender and ethnic categories tend to generate such

distinctive forms of network inequalities.

HYPOTHESES

I test four hypotheses:

H1: Dominant gender and ethnic groups have more social capital than less dominant

gender and ethnic groups.

H2: Gender and ethnic groups access distinctive forms of social capital.

H3: Gender and ethnic groups access distinctive forms of social capital because they

access distinctive forms of organizations.

H4: Organizations such as schools, paid work and voluntary associations generate social

capital unequally, depending on gender and ethnicity.

52

Singapore serves as an excellent fieldsite for testing these hypotheses because gender

and ethnic mechanisms are seen clearest in societies with strong forms of gender and

ethnic inequalities and boundaries. As a highly patriarchal and racially-stratified

society, Singapore is an appropriate case study for examining how gender and ethnicity

work as general categorical processes in contemporary society.

SINGAPORE CONTEXT

In Singapore as in the United States, gender and ethnicity are important social divisions

with significant consequences for stratification.

Concerning gender -- although mass education and industrialization have opened up

educational and work opportunities for men and women beginning from at least five

decades ago (Chang, 1995), many Singaporean women are still homemakers. In 2005,

only 56.6% of women were in paid work, much less than the 78.2% among men

(Department of Statistics, 2005). Lazar (2001) argues that the opening up of labour

markets in Singapore does not actually reflect a real desire on the part of the state to

grant women equal rights: the state needs the labour of women to grow the economy,

but when the economy turns down, it is women who leave first.

At work, many women are in clerical or service jobs, serving a mostly male sector of

CEOs, professionals and middle managers, even as a segment of lower-educated men

concentrate in blue-collar jobs. In Singapore households, women still shoulder the

majority of child-rearing and household chores (although many have foreign domestic

workers to help lighten the load). Whereas many mothers have gone into the

workplace (to supplement the household income in an increasingly expensive

Singapore), men are still reluctant to contribute more actively to child-rearing, leaving

the task primarily to wives and grandparents.

53

Working mothers are under stress in Singapore. On one hand, the state wants the paid

labour (especially educated labour) of women to expand the economy. On the other

hand, the state also wants women to be active in reproducing the next generation. The

declining birth rate, especially among the Chinese and well-educated, has elicited a

particular response from the state. According to Lee Kuan Yew,

Equal opportunities, yes, but we shouldn’t get our women into jobs where they

cannot, at the same time, be mothers… You just can’t be doing a full-time heavy

job like a doctor or engineer and run a home and bring up children.

(Lee Kuan Yew, Straits Times 15 August 1983, cited in Chan, 2000:50).

The patriarchal state thus curtails women’s more active participation in paid work. The

cultural mandate (Coser, 1991): that work is the domain of men and home is the domain

of women is a categorical mechanism that continues to undercut the life chances of

women (especially older women) in Singapore.

Concerning ethnicity -- the roots of Singapore’s racial social structure lie in the British

colonial application of racial ideology in the administration of a multiethnic population

(Hirschman, 1986). One historical outcome of racial rule was an economy based on a

racial division of labour with Chinese as traders, Malays as land cultivators and Indians

as plantation workers, and above all, a society characterized by racially-segregated

housing.

As Chinese immigration from the mainland grew due to trade, the Chinese population

soon superseded the indigenous Malay population. As colonial fortunes grew, so did

Chinese wealth and population. A racial stratification order was soon established: the

colonizers on top, followed by Chinese, Indians and Malays in tow. After the second

world war, when the British withdrew, the Chinese moved up the vacancy chain

(White, 1970), with Indians and Malays following behind.

54

Today, Chinese power permeates the various spheres of economy, politics, education,

and culture in Singapore, leaving the ethnic minorities, particularly Malays, in positions

of significant disadvantage (Rahim, 1998; Lee, 2006). To be sure, there are many poor

Chinese in Singapore (that is, ethnicity crosscuts class among the Chinese), but simply

“being Chinese” has status benefits. If Blumer (1958:4) is right that people tend to

perceive of ethnicity in categorical terms: that is, as a “sense of group position”, then

belonging to the dominant ethnic group is important, independent of class.

An important aspect of ethnic stratification in Singapore is Chinese’s and Indian’s

disproportionately greater access to higher education. In 2000, 12.6% and 16.5% of

Chinese and Indians were university graduates, while only 2.0% of Malays were

university graduates (Lee, 2006). The educational advantages of Chinese and Indians

may be due to several factors:

First, Chinese and Indians are much more likely than Malays to come from privileged

family backgrounds. The 2000 Census of Population revealed stark differences in the

median monthly household incomes of ethnic groups: Chinese households earned a

median monthly household income of $3,848, Malays: $2,708 and Indians: $3,387. That

family resources are such important determinants of educational access in

contemporary societies (Lareau, 2000), will help to partially account for why the richer

Chinese and Indians are more educationally advantaged than the poorer Malays.

Second, education is highly valued in the Chinese and Indian cultures. During the

period of the dynasties, formal examinations were an integral part of state

administration in the Chinese mainland. There was a highly pragmatic side to the

education, in that examinations were being mobilized as a means to select the most

competent administrators for the emperor’s service. The practice of education in

Singapore mirrors this ancient Chinese model. Today, a rigorous examinations process

selects the best candidates for the most influential jobs in the state sector. Rigorous

55

private tuition regimes have become the norm among Chinese families. Meanwhile,

children are increasingly seeking psychiatric help to cope with examination pressures.

Third, Chinese use education to hoard opportunities for themselves with the elite

Special Assistance Plan (SAP) schools being a major categorical tool in this regard. As

SAP schools teach both English and Mandarin as first languages, they inevitably

exclude many Malays and Indians. The mission schools are another categorical

mechanism. Large and influential networks among alumni ensure the sustained

channeling of wealth and resources into mission schools. These schools select students

based on legacy admissions and as mission schools are Christian schools, Malays (who

mostly are Muslim) do not attend.

To exacerbate matters, Malays (and to a lesser extent, Indians) have to contend with

unfavourable stereotypes being levelled against their racial category. Primary school

textbooks have often portrayed ethnic minorities as being in less prestigious work such

as “bus driver” or “housekeeper” for Malays and “zookeeper” or “policeman” for

Indians. By contrast, Chinese are represented favourably as “teachers”, “doctors” and

“principals” (Barr, 2006)!

DATA AND MEASURES

Data sources

I rely on personal network data from the Project Network Survey conducted in Singapore

between February and July 2005. The valid sample size is 989 Singapore citizens and

residents aged between 25 and 55 years. While there are several national surveys in

Singapore which focus on community development and relations (e.g. Housing and

Development Board, 2000; Ministry of Information and the Arts, 2000; Department of

Statistics, 2001), this is the first study which aims specifically at describing the personal

networks of Singapore citizens and residents in substantial detail. The data was

56

collected by a reputable and experienced survey research company, AC Nielsen, and

conducted in three languages, English, Mandarin or Malay, whichever suited the

respondent. Most of the interviews were administered by middle-age women as they

are often perceived to be less threatening than males or younger interviewers (see Lang

and Secic, 2006). Each interview lasted about an hour, and was conducted at the door of

the respondents’ homes.

Social capital measures

As in Fischer’s Northern Californian study (Fischer, 1982), I utilized a range of some

fourteen name generators (see Appendix A) to delineate the names, followed by name

interpreters enquiring about each name and the nature of his/her relationship with the

respondent.

The name generators were designed to cover a range of emotional, social and

instrumental scenarios, with the exact wordings modified to suit the Singapore context.

The name interpreters collected information such as the gender, ethnicity, age, housing

type and education level of the named alters, as well as the nature of the role

relationship and other tie characteristics (Marsden, 2005).

I used six measures of social capital and define each kind of social capital as the number

of network members who have a certain potential resource. These include: 1) number

of university graduates, 2) number of wealthy home owners 3) number of Chinese 4)

number of men 5) number of weak ties and 6) number of non-kin.

Each type of social capital represents potential access to specific kinds of resources: 1)

educational attainment is an important marker of social prestige and resources in many

contemporary societies. The well-educated have greater access to all kinds of material,

cultural and symbolic resources, 2) personal wealth is likewise a powerful resource.

Economic capital is a magnet for other kinds of resources, including social capital,

57

economic and social honour (Bourdieu, 1984), 3) Chinese ethnicity represents a

significant source of symbolic power in Singapore. As the ruling ethnic group, being

“Chinese” is a form of social power independent of class, 4) ‘male’ is another potentially

important resource given the highly patriarchal nature of Asian societies where men are

more likely than women to control valuable resources (Lai, 2008), 5) weak ties are

important pathways to novel and influential resources because of their boundary-

spanning nature (Granovetter, 1973; Lin, 1982), and 6) non-kin are important to the

extent that novel resources such as job information are typically found outside kinship

circles (Granovetter, 1973; Portes and Sensenbrenner, 1993).

Table 1 reports the types and amounts of each social capital by gender and ethnicity. I

rely mainly on OLS and negative binomial regressions to estimate the sources of the

respective kinds of social capital. My strategy consists of adding variables (representing

sources) in the sequence of a typical life course and noting the changes in gender and

ethnic coefficients.

While all the measures of social capital are based on count data, some of the

distributions are more skewed than others -- for example, the distributions of university

graduates, private housing dwellers and weak ties are highly skewed to the right (with

variances far exceeding the means), implying the need for negative binomial regressions

instead of the more conventional OLS. By contrast, the distributions of male, Chinese

and non-kin social capital were much less skewed. A square-root transformation was

applied to these distributions to make them more normal before proceeding with OLS

regression.

58

TABLE 1. NUMBER OF TYPES OF SOCIAL CAPITAL BY GENDER AND ETHNICITY

SOCIAL CAPITAL

Male Female Male/ Female

diff.

Chinese Malay Indian Chinese/Malay

diff. Number of university graduates

1.02 .99 ns 1.24 .21 1.00 ***

Number of private housing dwellers

1.02 1.16 ns 1.38 .33 .79 ***

Number of Chinese 4.63 4.18 * 5.98 .95 1.30 *** Number of men 4.53 1.77 *** 3.07 2.66 3.04 * Number of weak-ties .76 .48 *** .69 .39 .46 *** Number of non-kin 4.10 3.32 *** 3.70 3.41 3.87 ns

*P < .05 **P < .01 ***P< .001

Causes of social capital

Keeping with a life course approach, I entered the independent variables in a step-wise

sequential manner, beginning with ascribed characteristics: gender, ethnicity and age,

followed, by achieved characteristics: education, work, household income, family

formation, and voluntary associations, one at a time.

Gender is a dummy variable, with female assigned ‘1’ and men: female = 0. Ethnicity is

represented by two dummy variables: Chinese and Indian, with Malay as the reference

category. Age is entered in linear and quadratic forms, since research indicates that

social involvement tends to increase with age, peaks at middle life, and declines in the

later years (Mirowsky and Ross, 1999).

Education is entered as two dummy variables: ‘middle’ education and ‘high’ education.

The middle education category comprises respondents with at most secondary school

education, vocational training, or junior college qualifications. The high education

59

category comprises respondents with polytechnic or university degrees. The reference

category, ‘low’ education, comprises respondents with at most some secondary school

education.

Work is entered as a dichotomous variable, distinguishing between respondents in paid

work and non-paid work. Like education, work is an important milestone in the life

course. Work represents new opportunities to meet others and build social capital

extending beyond school and kin. Unfortunately, paid employment is unequally

distributed in the social structure. In Singapore, women, despite having comparable

levels of education as men, are still more likely to remain at home, due in no small part

to the persistence of gender role ideologies in contemporary society (Coser, 1991).

Household income refers to the income of all household members combined. There

were 46 missing cases, but this is small relative to the total sample size of 989. As with

typical income distributions, there was a noticeable positive skew. A square root was

applied to the seventeen levels of the variable in order to make the distribution more

normal.

Family formation is represented by two dummy variables: ‘married’ and ‘kids less than

18 years’. Marriage and parenthood are important stages in the life-course with

significant consequences for social relationships (Moore, 1990). Marriage increases kin

commitment substantially as the couple and their two families become linked through

the marital bond (de Vries, 1996). Kin involvement increases even further when

children arrive, especially for women: as noted by Jacobs (1988 cited in McPherson and

Smith-Lovin, 1993:245), “childbearing may (often) represent a network bottleneck

sending men and women into very different structural career streams”.

Participation in voluntary organizations is entered as a dummy variable, denoting

whether or not the respondent is a member of any voluntary organization. 32% of

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respondents indicated being part of at least one voluntary organization. A clear

majority of the participation was in religious groups (e.g. small groups in churches or

Islamic religious classes) with a scattering of participation in associations such as

charity organizations, country clubs, sports associations, ethnic organizations, special

interest groups, neighbourhood associations, parent-teacher associations, and

professional organizations. I did not use number of associations as my measure of

social participation, since only a few respondents (less than 7%) participated in more

than one association.

The relatively low participation in voluntary organizations in Singapore can be

explained by at least two factors: first, the small geographical size of Singapore along

with its highly efficient and interconnected transport system makes it relatively easy to

rely on kin relations rather than on civic relations. Second, the short and shallow

history of democracy in Singapore potentially limits the growth of its voluntary

associations, and reciprocally, the weakness of voluntary associations helps keep the

level of democracy low (see Paxton, 2002). As compared to the United States, where the

average number of voluntary association memberships per person is 1.98, the level of

participation in voluntary associations in Singapore is very low: the average number of

voluntary association memberships in this study is only .42, which is on par with

countries like Japan (.49) and Romania (.42) (Table 1 in Curtis et. al., 2001).

Interaction effects

As organizational settings may be expected to generate social capital at different rates

for different social categories (of people), the testing of interaction effects forms an

important part of the analysis.

I focus on three organizational settings in particular: 1) higher education 2) paid work

and 3) voluntary associations, and estimate the extent to which their effects on the six

61

types of social capital are modified by gender and ethnicity. The interaction terms were

entered as follows:

Differential impact of institutional settings on varieties of social capital by ‘gender’:

- [Middle education x Female], [High education x Female]

- [Work x Female]

- [Association x Female]

Differential impact of institutional settings on varieties of social capital by ‘ethnicity’:

- [Middle education x Chinese], [High education x Chinese], [Middle education x

Indian], [High education x Indian]

- [Work x Chinese], [Work x Indian]

- [Association x Chinese], [Association x Indian]

The omitted categories are low education (i.e. completed primary and some secondary

school), male, Malay, not in paid work, and no involvement in voluntary associations.

I did not report the fine details of every model, as this would certainly overwhelm the

reader (i.e. 36 regression models in total). Instead, I summarize the results using a ‘yes

(if interaction effects are present) and no’ (if interaction effects are not present) format

(see Table 8).

RESULTS

Gender and ethnic inequality in social capital

Table 2 presents findings on two levels. At the broad level, we see dominant gender

and ethnic groups (i.e. men and Chinese) having more social capital than their less

dominant counterparts (i.e. women, Malays and Indians).

62

At a more specific level however, we see distinctive patterns of network inequalities by

gender and ethnicity: that is, women have lower access to men (- .83***), weak ties (-

.44***) and non-kin (- .26***), but equivalent access to university graduates (.03), private

housing dwellers (.13) and Chinese (- .11) relative to men, while Chinese have greater

access to university graduates (1.79***), private housing dwellers (1.46***), Chinese

(5.06***) and weak ties (.54***), but equivalent access to men (.07) and non-kin (.08),

relative to Malays.

These broad and distinctive patterns of network inequalities are consistent with the first

and second hypotheses, which state that 1) dominant gender and ethnic groups have

more social capital than less dominant gender and ethnic groups (H1) and 2) that

gender and ethnic groups tend to access distinctive forms of social capital (H2).

Categorical sources of gender and ethnic network inequalities

In subsequent regression models, I control for the effects of organizations and life

course variables, beginning first with education (Table 3), then paid work (Table 4), then

household income (Table 5), then family formation (Table 6), then voluntary

associations (Table 7). Adding controls in a sequential manner will help us better

understand how various organizations and life-course events contribute to the

distinctive patterns of network inequalities we see.

Age

Contrary to the literature which reports a peak in social capital during midlife

(Erickson, 2004), there is no such quadratic relationship between age (ranging from 25

to 55 years) and the kinds of social capital studied here. Instead, the association

between age and social capital is linear and negative.

63

TABLE 2. CATEGORICAL INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .03 .13 - .11 - .83*** - .44*** - .26*** Chinese 1.79*** 1.46*** 5.06*** .07† .54*** .08 Indian 1.54*** .90*** .35 .09 .17 .06 Age - .23*** .03 - .14** - .04** .04 - .06*** Age square - .03 - .03 - .05 .00 - .01 .02† Constant - 1.57 - 1.14 1.11 1.97 - .67 1.82 R square/BIC 2517.25 2756.11 .55*** .36*** 2104.31 .06*** N 988 987 989 989 989 989 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay

Table 2 indicates that older cohorts are less likely than younger cohorts to have social

capital such as university graduates (- .23***), Chinese (- .14**), men (- .04**) and non-kin

(- .06***).

One reason is cohort differences in education. The opening up of mass education in

Singapore beginning in the 1970s has benefited the younger cohorts in particular

(Chang, 1995). As older cohorts belonged to a poorer, less developed era of Singapore’s

history, they have had fewer opportunities to procure a good education.

With educational effects controlled for in Table 3, the effect of age on access to

university graduates, Chinese, men and non-kin disappears, suggesting that the

negative effect of age on social capital is driven primarily by older cohorts’ lower access

to education. Furthermore, the effect of age on access to private housing dwellers

changes from non-significant (.03 in Table 2) to highly significant (.19*** in Table 3),

suggesting that it is indeed the lack of education among older cohorts that suppresses

their access to wealthy social capital.

Education

64

Table 3 shows that higher levels of education are a substantial source of well-educated

(2.97***), wealthy (1.78***), Chinese (.75***), men (.17***), and non-kin (.42***) social

capital.

Controlling for education in Table 3, we see a sizable decline in the effects of Chinese

and Indian on access to university graduates and private housing dwellers, suggesting

that educational resources are a major factor explaining Chinese’s and Indian’s greater

access to well-educated and wealthy social capital, relative to Malays.

The fact that ethnicity remains highly-significant at the .001 level, also suggests that

there are other factors besides education that potentially explain ethnic inequalities in

educated and wealthy social capital. To add, Chinese are much more likely to have

Chinese networks, and again education explains some of this, but not completely. So

what are some of these other factors?

First, dominant ethnic groups may generally find it easier to add valuable contacts to

their networks because of the high social status of their ethnic group. Members from

high-status ethnic groups may appear as attractive network members to others, and

hence find it easier to add all kinds of individuals to their personal networks.

Second, ethnic culture plays an important role linking ethnically-similar individuals

together. Having a shared ethnic culture facilitates ease of communication and becomes

the basis upon which networks of social closure and ethnic homophily are established.

Third, controlling for education does not by itself equalize educational resources. A

Chinese and Malay may be both high school graduates, but because Chinese goes to a

better school, he/she ends up being in better social circles.

65

Notice that education does practically nothing to account for gender inequalities in

access to men, weak ties and non-kin (Table 3), which suggests that gender inequalities

in social capital are driven by factors other than education.

TABLE 3. EDUCATION AND INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .10 .19† - .10 - .83*** - .43*** - .26*** Chinese 1.10*** 1.07*** 4.91*** .03 .52*** .01 Indian .93*** .49* .22 .05 .15 - .00 Age .02 .19*** - .07 - .02 .05 - .02 Age square .00 - .02 - .05† .00 - .01 .02† Education (mid) 1.27*** .85*** .34* .03 .04 .27*** Education (high) 2.97*** 1.78*** .75*** .17*** .10 .42*** Constant - 3.03 - 1.93 .87 1.94 - .70 1.65 R square/BIC 2198.26 2622.12 .55*** .37*** 2117.65 .11*** N 988 987 989 989 989 989 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low)

Access to paid work

With ascribed characteristics and education held constant, access to paid work is

strongly correlated with access to non-kin (.26***). Controlling for work, the most

noticeable changes (between Tables 3 and 4) are the reduced effects of female on access

to weak ties and non-kin, suggesting that women’s lower participation in paid work is a

very important factor accounting for their lower access to weak ties and non-kin.

Although men and women in Singapore have equal access to educational attainment,

women lag behind men in labour force participation. This implies an inequality

mechanism that suppresses women’s ability to convert their human capital into labour

force participation. A salient source of female disadvantage is the persistence of gender

66

role ideologies emphasizing women’s ostensibly natural place in the home (and men’s

ostensibly natural place at work).

TABLE 4. WORK AND INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .14 .13 .08 - .81*** - .36** - .16*** Chinese 1.09*** 1.07*** 4.90*** .03 .51** .00 Indian .93*** .48* .20 .05 .13 - .01 Age .03 .18*** - .06 - .02 .06 - .02 Age square .00 - .02 - .04 .00 - .01 .02* Education (mid) 1.25*** .88*** .25 .02 .00 .22*** Education (high) 2.94*** 1.83*** .61** .16** .05 .35*** Working .12 - .17 .51** .06 .20 .26*** Constant - 3.12 - 1.80 .49 1.90 - .85 1.46*** R square/BIC 2204.31 2627.19 .56*** .37*** 2122.48 .12*** N 988 987 989 989 989 989 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work

Household income

With ascribed characteristics, education and work held constant, household income is

associated with knowing more university graduates (.45***), private housing dwellers

(.78***) and men (.09**) (Table 5). The most noticeable changes between Tables 4 and 5

are the reduced effects of Chinese and Indian on access to university graduates and

private housing dwellers, suggesting that household resources are important sources of

Chinese and Indians’ greater access to well-educated and wealthy social capital.

Household wealth may facilitate access to well-educated and wealthy social capital in

several ways. First, wealthy individuals are likely to move around in privileged social

circles, such as in elite clubs where they meet other advantaged people like themselves.

67

Second, wealthier people are more likely to live in private housing and may therefore

meet other wealthy residents. Third, wealthier people enjoy higher levels of

geographical mobility. As people travel far and wide, their networks are expanded

through meeting others who are similarly privileged and geographically mobile.

TABLE 5. HOUSEHOLD INCOME AND INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .05 - .02 .08 - .82*** - .34** - .16*** Chinese .90*** .77*** 4.90*** .01 .51** .00 Indian .83*** .21 .21 .04 .11 .00 Age - .01 .14*** - .06 - .02 .07† - .01 Age square .01 - .01 - .04 .01 - .02 .02* Education (mid) 1.00*** .45** .18 - .03 .05 .20*** Education (high) 2.47*** .92*** .52* .06 .21 .34*** Working .01 - .23† .51** .05 .29* .26*** Household income

.45*** .78*** .14 .09** - .17† .02

Constant - 3.93 - 3.36 .15 1.70 - .52 1.41 R square/BIC 2061.95 2376.89 .56*** .38*** 2036.98 .13*** N 953 952 954 954 954 954 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work

Family formation

There are two aspects of family formation that are of interest here: 1) being married and

2) having young children (less than 18 years). Both are significant turning points in the

life course with important consequences for social relations. Table 6 indicates that other

factors held constant, being married is associated with knowing less non-kin (- .13*), but

knowing more men (.11*).

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As marriage is normatively a time to focus on the family and devote energies to setting

up and maintaining a household, access to non-kin may be expected to shrink.

Concerning more men, research indicates that women are often kin-keepers and

sometimes managers of their husband’s networks (Lai, 2008).

TABLE 6. FAMILY FORMATION AND INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .06 - .03 .06 - .83*** - .36** - .16*** Chinese .87*** .77*** 4.90*** .01 .52** .01 Indian .75** .19 .25 .04 .17 .00 Age - .01 .14*** - .06 - .02 .08† - .01 Age square - .01 - .02 .00 .02* .00 .02* Education (mid) 1.01*** .46*** .16 - .03 .03 .20*** Education (high) 2.50*** .93*** .54* .07 .17 .33*** Working - .02 - .25* .55*** .07 .29† .24*** Household income

.45*** .79*** .10 .08* - .14 .04

Married .16 - .03 .17 .11* - .24 - .13* Kids < 18 - .39** - .13 .41* .07 .37* .05 Constant - 3.75 - 3.24 - .23 1.60 - .67 1.44 R square/BIC 2066.11 2388.56 .57*** .39*** 2044.35 .13*** N 953 952 954 954 954 954 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work, not married, no children below 18 years

Having children less than 18 years old is associated with having more weak ties (.37* in

Table 6), which is an interesting result when juxtaposed against the earlier finding that

marriage reduce relations with non-kin (- .13* in Table 6). It appears that whereas

couplehood strengthens kinship boundaries, young children reopen parents to the

outside world. Children are often brokers of relationships. Through their various

activities such as childcare, school activities, private tuition and sports, children provide

69

parents with opportunities to know other parents and develop other kinds of weak ties

(Erickson, 2004; Small, 2009).

Interestingly, having children (less than 18 years old) is associated with lower access to

university graduates (- .39** in Table 6). One possible reason is that children require

constantly available care, so parents may tend to concentrate more on helpers who are

free to help and do not have the education: folks such as ‘grandma’ or ‘grandpa’.

University graduates probably are too busy working (or caring for their own children)

to be much use.

Voluntary associations

Social participation is positively associated with many kinds of social capital: well-

educated social capital (.62***), wealthy social capital (.53***), Chinese (1.21***), men

(.26***), weak ties (.45***) and non-kin (.51***) (Table 7).

So why are voluntary associations such fertile ground for social relations? First, it could

be that joiners of voluntary associations are generally more sociable or gregarious to

begin with, and therefore are more likely to have diverse connections. Second,

voluntary associations may often have institutional linkages with other organizations:

for instance, the childcare centre that brings in the occasional stress management guru

or elementary school application advisor for parents, thus allowing them to know

people from outside the childcare centre itself (Small, 2009). Indeed, voluntary

associations expand the reach of personal contacts and are significant sources of diverse

ties for both men and women (Erickson, 2004; Bekkers et al., 2008).

The link between social participation and social capital may work in the reverse as well.

As voluntary associations may often recruit members through the networks of existing

members, having a large personal network increases one’s chances of being introduced

70

to a voluntary association. To better understand the nature of the associations/social

capital link, future research using longitudinal data is needed.

With voluntary associations controlled for, the negative effect of female on weak ties

and non-kin becomes stronger (i.e. more negative), suggesting that women’s more

active participation in voluntary associations (very data verifies this), alleviates their

lack of social capital.

TABLE 7. VOLUNTARY ASSOCIATIONS AND INEQUALITY IN SOCIAL CAPITAL

# university graduates

# private housing dwellers

# Chinese # men # weak ties # non-kin

Predictors Female .01 - .07 - .04 - .85*** - .42*** - .20*** Chinese .98*** .85*** 5.08*** .05 .62*** .09 Indian .75*** .19 .16 .02 .13 - .03 Age - .05 .11*** - .13** - .03** .05 - .04** Age square - .02 - .02 .00 .02* .00 .02* Education (mid) .94*** .40** .02 - .06 - .03 .14** Education (high) 2.39*** .78*** .24 .01 .03 .21** Working - .02 - .25* .55*** .07 .28† .24*** Household income

.41*** .78*** .07 .07* - .16 .02

Married .20 - .02 .18 .11* - .24 - .12* Kids < 18 - .43*** - .16 .37* .06 .36* .03 Associations .62*** .53*** 1.21*** .26*** .45*** .51*** Constant - 3.88 - 3.37 - .41 1.56 - .75 1.36 R square/BIC 2037.68 2366.30 .60*** .42*** 2038.39 .23*** N 953 952 954 954 954 954 †p < .10 *p < .05 **p < .01 ***p < 0.001 Omitted categories: Male, Malay, Education (low), not in paid work, not married, no children below 18 years, No participation in voluntary associations

71

Another noticeable change when voluntary associations is held constant, is that the

positive effect of Chinese on access to university graduates, private housing dwellers,

Chinese and weak ties becomes stronger, suggesting that Chinese’s lower participation

in voluntary associations (my data verifies this) suppresses their access to social capital.

Chinese have lower rates of participation in voluntary associations because they are less

likely than Malays and Indians to be part of religious associations. Practically all

Malays are (mosque-going) Muslims, and most Indians are either Muslims or Hindus.

Chinese are Buddhists, Christians, or Taoists, but many are free-thinkers and therefore

not affiliated with any religion or religious associations.

Interactions

To the extent that organizations such as universities, paid work and voluntary

associations generate social capital unequally across gender and ethnic groups,

categorical inequalities are being reproduced. Yet more than that, by testing

interactions, we are also interested to see if organizations have effects beyond the

powerful effects of access.

Higher education: Table 8 indicates that the relative effect of education on social capital

does not differ by gender or ethnicity. That is, education is an equally efficacious

generator of social capital, regardless of whether the person is male or female, Chinese,

Malay or Indian. Hence, the primary mode of network disadvantages among ethnic

groups appears not to lie in high education producing more social capital for some

ethnic groups than others, but in ethnic groups having unequal access to high

education, more primarily.

Paid work: Women are as likely as men to gain social capital from participation in paid

labour. As is the case for ethnic minorities and education, this finding suggests that

women’s deficits in social capital arise more fundamentally from their lower access to

72

paid labour markets, rather than from paid labour markets working more efficaciously

for men. Being in paid work also generates social capital equally well for ethnic groups.

Except for some marginal evidence that paid work generates non-kin social capital more

efficaciously for Indians (.29†), the majority results indicate a clear pattern of equal

relative payoffs by ethnic group. These general results are rather surprising, given that

there are such large gender and ethnic differences in the kinds of work people do. As

my data is based on name generators and therefore closer ties (Marin, 2004), it may not

have successfully captured the much broader set of weak and influential ties that work

and occupations help generate.

Voluntary associations: Women are especially likely to gain on weak ties (.39†) and non-

kin (.23**) when they join voluntary associations, suggesting that voluntary associations

are strong compensation mechanisms for women. It appears that women’s lower access

to paid work is freeing their time for participation in voluntary associations.

Voluntary associations are especially likely to increase Chinese’s access to other Chinese

(1.29***). One plausible reason is the ethnically homogeneous nature of many voluntary

associations in Singapore, especially religious organizations (such as churches and

Chinese temples). Also, as Chinese form the majority of residents in Singapore (75%),

the likelihood of having ties to Chinese rather than Malays or Indians is higher by

virtue of demography (Blau, 1977).

Interestingly, while voluntary associations are especially likely to increase Chinese

networks among Chinese (1.29***), they are especially unlikely to increase Chinese’s

access to weak ties (- .93**) and non-kin social capital (- .19†). These significant

interactions may be interpreted in another way and that is, voluntary associations are

especially likely to increase weak ties and non-kin among Malays (since it is the omitted

category). In sum, voluntary associations are especially useful generators of social

capital, not only for women, but for ethnic minorities as well.

73

DISCUSSION

Ascriptive categorical forms of stratification such as gender and ethnicity produce

distinctive forms of network inequalities. The case of Singapore illustrates that whereas

men tend to have more social capital such as men, weak ties and non-kin (but not

university graduates, private housing dwellers, Chinese and weak ties), dominant

ethnic groups tend to have more social capital such as university graduates, private

housing dwellers, Chinese social capital and weak ties (but not men and non-kin).

These distinctive patterns of access to social capital are a function of gender and ethnic

groups’ distinctive patterns of access to various types of organizations such as schools,

paid work and voluntary associations. My data illustrates that ethnic groups’ unequal

access to education (but equal access to paid work) and gender groups’ unequal access

to paid work and voluntary associations (but equal access to education) account for

much of why men and women, Chinese, Malays and Indians tend to have such

distinctive forms of social capital (i.e. H3).

Certainly, the exact nature of the links between ascriptive categorical forms of

stratification, organizational access and social capital will be expected to differ

depending on the specific conditions of societies. In Japan, for example, men continue

to outnumber women in colleges and universities (see Brinton, 1992:86). And in the

United States, blacks continue to be greatly disadvantaged in education, while some

minority groups such as East Asians have excelled (Kao, 1995). In other words, there

will be variations in the characteristic types of social capital that gender and ethnic

groups have access to, depending on societal variations in gender and ethnic groups’

access to organizational settings where social capital is formed.

So why have educational inequalities narrowed so considerably for men and women,

and yet remained so salient among ethnic groups in contemporary society? One reason

74

is that in modern societies, educational achievement remains highly-correlated with

race and socio-economic background (Lareau, 2000). While mass education has opened

up the educational landscape for many people, parental resources still play an

extremely important role determining who the eventual winners and losers are in the

education race. Well-to-do families have clearly an upper hand as elite parents are able

to impart to their children the relevant cultural codes needed for successful education,

hire private tutors, and maintain libraries of information at home. In contemporary

times, it is ethnic minorities rather than girls who are especially disadvantaged in this

area of household wealth and family privilege (Gamoran, 2001).

75

TABLE 8. SUMMARY OF INTERACTION EFFECTS

Does effect of

education on social capital vary by gender?

Does effect of

education on social capital vary by

ethnicity?

Does effect of working on social capital vary by gender?

Does effect of working on social capital vary by

ethnicity?

Does effect of associations on social capital vary by

gender?

Does effect of associations on social capital vary by ethnicity?

Type of social capital # university graduates

No No No No No No

# private housing dwellers

No No No No No No

# Chinese No No No No No [association] x [Chinese] =

1.29*** # men No No No No No No # weak ties No No No No [association] x [female] =

.39† [association] x [Chinese] = - .93**

# non-kin No No No [working] x [Indian] = .29† [association] x [female] =

.23** [association] x [Chinese] = - .19†

Omitted categories: Male, Malay, not working, no participation in voluntary associations †p < .10 *p < .05 **p < .01 ***p < 0.001

76

The opening up of mass education in 1960s, along with the establishment of the

Women’s Charter in 1961 has considerably narrowed educational inequalities among

men and women in Singapore. The heavy subsidization of tertiary education by the

state and the growing wealth of families have ensured that households could now send

both sons and daughters to the polytechnics and universities, and not just sons alone, as

in a generation ago. While there continues to be gender discrimination in some areas of

tertiary education (e.g. entry into medical school), the prospect of obtaining a university

education remains high for women (in some cases, higher than men). Instead, it is in

the area of paid work that gender inequalities are more salient, especially from the

viewpoint of women’s significantly lower participation in paid work and their higher

involvement in childcare.

The swift advancement of women in education has not been followed up by an equally

swift progress in women’s access to paid work. One reason is the persisting gender

script in contemporary societies, which fosters the categorical mindset that the place of

men is work, while the place of women is the home (Coser, 1991). Today, women are

still significantly less likely than men to be in paid work.

It is interesting that women and ethnic minorities experience their respective forms of

network inequalities at different points in the life course. My data suggests that

whereas women experience significant network disadvantages during the work/family

formation stage of the life-course, ethnic minorities experience significant network

disadvantages much earlier, during the education stage of the life course. Indeed, the

experience of network inequalities among men and women and ethnic groups is bound

up with such structural conditions such as gender scripts, ethnic categorization and life

course sequencing.

While women often experience network inequalities stemming from their lower access

to paid work, their greater participation in voluntary associations has helped alleviate

77

those network disadvantages to some extent. According to Table 8, women are

especially likely to gain on weak ties and non-kin when joining voluntary associations.

These findings illustrate that network deficits at one point in the life course can be

compensated at other points in the life course.

On the question of whether organizations add social capital unequally to social groups,

there appears to be a mixture of results. Most of the tests for interaction effects point to

an absence of conditional effects, but there were some important instances of

conditional effects – such as the heterogeneous impact of voluntary associations on

access to weak tie, non-kin, and Chinese social capital by gender and ethnic groups (see

Figure 8) (this grants some support to H4).

The general lack of conditional effects does not however imply the absence of

categorical inequalities. Much of the gender and ethnic inequalities in social capital

stem from gender and ethnic differences in access to organizations rather than in

organizations rewarding some groups better than others.

There are other categorical factors besides organizational access and personal resources

that possibly account for persisting network inequalities by gender and ethnicity. These

include: 1) the effects of stereotyping (which make individuals from some categories

more (and less) attractive as potential network members), 2) the different kinds of work

gender and ethnic groups do, which affect networking opportunities and demands, and

3) the role of gender and ethnic homophily.

This paper has shown that distinctive patterns of gender and ethnic inequalities in

organizational access and life course patterns produce correspondingly distinctive

patterns of gender and ethnic inequalities in access to varieties of social capital.

Without understanding the distinctive dynamics of ascriptive categorical forms of

stratification at the level of social structure, organizations and the life course, we would

78

not understand the distinctive distribution of different kinds of social capital by social

categories.

The nuanced nature of my results shows that when studying social capital, it is not

enough to simply ask: “who has more (or less) social capital?” Instead, we need to ask:

“who has more (or less) of what types of social capital and why?”

79

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Chapter 4 (Paper 2) Social Networks and Labour Market Outcomes in a Meritocracy

This paper examines the significance of personal contacts in job searches, in the context of Singapore’s meritocratic system. I show that in certain sectors, such as the state bureaucracy, social networking brings no distinct advantages as appointments are made exclusively on the basis of the academic credentials of the candidates. Thus, personal contacts are not always useful, especially in labour markets that rely heavily on the signaling role of academic credentials to match persons to jobs and allocate rewards. In contrast, personal contacts are more useful among less qualified job searchers in the private sector. INTRODUCTION

We know that personal contacts are generally useful for getting jobs (Granovetter, 1995

[1974]), changing jobs (Bian, 1994, 1997) and getting good jobs (Marsden and Hurlbert,

1988; Lai, Lin and Leung, 1998; Erickson, 2001). However, should we expect personal

contacts to work the same way in all kinds of labour markets? This seems a logical

question, but the relative role and usefulness of job contacts within and between labour

market contexts remain relatively unexplored in the literature.

Many researchers into the network theory of job searches argue that personal contacts,

whether offering nuanced information (Wanous, 1980), facilitating newcomer

socialization (Fernandez, Castilla and Moore, 2000) or providing timely influence (Bian,

1997), enable better job matches than non-network methods. Others like Granovetter

(1973), Montgomery (1992), Burt (1992) and Lin (2001) posit that certain network

characteristics such as weak ties, structural holes and high-status contacts can be more

important than matching methods. I argue that while matching methods and network

characteristics are important, labour market contexts influence the extent to which

either is useful.

More specifically, using representative data from Singapore but drawing comparisons

with information on the United States and other countries, I show that “who you know”

does not always lead to better job outcomes, especially where recruitment and

86

promotion procedures are highly formal and bureaucratized. The heavy reliance on

academic credentials for choosing the best candidates in Singapore’s state sector reflects

a situation where educational and labour market hierarchies are tightly-linked and

hence impermeable to informal influences such as networking.

Broadly, this paper contributes to our growing understanding of the effects of

institutional contexts on the role and value of job contacts. It argues that cultural

explanations do not suffice in explaining variations in the use and value of job contacts.

INSTITUTIONAL EXPLANATIONS

Rates of contact use vary by national context. In the United States, between 50% and

65% of Americans report using contacts (Granovetter, 1974; Lin, Ensel and Vaughn,

1981; Campbell and Marsden, 1990; Lai, Lin and Leung, 1998). Rates are noticeably

lower elsewhere. In East Germany (under Communism), 40% found jobs through

personal contacts (Völker and Flap, 2001). In the Netherlands, the percentage is

between 35% and 50% depending on the period (see DeGraaf and Flap, 1988; Moerbeek

et al., 1995). In Japan, the percentage is about 35% (Watanabe, 1987). In China, it about

45% (Bian, 1997), although another study found that only 23% of men and 14% of

women used a contact when finding their first job (Lin and Bian, 1989).

Job contact effects on post-hire outcomes also differ between countries. Although

studies indicate that high-status contacts consistently yield better post-hire outcomes

(e.g. see Lin’s summary of studies, 2001:84), the sizes of these effects may vary

according to which society is being studied. Some studies have found a positive effect

of contact use on post-hire outcomes (e.g. Coverdill, 1998 in the United States

concerning wages and Bian, 1994 in China concerning occupational change and non-

state to state sector mobility), while others have found no or negative effects (e.g.

Korennman and Turner, 1996; Lin, 1999; Mouw, 2003, all in the United States).

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Variations in contact use and their effects within and between countries signal a need to

explore their structural antecedents.

While laypersons and scholars alike may be tempted to rely on cultural explanations to

account for national variations, cultural explanations could obscure the important role

of institutional factors. Culture may be important for providing individuals with

“routine scripts” and “lines of action” (Swidler, 1986:277), but culture often intersects

with institutions to shape behaviour. Noting the role of job contacts in a variety of

countries, Granovetter (1995) notes that while there may be somewhat more cultural

emphasis on strong ties in countries such as China and Japan, most of the reasons for

network differences seem to lie in institutional variations. Lin (1999) concurs, arguing

that national differences in the use of job contacts are likely the result of institutional

factors, for instance, the association between specific educational institutions and

methods of job allocations and searches. Building on this argumentation, this paper

examines how education and employment systems impact the role and payoffs of

contact use in countries as diverse as Singapore and the United States.

Singapore is an excellent case study because it is located at one ideal-typical extreme of

a distribution of meritocracy (Evans and Rauch, 1999). In their innovative paper, Evans

and Rauch (1999) devised a “Weberianness scale” to measure the extent to which a

group of 35 countries possess strong state bureaucracies characterized by meritocratic

recruitment and predictable career ladders. The fact that Singapore was rated at the top

of this scale makes it an ideal fieldsite for testing the relationship between bureaucratic

labour market structures, job contacts, education and status attainment. Although

Evans and Rauch (1999) did not include the United States in their study, Evans believes

that the United States is on the whole less “Weberian” than Singapore (per. comm.).

VARIETIES OF CAPITALISM

My analysis draws upon a distinction in the varieties of capitalism literature (Hall and

Soskice, 2001): “liberal market economies” (LMEs) and “coordinated market

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economies” (CMEs). Briefly stated, LMEs and CMEs are ideal-type economies situated

at the extreme ends of an array of nations. While multiple features distinguish LMEs

and CMEs, one feature is the interrelationship between the supply (education) and

demand (employment) sides of the labour market (Allmendinger, 1989).

In LMEs, the supply and demand sides of the labour market are “loosely-coupled”: that

is, education systems in liberal economies send only weak signals to employers about

the skills and qualifications of the labour pool. In CMEs, the supply and demand sides

of the labour market tend to be “tightly-coupled” with education systems sending

strong signals to employers about their potential employees. In the literature, the

United States is often associated with LMEs, while countries like Norway and West

Germany are more often associated with CMEs (Allmendinger, 1989; Mayer, 2005).

Based on the distinction between loosely and tightly coupled, Singapore is more aptly

described as a CME.

LMEs and CMEs may be further distinguished by standardization of educational

provisions and the stratification of educational opportunities (Allmendinger, 1989;

Mayer, 2005). In LMEs, schools have greater flexibility in the design and administration

of their educational provisions. They have few prescribed national guidelines or

standards. National examinations, particularly at the elementary and junior high school

levels, are almost non-existent, and the idea of educational tracking at a young age is

virtually unknown. Since students do not sit for national examinations, the signaling

role of grades and certificates in LME labour markets is a less important issue.

Educational certificates are of relatively minor importance in LMEs as work lives by

individual attempts to make good earnings (Mayer, 2005:36). While a university degree

is qualitatively different from a high-school diploma, because of the large number and

types of colleges and universities in LMEs, it is difficult, even with visible degree and

grade differences, to judge between so many different types of graduates. The symbolic

role of modern education compounds the problem -- as Dore (1976: ix) notes: “…not all

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schooling is education… much of it is mere qualification-earning”. Given the uncertain

meanings attached to degree, diplomas and grades in LMEs, employers may often rely

on network mechanisms to select the best candidates, in addition to relying on formal

qualifications.

CMEs are characterized by a standardized and examination-based school system.

CMEs whether West Germany, Norway (Allmendinger, 1989), Japan (Dore, 1976;

Rosenbaum et al., 1990), Hong Kong, Korea, Taiwan or Singapore (Schmidt, 2006), are

united by the highly-significant role of qualifications for job allocation. The close

relationship between “school” and “job” starts early in elementary school, when

students are tracked into ability streams which set them up for certain kinds of

employment (Cheung, 1994). Given that education is itself a rigorous sorting process,

employers “can rely on information given by certificates and do not have to screen or

train individuals entering the labour force” (Allmendinger, 1989:60).

To be clear, it is not that credentials are of little importance in LMEs. Standardized tests

such as the SAT, GRE and GMAT have been an integral part of the North American

tertiary education system, and doing well in them continues to be extremely important

for gaining entry into prestigious universities. Furthermore, entry into professional

careers requires specific forms of education, often in professional schools (DiMaggio

and Powell, 1983). The difference between CMEs and LMEs is that the sorting process

begins much earlier in the former (Turner, 1960). Furthermore, while LMEs may use a

combination of credentials and networks to determine job hires, CMEs pay much more

attention to credentials alone. In the Singapore CME, education alone makes for all

kinds of great matches, particularly in highly-meritocratic jobs (MacDougall and Chew,

1976; Tan, 2004). The argument advanced in this paper is that in CME type labour

markets where education and employment systems are tightly-coupled, personal

contacts are generally ineffective. By contrast, in LME type labour markets where

education and employment systems are loosely-coupled, personal contacts are more

useful.

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SINGAPORE CONTEXT

In addition to its CME categorization, Singapore has been called the “quintessential

developmental state” (Castells, 1988:4). The most pressing objective of a developmental

state is economic growth, even if at the expense of political freedoms (Kim, 1994). In the

literature, the developmental state is often contrasted with the liberal market economies

(LMEs) of Britain and the United States where the government’s role in the economy is

more regulatory than interventionist (Wade, 1990; Woo-Cumings, 1999).

Between 1965 and 1984, Singapore saw the rise of an “administrative state”, whereby

politics was removed from civil society and national decisions devolved to government

bureaucrats (Chan, 1989). Because the administrative state is technocratic, its mode of

leadership renewal is often informed by an elitist and meritocratic selection process

based on academic achievement rather than personal charisma (Barr, 2006). In practice,

the Singapore case is very similar to the French developmental state whose

administrative elite is recruited from France’s grande ecoles. These grande ecoles lead to

well-paid and prestigious positions within the civil service and state enterprises, thus

reinforcing France’s reputation as a “Republic of Valedictorians” (Loriaux, 1999:240).

As in France, the Singapore state is built upon a system of identifying and grooming

scholars for high-level government work. The Singapore state is also much like ancient

China’s Confucian Mandarinate, whereby examination stalwarts are sponsored into the

highest positions within the state bureaucracy (Barr and Skrbis, 2008).

The developmental state draws its ideological power and legitimacy from its sterling

economic performance and heavy reliance on human capital (Johnson, 1982; Castells,

1988). Without economic growth, the developmental state quickly loses its political

legitimacy and must find a way to restore confidence among the electorate. The state’s

answer to electoral expectations is, ironically, to intervene even more in industrial

allocations (what jobs to do) and educational policy (what subjects to study). In the

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Singapore developmental state, human capital development, technocratic planning and

political stability are cited as fundamental engines of economic growth (Castells, 1988).

The eviction of Singapore from Malaysia in August 1965 (due primarily to Singapore’s

persisting stand on meritocracy and its subsequent refusal to accede to Malaysia’s racial

politics), allowed the ruling People’s Action Party (PAP) to play on public insecurities

and propagate an ideology of survivalism (Chan, 1971; Tremewan, 1994). The lack of

natural resources in the island city-state, coupled with its geographical realities

(particularly its small size) enabled the Singapore state to generate a discourse

underscoring the redemptive role of an important substitute: human capital.

Unlike other East Asian economies (e.g. Japan, South Korea and Taiwan) which built

their post World War II economies on the strength of entrepreneurial ventures initiated

by local capitalists (hence the rise of economic giants such as Toyota, Honda and

Samsung), Singapore chose the path of MNC-led growth (Schuman, 2009). To stem the

tide of growing unemployment, the state elites marketed Singapore as a low-cost

manufacturing base for foreign capital (Castells, 1988). During the 1960s and 1970s,

American and European companies were looking for offshore manufacturing bases for

their electronics sector, and Singapore had by that time, an attractive mix of developed

infrastructure, tax incentives, and educated labour (Castells, 1988; Tremewan, 1994).

Today, multi-national companies (MNCs) continue to be an important part of

Singapore’s economic landscape, but competition has certainly intensified with MNCs

seeking out cheaper locations (Ngiam, 2006). To remain competitive, Singapore has had

to re-invent itself, i.e. upgrade its human capital and technological base while keeping

wages in high-end industries relatively low. The latest direct foreign investments have

been in the areas of pharmaceuticals and biotechnology -- human capital intensive

spheres (Pereira, 2008).

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Singapore’s powerful state sector has three important sets of institutions: the civil

service; statutory boards; and state enterprises (otherwise known as government-linked

companies or GLCs). The main criterion for entering the state sector is good academic

performance (Neo and Chen, 2007). By enforcing meritocracy within the state

bureaucracies, political elites can select the most talented individuals (Quah, 1998). To

attract and keep the best talent, bureaucratic salaries in Singapore are about 10 percent

higher than wages in comparable private sector positions (Evans, 1995). Although the

state sector employs only about 20% of the workforce, its contribution to GDP is almost

45% (Castells, 1988).

Singapore’s rigorous academic tracking system extends into the military service that all

18-year-old Singaporean males undergo. Typically, those with excellent GCE ‘A’ level

scores are assigned to scholar platoons for officer-cadet training (OCS) and are

considered for prestigious government scholarships to top universities abroad. After

their three to four year stints, these officer-cadets return to Singapore to serve their

bond for their state sector employer (Barr, 2006). Depending on national needs, some

are seconded to state enterprises (GLCs) where they are groomed for important roles

mediating the link between state initiatives and free market.

Like the civil service, the GLCs are known to offer overseas scholarships to attract

young talent and bind these young people for six to eight years (see Chan and Ng,

2000:295/6). As state enterprises, GLCs often have access to the civil service’s pool of

talented elites. Indeed, some high-ranking civil servants are known to sit on the boards

of GLCs, and a few are sequestered to them full time (Krause, 1989:443; Worthington,

2002). GLCs have great economic power. One Singapore study found that although

GLCs “are no more or less liquidity-constrained in their investment decisions than their

private sector counterparts”, they are “rewarded in financial markets with a premium

of more than 20 percent” (RamÃrez and Tan, 2003:20).

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The private sector tends to be less focused on credentials than the state sector. In

Singapore, the private sector comprises two major groups: the multinational companies

(MNCs), and the large but relatively powerless small business sector (or ‘SMEs’

standing for small and medium-sized enterprises). These SMEs value education, but

they do not enforce it to the same exacting degree as the state sector. We may expect

social networking to play a more active role in entering the SMEs (Tong and Yong,

2002), and there is anecdotal evidence that in Singapore’s high-end banking industry

recruitment is based predominantly on old boy/girl networks.

Although Singapore contains three main ethnic groups: Chinese, Malay and Indian,

Chinese predominate in the private sector arguably because during British colonial rule,

they were assigned by the British to trade and commerce, with many working as

coolies, shopkeepers and middlemen agents facilitating trade relations between the

Europeans and locals (Visscher, 2007). Traditionally, then, Chinese have concentrated

in sectors such as retail and wholesale, construction and light manufacturing, and

banking. These industries tend to be network-based rather than human capital-based

(Chan and Ng, 2000).

The three analytical frames I have adopted: 1) meritocracy and Weberianness, 2) CME

versus LME and 3) the developmental state, while distinct ideas on their own, are

interrelated in practice. Meritocracy creates a system whereby the best are allocated to

the best jobs in the state sector. Elite civil servants are transformed into technocrats and

economic agents whose mandate is to fulfill the economic goals of the developmental

state. The growth of the economy through human capital development and other

systematic and ‘Weberian’ means strengthen the citizenry’s belief that educational

qualifications are the most important signal in labour markets (i.e. CME). When

education and labour markets operate in meritocratic and hence predictable ways (and

is accompanied by high economic growth), the political legitimacy of the state is

enhanced.

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PROPOSITIONS

According to one influential school of thought, institutions refer to the set of

“constraints and rules” which exist to create order and reduce uncertainties in

exchanges between social systems (North 1991:97). These constraints and rules make

institutions predictable: over time, participants become familiar with the institution’s

incentive structure and orient their behaviour accordingly.

A prevailing institutional rule of education-based meritocracies is that jobs are allocated

based on ‘what you know’ rather than ‘who you know’. According to this rule, job

allocation should depend on achieved criteria such as formal qualifications and

accumulated skills rather than ascribed characteristics such as gender, ethnicity, family

background, or social connections. In meritocratic markets, criteria other than human

capital will interfere with the selection of the most competent workers (Reskin and

McBrier, 2000). To the extent that developmentalism is sustained in a meritocracy, we

should expect to see job seekers more reliant on educational resources than personal

contacts.

Proposition 1: In highly-meritocratic societies where educational credentials are highly

sought after by employers as evidence of future productivity, job seekers are less likely to

use personal contacts.

As credentials are highly-valued in meritocratic society, we should expect to see well-

educated job seekers relying on their hard-earned credentials. Meanwhile, individuals

who lack credentials will have to rely on alternative strategies such as job contacts. This

principle of substituting social capital for a lack of human capital is reported in studies

of ethnicity and immigration where individuals from lower-status ethnic groups rely on

personal contacts to enter ethnic economies (Light and Gold, 2000; Sanders, Nee and

Sernau, 2002).

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Proposition 2: In highly-meritocratic societies, highly-educated individuals are less likely

than lower-educated individuals to rely on personal contacts during job search.

Assuming that well-educated job seekers are more likely to enter meritocratic jobs than

lower-educated job seekers, and that meritocratic jobs are likely to value credentials

over personal contacts, I hypothesize that well-educated job seekers are less likely than

lower-educated job seekers to experience added returns from using job contacts.

Proposition 3: In highly-meritocratic societies, the well-educated are less likely than the

lower-educated to experience added returns (i.e. earnings) from job contacts.

Individuals with sterling academic results are the preferred candidates in the state

sector. Since coming to power in 1959, the former Prime Minister, Lee Kuan Yew had

always pushed the meritocratic principle in his policies. In the words of Lee himself in

a 1961 speech (in Quah 1998:111):

I am in favour of efficient service. The brighter chap goes up and I don’t care

how many years he has been in or he hasn’t been in. If he’s the best man for the

job, put him there.

While the meritocratic ideology came from Lee, its implementation was often entrusted

to his Finance Minister, Dr Goh Keng Swee. Goh’s version of meritocracy was at times

even more exacting than Lee’s. Holding a doctorate in Economics from the London

School of Economics (LSE), Goh “placed a high premium on intellectual ability and

academic brilliance, rather than experience… and as Goh had carte blanche to hire

anyone from the list of government scholars given to him, he paved the careers of many

young officers” (Neo and Chen, 2007:163). This “best man” policy was recently

reiterated by current Prime Minister Lee Hsien Loong, in a conversation with Charlie

Rose (reported 16 April 2010 in the Straits Times): “The whole of our system is founded

on a basic concept of meritocracy. You are where you are because you are the best man

for the job, and not because of your connections or your parents or your relatives.”

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Based on Singapore’s strongly meritocratic state structure, we would expect the

following two patterns:

Proposition 4a: Job contacts are less likely to facilitate entry into the meritocratic state

sector.

Proposition 4b: Job contacts are less likely to pay off in the meritocratic job sector.

In addition, we would also expect job contacts to be less likely than formal mechanisms

to facilitate entry into industries that emphasize formal credentials.

Proposition 5: Job contacts are less likely to be associated with entry into formal

industries such as public administration and defence, health and social work and

education.

High-status job contacts

A consistent finding is that high-status contacts create better post-hire outcomes for job-

seekers (Lin, 2001), arguably because high-status contacts provide better access to

resources and thus wield greater influence. Therefore, it is important to study the role

of high-status contacts, in addition to contact use alone (Mouw, 2003). High-status

contact use is a more targeted measure of social capital as it specifies the status of the

job contact being mobilized.

I hypothesize that if a social system is highly meritocratic, then high-status contacts

(even though they embody better resources) should not provide additional advantages.

That is, the economic payoffs associated with using a high-status job contact should not

surpass the economic payoffs associated with using a non-high-status contact.

Proposition 6 will be stated as follows:

Proposition 6: In a highly-meritocratic society, high-status social capital will not lead to

better earnings.

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Proposition 7 is like Proposition 3. It asserts that well-educated job seekers are less

likely than lower-educated job seekers to experience added returns from social capital.

In highly-meritocratic societies, the payoffs to social capital should tend to be lower for

people with educational advantages.

Proposition 7: Well-educated contact users are less likely to experience added returns

from high-status contacts than less-educated contact users.

DATA AND METHOD

I analyze data from the 2005 Project Network Survey, using a sub-sample of 656 currently

employed Singaporean adults aged between 25 and 55. The survey was designed to

better understand the nature of personal communities in multiethnic Singapore. Like

Fischer’s Northern Californian study (Fischer, 1982), the survey employed a range of 12

name generators to delineate the names, followed by questions about each network

member and the nature of the ties. The exact wording of the questions was modified

(after pre-tests) to suit the Singapore context. To ensure quality, the data were collected

with the help of a highly reputable market research company, ACNielsen.

Following Granovetter’s (1974) study, the survey included a question about how

respondents found their current jobs. As people often find their jobs through a

combination of means (Montgomery, 1992), a multiple response question was called for.

The options were the following: 1) I saw an advertisement in a newspaper (or other

sources of media); 2) I found out through an employment agency; 3) I submitted an

application; 4) Someone I didn’t know contacted me and said that I had been

recommended; 5) I asked friend/person who told me about the job; 6) A friend/person

who knew I was looking for a job contacted me; 7) A friend/person who didn’t know I

was looking for a job contacted me; and 8) Others. Respondents who indicated options

5, 6 or 7 were assigned ‘1’ on the job contact variable, while the remaining respondents

were assigned ‘0’.

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Table 1 presents information about the sample. Most of the respondents are between 40

and 44 years of age (23.3%), although other age categories are represented as well.

Males and females constitute 58.4% and 41.6% of the sample respectively; this uneven

gender distribution is due to men’s greater participation in paid labour markets than

women. As the numerically dominant ethnic group, Chinese make up 67.8% of the

sample, while Malays and Indians make up 18.6% and 13.6% respectively. The sample

distinguishes between three educational groups: 25.0% have ‘low’ levels of education

(i.e. no formal education or some secondary education), 40.9% have ‘middle’ levels of

education (i.e. completed secondary school, technical school or pre-university) and

34.2% have ‘high’ levels of education (i.e. polytechnic or university graduate). Of the

respondents, 24.3% are employed in public sector jobs (comprising the civil service,

statutory boards and GLCs) while 55.4% and 20.3% are employed in the small business

sector (SMEs) and multinational companies (MNCs) respectively. 91% are fully

employed, and 9% are employed part-time.

Of the 656 respondents, 233 were contact users (35.5%). This percentage of 35.5% is

substantially lower than the percentages in the United States (50% to 65%), but closer to

the percentages in Japan (35%), the Netherlands (35%-50%), East Germany (40%) and

China (25%-45%). An earlier Singapore study conducted by Bian and Ang (1997:1002),

found that 35% of their Singaporean respondents had used a personal contact to find a

job: this is almost identical to the current study’s 35.5%.

Of all the contact users, 77.3% used an intimate tie (i.e. ‘close’, ‘quite close’ or ‘very

close’) to obtain their current jobs. This concurs with findings in the literature, which

suggest that job-seekers in predominantly Chinese societies tend to rely on strong ties

during the job search (Bian, 1997; Bian and Ang, 1997). Among contact users, friends

(57.6%) and kin (23.1%) were most likely to be relied upon, suggesting that strong-tie-

bridges are important sources of job information.

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Although Singapore is like China, a predominantly Chinese society where strong ties

are important for job matching, the reasons for mobilizing strong ties are possibly

different depending on the country. In China, strong ties are mobilized to get around

bureaucratic structures of government and facilitate illegal job changes. In Singapore,

strong ties are important because they aid the selection of reliable workers into private

sector jobs (see Bian and Ang, 1997).

Outcome variables – Contact use and Earnings

The dependent variables are either contact use or earnings (per month) depending on

the analysis. Contact use is dichotomous. Earnings are measured by the square root to

the numeric codes representing each of 17 earning categories.

Focal independent variables

Depending on the hypothesis being tested, the focal independent variable is either: 1)

used a job contact (vs. did not use a job contact) or 2) used a high-status job contact (vs.

used a non-high-status job contact). In the latter, the respondent was asked to report

whether the job contact had a: 1) much lower status than the respondent, 2) lower status

than the respondent, 3) a bit lower status than the respondent, 4) same status as the

respondent, 5) a bit higher status than the respondent, 6) higher status than the

respondent or 7) much higher status than the respondent. I dichotomized the variable:

respondents who indicated 5, 6 or 7 were considered to have used a high-status contact

(1), while the rest are considered to have used a non-high-status contact (0).

The problem of contact use

One problem with studying contact use and post-hire outcomes is that one never really

knows whether the contact affected the post-hire outcome or if another means of job

search used in tandem with the contact was more important (Montgomery, 1992). One

solution is to confine the analysis to the early stage – that is, study the sources of contact

use without seeking to model the effects of contact use on post-hire outcomes.

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TABLE 1. DESCRIPTIVE STATISTICS OF SAMPLE OF SINGAPORE CITIZENS AND PERMANENT RESIDENTS (N = 656).

RESPONDENTS’ PERSONAL CHARACTERISTICS Age: 25-29 years 11.9% 30-34 years 16.2% 35-39 years 17.4% 40-44 years 23.3% 45-49 years 17.7% 50-55 years 13.6% Gender: Male 58.4% Female 41.6% Ethnicity: Chinese 67.8% Malay 18.6% Indian 13.6% Employment status: Full-time 91.0% Part-time 9.0% Education: ‘Low’ education ( No formal education or some secondary )

25.0%

‘Middle’ education (Completed secondary or technical or pre-university )

40.9%

‘High’ education (Polytechnic, professional qualification, University )

34.2%

Work sector: Private sector – Small business sector (SMEs) 55.4% Private sector – Multinational Companies (MNCs) 20.3% Public sector – Civil service, statutory boards and GLCs 24.3% JOB SEEKING TIE CHARACTERISITCS: Proportion of job contact users 35.5% Role relations of contact persons: Kin 23.1% Friends 57.6% Coworkers/supervisors 18.5% Neighbors .008% Tie strength with contact persons: Very close 26.9% Quite close 26.9% Close 23.5% Not that close 21.0% Distant 1.7% Median tie strength ‘Close’

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Another less restricting solution is to measure the extent to which multiple search

methods are used by job seekers (i.e. check the extent of multiple responses) and then

decide whether to proceed with post-hire models. If the extent of multiple search

methods is small, the researcher may justifiably proceed with the modeling. If the

overlap in big, the researcher may refrain or proceed while stating the limitations.

In my case, the number of job seekers who reported using a combination of methods

(formal and informal) was extremely small: 2 out of 656 respondents. Almost all

respondents indicated either using a job contact (231) or some formal mechanism (407)

(with only 2 indicating both and 16 indicating ‘others’), suggesting that technically, the

problem of multiple search methods is not a serious one in this particular study.

But assuming that this figure is being underestimated due to factors such as

respondents choosing to report in terms of their most primary search strategy instead of

reporting multiple strategies (the question did permit multiple responses), then we need

other reasons for estimating post-hire models1. Above all, we have to acknowledge the

limitations and interpret the data with them in mind.

Controls

1 The problem of multiple search strategies notwithstanding, many scholars (e.g. Bian, 1994; Mortensen and Vishwanath, 1994; Fernandez and Weinberg, 1997; Coverdill, 1998; Fernandez, Castilla and Moore, 2000; Castilla, 2005; Antoninis, 2006; Loury, 2006; Behtoui, 2008; Stainback, 2008) have through the years, continued to estimate and report the impact of contact use on post-hire outcomes and publish their findings in top and reputable journals. Substantively, contact use reflects general properties which matter for status attainment: 1) contacts provide useful information that enable job seekers to self-select into jobs they expect to do well in, 2) contacts provide a smoother transition into the prospective firm (especially if the contact is from the firm) and 3) contacts are often willing to put in a good word on behalf of the job seeker. Each of these mechanisms may influence post-hire outcomes (such as earnings and tenure on the job) in substantial ways.

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The effect of the respondent’s education is represented by two dummy variables:

‘middle’ education and ‘high’ education, with ‘low’ education being the reference group

(see Table 1 for the meaning of the categories). Age and age square are used as proxies

for overall work experience. Gender, ethnicity and employment status are added as

further controls, with male, Malay and full-time work being the reference groups

respectively.

Interactions

I test a number of interaction effects:

a) [Job contact] x [Respondent has middle education]

b) [Job contact] x [Respondent has high education]

c) [Job contact] x [Respondent works in the state sector]

d) [High-status job contact] x [Respondent has middle education]

e) [High-status job contact] x [Respondent has high education]

The first two interaction terms (a, b) test Proposition 3, which predicts that payoffs to

contact use are lower for highly-educated individuals. The fourth and fifth interaction

terms (d, e) test Proposition 7, which predicts that payoffs to high-status job contacts are

lower for highly-educated individuals. The third interaction term (c) tests Proposition

4, which predicts that payoffs to contact use are lower for individuals working in

highly-meritocratic jobs (i.e. the state sector).

To test Proposition 2, I employ a binary logistic regression whereby I estimate the

effects of education, ethnicity, gender and age on the odds of using a job contact. It is

hypothesized that as education increases, the likelihood of contact use decreases. To

test Proposition 5, I simply compare the proportion of job contact users across various

industries. These industries include manufacturing, utilities, construction, wholesale

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and retail trade, hotels and restaurants, transport, storage and communications,

financial intermediation, public administration and defence, education and health and

social work.

RESULTS

1) Low level of contact use in Singapore

Of the 656 currently employed respondents, 233 reported using job contacts. This

percentage of 35.5% is substantially lower than the 50%-65% reported in North

American studies, suggesting that on average, contact use is a much less prevalent job

matching strategy in coordinated markets (CMEs) than in liberal markets (LMEs).

National differences in contact use is interrelated, I argue, with the way in which

education systems interface with employment systems in societies. In Singapore,

educational credentials send strong signals to employers about a candidate’s ability to

perform, while in the United States, these signals tend to be weaker and thus, are often

supplemented by additional signals such as personal contacts (see Mayer, 2005:38).

Likewise, the lower rate of contact use in countries like Japan (35%), the Netherlands

(35%-50%), East Germany (40%) and China (25%-45%) may be attributed to strong

linkages between educational qualifications and job allocations in these CME-like

societies (Allmendinger, 1989; Mayer, 2005). The range of contact use rates is notably

wide in China. Some scholars believe that as China modernizes, contacts have become

even more essential as bridges of institutional gaps (e.g. Bian, 2002). Other scholars (e.g.

Guthrie, 2002; Hanser, 2002) believe that the strengthening of institutions in China has

generally reduced contact use. A possible resolution for both these viewpoints is to say

that while contacts may be of reduced importance in China’s modernizing sectors, they

remain critically important in China’s less developed markets and job sectors.

2) Highly-educated individuals are less likely than lower-educated individuals to rely on job

contacts

104

Model 1 in Table 2 shows that highly-educated job seekers are less likely than middle or

low-educated job seekers to use job contacts (- .746*** for ‘middle’ education and -

1.220*** for ‘high’ education). This inverse relationship remains significant at the .01

level when ethnicity, gender and age are controlled for (in model 3). Model 3 indicates

that highly-educated respondents and middle-educated respondents are about four

times (1/.244 = 4.10) and two times (1/.463 = 2.16) less likely than low-educated

respondents to use job contacts respectively, suggesting that educational credentials

reduce a job seeker’s need to rely on job contacts.

Model 2 indicates that Chinese are more likely than Malays (and Indians) to use job

contacts (.435*). When ethnic differences in education are accounted for in model 3, the

Chinese effect on job contacts becomes even stronger (.709**), implying that their high

credentials suppress their use of job contacts. So the question becomes: if well-educated

people usually do not use contacts (model 1), and Chinese lead in education, why is it

that Chinese are still most likely to use contacts (e.g. .435* in model 2 and .709** in

model 3)? While Chinese culture is one plausible explanation, another explanation, this

time from an institutional viewpoint, would be Chinese’s active participation in the

network-intensive spheres of the Singapore economy.

Notice that when the effects of private sector firms (namely SMEs and MNCs) are

added in model 4, the impact of Chinese decreases from .709** (in model 3) to .618* (in

model 4) suggesting firstly that the active participation in private sector jobs by Chinese

is a substantial source of their high contact use. Furthermore, since the effect of Chinese

on contact use does not disappear but persists in model 4, we may argue that cultural

factors account for their active use of job contacts. However, such an argument must

remain tentative, since the models do not yet incorporate all relevant institutional

factors. In sum, the pervasive use of job contacts among Chinese is probably due to

some meaningful (albeit tentative) combination of cultural and institutional factors.

More research needs to be done, preferably between different kinds of Chinese societies,

to ascertain the actual size of the alleged cultural effect.

105

3) Job contacts are less likely to pay off for the well-educated.

Table 3 shows that job contacts are negatively associated with earnings (- .261***, model

1). When controls for respondents’ education, gender, age and ethnicity are added (in

model 2), the negative relationship remains significant at the .01 level (- .084**),

suggesting that job contacts are associated with downward mobility, net of other

factors. This downward effect could be interpreted to mean that job contacts are not so

much a strategy for getting ahead, as they are a substitute for lack of formal resources.

TABLE 2. BINARY LOGISTIC REGRESSION ESTIMATING THE EFFECT OF EDUCATION ON CONTACT USE

Predictors Model 1 Model 2 Model 3 Model 4 Middle education - .746***

(.474) - .770***

(.463) - .654** (.520)

High education -1.220*** (.295)

-1.409*** (.244)

- 1.217*** (.296)

Chinese .435* (1.545)

.709** (2.031)

.618* (1.855)

Indian - .034 (.966)

.150 (1.162)

.246 (1.278)

Female - .301 (.740)

- .223 (.800)

- .189 (.828)

Age .078 (1.081)

- .046 (.955)

- .021 (.979)

Small business sector (SMEs)

.915*** (2.496)

Multinational companies (MNCs)

.789** (2.201)

Intercept .098 - 1.210 .008 - .904 N 656 656 656 656 Degrees of freedom 2 4 6 8 Chi-square 32.166*** 12.461* 46.915*** 62.937***

NOTE. – Odds ratio of the response reported in parentheses OMITTED CATEGORIES. - Low education, Malay, Male, state sector. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). -2LL intercept is 853.582

106

The negative interaction effect, [(Job contact) x (R has high education), - .163*] in model

3 supports the proposition that well-educated job seekers tend to gain less from job

contacts than less-educated job seekers (Proposition 2). For the well-educated, job

contacts are a rather useless strategy for getting ahead.

If job contacts tend to be relatively useless for the well-educated, why do some

university graduates still use them? A possible explanation is that employers may

choose to evaluate their job applicants on multiple dimensions of education: for

example, level of education (i.e. years of schooling) and quality of education (e.g. reputation

of applicants’ university and grades). A pool of applicants may all be university

graduates, but particularly in labour markets that seek talented candidates, excellent

grades and reputable universities are distinguishing factors. In Singapore, a good

university degree (e.g. first or second-upper class honours from a good university) is a

highly valuable asset. University graduates with poorer grades often experience

difficulties getting the best jobs, despite being well-educated (in terms of number of

years) (see MacDougall and Chew, 1976).

The absence of significant ethnic effects on earnings (in models 2 and 3 of Table 3) is

attributed to education effects already being accounted for. Indeed, educational

inequalities between Chinese, Malays and Indians are a major source of earning

differences between Singapore’s ethnic groups. The inequality dynamic of gender is in

comparison different from ethnicity. As women are as likely as men to be well-

educated, gender differences in earnings (models 2 and 3) may be attributed to factors

other than education, such as persisting gender discrimination in paid work. In

Singapore’s state sector, men are paid more than women, net of education. The state

rationalizes the gender wage gap by evoking men’s later entry into paid work due to

national (military) service.

4) Job contacts are less likely to pay off in meritocratic job sectors (i.e. the state sector)

107

As credentials are especially important in Singapore’s state sector, it is not surprising

that its employees are generally more highly-educated than employees in the private

sector (6.96 vs. 6.01, t-test, .95*** in Table 4). Net of education, state sector jobs tend to

pay higher than private sector jobs (.088* in Table 4): this corroborates Evans’ (1995)

findings that bureaucratic salaries in Singapore are 10% higher than wages in

comparable private sector jobs. Because of attractive salaries, state sector jobs are often

target destinations for new university graduates, especially the high performers. The

data show that state sector employees are significantly less likely than private sector

employees to rely on job contacts (.18 vs. .43, Table 4), thus supporting proposition 4a.

The negative interaction effect in model 3 of Table 5a [(Job contact) x (R works in state

sector), - .153†] constitutes evidence at the .10 level that job contacts are not likely to be

as useful in the state sector as in the private sector. This attenuating effect becomes

more obvious when we make a further distinction between private sector jobs, namely:

‘small business sector (SMEs)’ and ‘multi-national companies (MNCs)’. The new

reference category would be ‘small business sector (SMEs)’ (Table 5b) instead of the

more general ‘private sector’ (Table 5a). With this distinction, the interaction term [(Job

contact) x (R works in a state sector job), - .169* in Table 5b] registers a higher level of

significance (p < .05), granting stronger support to proposition 4b.

108

TABLE 3. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS

Predictors Model 1 Model 2 Model 3 Focal independent variable:

Job contact - .261*** (.045)

- .084** (.033)

.009 (.061)

Control variables:

Middle education .369*** (.040)

.424*** (.055)

High education .941*** (.045)

1.010*** (.057)

Female - .204*** (.031)

- .206*** (.031)

Age .368*** (.071)

.372*** (.071)

Age square - .027*** (.006)

- .028*** (.006)

Chinese .036 (.041)

.031 (.041)

Indian .027 (.055)

.026 (.055)

Part time employment - .463*** (.055)

- .463*** (.055)

Interactions:

(Job contact) x (R has middle education)

- .106 (.079)

(Job contact) x (R has high education) - .163* (.085)

Intercept 2.508 .926 .870 R-square .0492*** .5393*** .5420*** Degrees of freedom 1 9 11 N 656 656 656

OMITTED CATEGORIES. – Low education, Malay, Male, Full-time employment. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

109

TABLE 4. JOB SECTOR DIFFERENCES IN EDUCATION, EARNINGS AND PROPORTION OF JOB CONTACT USERS

*P < .05. ** P < .01. *** P < .001 (two-tailed tests). † ‘Private sector’ includes both the small business sector (SME) and the multinational companies (MNC)

sector

Job sector

# of respondents

Mean education

level

Proportion of job

contact users

Difference in mean earnings between public and private job sectors when

effect of education is controlled

Public sector (1) 159 6.96 .18 Private sector† (2) 495 6.01 .43 Total or difference (1) – (2)

654 .95*** - .24*** .088*

INDUSTRIES Public Administration & Defense

15.8

Education 19.6 Health & Social Work 24.3 Electricity, Gas & Water 27.8 Transport, Storage & Communication

29.5

Financial Intermediation 33.3 Manufacturing 36.6 Real estate, Renting & Business

39.1

Wholesale & Retail Trade 50.7 Hotel & Restaurants 55.9 Construction 61.4

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TABLE 5a. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS BY JOB SECTOR

Predictors Model 1 Model 2 Model 3 Focal independent variable:

Job contact - .258*** (.045)

- .073* (.033)

- .048 (.036)

Control variables:

Middle education .358*** (.040)

.357*** (.040)

High education .925*** (.046)

.924*** (.046)

Age .368*** (.071)

.359*** (.071)

Age square - .027*** (.006)

- .027*** (.006)

Female - .208*** (.031)

- .208*** (.031)

Chinese .046 (.042)

.040 (.042)

Indian .023 (.055)

.023 (.055)

Part time employment - .454*** (.055)

- .450*** (.055)

State sector (civil service, statutory boards, GLCs)

.076* (.037)

.109** (.042)

Interaction:

(Job contact) x (R works in state sector job)

- .153 †

(.088) Intercept 2.508 .915 .932 R-square .0482*** .5403*** .5425*** Degrees of freedom 1 10 11 N 654 654 654

OMITTED CATEGORIES. - Low education, Malay, Male, Private sector, Full time employment. †P < .10. *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

111

TABLE 5b. OLS REGRESSION ESTIMATING THE EFFECT OF CONTACT USE ON EARNINGS BY JOB SECTOR

Predictors Model 1 Model 2 Model 3 Focal independent variable:

Job contact - .258*** (.045)

- .068* (.033)

- .041 (.041)

Control variables:

Middle education .351*** (.040)

.350*** (.040)

High education .898*** (.046)

.895*** (.046)

Age .352*** (.070)

.342*** (.070)

Age square - .026*** (.006)

- .025*** (.006)

Female - .210*** (.031)

- .210*** (.031)

Chinese .049 (.041)

.043 (.041)

Indian .018 (.054)

.017 (.054)

Part time employment - .443*** (.055)

- .438*** (.055)

State sector jobs (civil service, statutory boards, GLCs)

.126*** (.039)

.164*** (.044)

Multinational Company (MNC) .161*** (.040)

.164*** (.050)

Interactions:

(Job contact) x (R works in state sector job)

- .169* (.089)

(Job contact) x (R works in MNC) .00089 (.081)

Intercept 2.508 .920 .939 R-square .0482*** .5518*** .5545*** Degrees of freedom 1 11 13 N 654 654 654

OMITTED CATEGORIES. - Low education, Malay, Male, small business sector (SME), Full time employment. *P < .05. ** P < .01. *** P < .001 (two-tailed tests) Standard error in parentheses

112

5) Job contacts are less likely to be associated with formal industries

Table 4 and Figure 1 support the hypothesis that job contacts are less likely to be

associated with entry into formal industries such as public administration and defence,

health and social work and education (Proposition 5).

Based on post-hoc one-way ANOVA tests, the industries being examined can be

divided into three distinguishable clusters: generally, jobs in public administration and

defence, education and health and social work tend to go with the lowest levels of

contact use. Jobs in electricity, gas and water, financial intermediation, manufacturing,

real estate, renting and business and transport, storage and communication tend to go

with middle levels of contact use, and jobs in wholesale and retail trade, hotels and

restaurants and construction tend to go with the highest levels of contact use. In sum,

the more formal the industry, the less prevalent the use of job contacts.

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6) High-status job contacts do not result in higher earnings for contact users

Model 1 in Table 6 reports no significant relationship between high-status job contacts

and earnings (- .029, ns). With relevant controls added in model 2, this non-significant

effect persists (- .064, ns in model 2), suggesting that high-status job contacts do little to

facilitate status attainment (Proposition 6). It appears, despite strong evidence of

significant post-hire benefits associated with high-status contacts in many

contemporary labour markets (see summary table in Lin, 2001:84), Singapore seems to

be make for an exception, at least in this particular study2.

7) Well-educated contact users are less likely to experience added returns from high-status

contacts than less-educated contact users

Model 3 in Table 6 tests the interaction between respondents’ level of education and the

status of their job contacts relative to their own. The negative interaction effect,

[(Contact has higher status than respondent) x (R has high education) - .293*], suggests

that well-educated contact users are less likely than lower-educated contact users to

experience added returns from using high-status job contacts (Proposition 7). This

reinforces the point that those with already good credentials may often find social

capital a less valuable route of status advancement.

2 Studying the United States, Mouw (2003) argues that high-status contacts relate spuriously with post-hire outcomes, and that any positive relationship is actually the result of homophilous friendship patterns. Given this endogeneity problem, Mouw suggest using other measures of social capital to measure and verify the positive relationship between social capital and post-hire outcomes. Furthermore, some scholars may choose to argue that the Singapore case is in fact no different from the American case. At this point, more research is required in the area of comparisons. But Mouw’s arguments notwithstanding, the overwhelming consensus in the literature is that high-status contacts do indeed make a substantial difference to post-hire outcomes in the United States and other countries (see the many studies reviewed in Lin (2001:83-87).

114

TABLE 6. OLS REGRESSION ESTIMATING THE EFFECT OF HIGH-STATUS JOB CONTACT ON EARNINGS BY RESPONDENT’S EDUCATION

Predictors Model 1 Model 2 Model 3 Job contact is of higher status than respondent

- .029 (.070)

- .064 (.050)

.032 (.085)

Respondent’s characteristics:

Middle education .295*** (.056)

.310*** (.069)

High education .808*** (.070)

.910*** (.082)

Age .325** (.114)

.322** (.113)

Age square - .026* (.010)

- .025* (.010)

Female - .240*** (.051)

- .238*** (.051)

Chinese .025 (.071)

.034 (.071)

Indian .002 (.097)

.017 (.097)

Part time employment - .461*** (.071)

- .467*** (.071)

Interactions:

(Job contact has higher status than R) x (R has middle education)

- .060 (.115)

(Job contact has higher status than R) x (R has high education)

- .293* (.131)

Intercept 2.264 1.140 1.120 R-square .0007 .5259*** .5372*** Degrees of freedom 1 9 11 N 237 237 237

OMITTED CATEGORIES. - Contact is of same or lower status than the respondent, Respondent has low education, Malay, Male, Part time employment *P < .05. ** P < .01. *** P < .001 (two-tailed tests). Standard error in parentheses

115

DISCUSSION

I have drawn upon a distinction popularly used in the varieties of capitalism literature:

‘liberal market economies’ (LMEs) and ‘coordinated market economies’ (CMEs) (Hall

and Sockice, 2001). Each shows a unique relationship between the education and labour

sides of the labour market (Allmendinger, 1989). My results have suggested that in

labour markets that stress the tight bureaucratic link between educational signals and

labour markets, personal contacts are less prevalent and effective in job searches,

especially among the well-educated and those working in the highly-meritocratic state

sector.

While Singapore is a broadly meritocratic society and may have a strong meritocratic

system in government, the extent of this meritocracy is less pervasive in the private

sector. But this may soon change: using its political and economic clout, the Singapore

state is pressuring private sector firms to emulate the meritocratic practices of

government sector jobs. Indeed, the government has recently (in 2007) set up a council

called the Tripartite Alliance for Fair Employment Practices (or TAFEP), strongly

encouraging employers to sign an “Employers’ Pledge” against discrimination in

hiring. To date, 1000 private sector companies have signed and the numbers are

growing.

In state sector jobs, the link between qualifications and earnings at entry level is clear

and transparent. Recently, in the Ministry of Home Affairs, first-class graduates got a

starting salary of $3,494; second-class (upper) honours graduates received $3,310; basic

degree holders $3,310, and so on. With such standardization in place, there is little

room for job contacts to influence remuneration outcomes. To be sure, salaries are

adjusted after a few years; once the person is in the job and he/she is assessed on

current performance. But the base-pay remains a function of formal qualifications.

116

This is not to say that credentials are only important among Singaporeans or that only

Singaporean employers consider them worthy. The growth of tertiary education

around the world reflects the increasing importance of formal qualifications, even if its

role is often symbolic and not always matched by real increases in productivity (Dore,

1976; Collins, 1979).

In Singapore, the symbolic power of credentials (assumed to be indicative of skills) is

most palpable in the meritocratic state sector where there is ideological pressure to

reward university graduates with good wages, despite weak increases in productivity.

The allocation of wages is as much an economic process as it is an exercise in

political/legitimacy-building. Indeed, it has been argued that Singapore’s university

graduates are often over-qualified but under-skilled for their jobs (Appold, 2005).

Dore’s “credentialism” (1976) is probably stronger in Singapore than in the United

States. Comparing Singapore and America, the former minister of education (of

Singapore), Tharman Shanmugaratnam, said:

We both have meritocracies. Yours is a talent meritocracy, ours is an exam

meritocracy. We know how to train people to take exams. You know how to use

people’s talents to the fullest. Both are important, but there are some parts of the

intellect that we are not able to test well – like creativity, curiosity, a sense of

adventure, ambition. Most of all, America has a culture of learning that

challenges conventional wisdom, even if it means challenging authority. These

are the areas where Singapore must learn from America. (Zakaria, 2008:193-194)

In the North American context, talent is often elicited through a combination of

credentials and networks; in fact, the two are often perceived as being inextricably

bound together (see Coleman, 1988 or Erickson, 2001). In Singapore, talent is typically

elicited through national examinations. Rodan (1996:24) notes:

117

The pattern of increased educational attainment in Singapore is often

compounded by the exceptional importance on credentials in ‘meritocratic’

Singapore… there is probably no other place in the world where formal

qualifications represent as much economic or social capital.

This invites the question: what makes it so difficult to re-invent, change or move away

from an exam-based meritocracy? One reason is that institutional structures are

notoriously difficult to change (see Meyer and Rowen, 1977 and Hannan and Freeman,

1984 on organizational inertia, myth and ceremony). Power holders have a vested

interest in reproducing their advantages, and education seems an expedient way to do

it. As class factors (namely family background) are strong predictors of educational

resources, children from wealthier families inadvertently get a head start (Bowles and

Gintis, 1976). Indeed, meritocracy supplies the wealthy with a discourse which

attributes personal success to meritocratic attributes such as effort and ability rather

more structurally, initial class standing (Young, 1958).

In an exam-based meritocracy, education contributes indirectly to political stability by

serving as the only (in principle) legitimate means of upward mobility. The motif of

meritocracy generates the often unquestioned belief that individuals from humble

backgrounds are as likely as individuals from privileged backgrounds to succeed if they

are willing to work hard. Meritocracy upholds the myth of equal educational

opportunities for all, and conceals the fact that kindergartens and elementary schools

continue to vary greatly in quality. The logical end of a meritocracy is an elitist system

whereby class privileges are reproduced through education, even as schools continue to

be at least, partly, social levellers of inequality (Bowles and Gintis, 1976).

In Singapore, education is a means for the Chinese majority to maintain their political

hegemony and economic dominance in relation to the other ethnic groups (Rahim,

1998). As the most highly-educated ethnic group in Singapore, the Chinese have a

vested interest in upholding education as the most important route of status

118

advancement. Through education, they (especially English-educated Chinese) get to

maintain their control over the powerful state and MNC sectors. Chinese-educated

Chinese on the other hand, rely not on education, but on their networks to hoard

opportunities within the small business sector. Either way, Chinese have secured for

themselves -- either through education or networks – lucrative and stable positions

within both state and non-state sectors.

Of course, one could argue that with only one country, it is hard to make an argument

about national differences, and that we need data for other liberal and coordinated

economies to be sure that the Singapore results are not due to something else like

culture. This is one limitation of the study that further comparative work on national

economies could seek to rectify.

CONCLUSION

Granovetter (1974) found that in the United States, more than half of his respondents

used a personal contact to find a job. By contrast, this study shows that only a third of

Singapore respondents used a contact. Why the difference? In his Afterword,

Granovetter (1995:160) posits that “there do not seem to be sharp variations by country

in what proportion of people find jobs through contacts, but institutional variations do

lead to differences in the detailed process.” Based on my findings, I would disagree

with the former part of his argument and agree with the latter – institutional variations

do matter.

Cultural differences cannot fully explain the role of personal contacts in different kinds

of job sectors and economies, and institutional involvement should also be considered.

Several studies have pointed to the contingent nature of job contacts on status

attainment (e.g. Granovetter, 1995; Burt, 1997; Guthrie, 2002; Lin, 1999), but the question

of mechanisms needs further exploration. Evoking a “varieties of capitalism”

framework, I have argued that variations in contact use and payoffs may be explained

119

by variations in the manner with which education and labour market systems are

interrelated in different types of economies and job sectors.

While several LME-based studies show that high-status contacts lead predictably to

status attainment (Marsden and Hurlbert, 1988; Lai, Lin and Leung, 1998; Lin, 2001), my

study suggests that such effects do not necessarily apply to labour market institutions

which rely heavily on academic credentials for job matching. Although individuals are

free to choose the kinds of search methods they think relevant, contextual factors play a

critical role influencing the usefulness of those strategies. My contention is that in order

to better understand the role and value of job contacts one must consider the role of

institutions, namely the different ways in which education and employment systems

interrelate with each other within and between national economies.

120

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Chapter 5 (Paper 3) The Invisible Hand of Social Capital

This paper underscores the importance of institutional factors affecting the role and value of social capital in labour markets. Distinguishing between two broad categories of social capital: ‘accessed’ and ‘mobilized’ social capital, I ask: how do meritocratic constraints in labour markets affect the role and value of different kinds of embedded social capital? Using representative survey data from Singapore, I show that 1) social capital continues to be important even in highly-meritocratic jobs, and 2) that social capital works primarily through the invisible hand of ‘accessed’ rather than the visible hand of ‘mobilized’ in contexts of meritocracy. INTRODUCTION

This paper aims to further our understanding concerning the impact of institutional

contexts on the role and value of social capital. The contexts that I am concerned about

are those characterizing meritocracies: that form of society that focuses heavily on

formal credentials and that seeks to reward people according to their efforts, abilities

and achievements rather than their ascribed characteristics such as gender, ethnicity,

age, or social networks (Young, 1958; Goldthorpe and Jackson, 2008).

While there are many approximately meritocratic societies in the world today, a most

notable extreme case is Singapore (Evans and Rauch, 1999). In their study of a group of

some 35 countries (including countries such as Canada, Japan, Taiwan, South Korea, but

not the United States), Evans and Rauch (1999), found that Singapore was the most

“Weberian” among them: that is, Singapore had registered the highest score for having

a highly formal state bureaucracy, for emphasizing meritocratic recruitment in state jobs

and for having career paths that are transparent and predictable.

The meritocratic system of Singapore provides an excellent opportunity for asking some

pertinent research questions: 1) how do meritocratic constraints influence the role and

value of social capital in labour markets? 2) does the heavy emphasis on formal

credentials in a meritocracy mean that social capital is consigned to play a marginal

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role? And 3) assuming that personal contacts are perceived as unethical in the context

of meritocratic jobs, may we expect social capital to work in embedded ways?

ISSUES

Need to consider the role of contextual factors on social capital

Having social capital means having access to resources as a result of knowing

influential people who have those resources (Lin, 2001). In the literature, discussions of

social capital are often couched in a vocabulary of ‘investments’. The theoretical

assumption is that people are motivated by expressive and instrumental needs that

propel them to form (or ‘invest’) in interactions with others to gain resources such as

wealth and reputation (Lin, 2001:184).

Such an instrumental viewpoint however tends to over-privilege the role of people’s

choices over that of their environments. Indeed, an emphasis on choice arguably

bestows too much power on individuals’ social networking abilities and skills, while

downplaying the fact that labour market conditions profoundly affect the extent to

which those networking abilities and skills are utilized and/or pay off. This paper

underscores that it is important to consider the influential role of macro-institutional

structures and constraints (such as the highly-meritocratic nature of some labour

markets) on social capital, even as people seek to optimize their networks as social

capitalists (Hsung, Lin and Breiger, 2009).

Comparing the United States, Taiwan and China, a recent study (by Son, 2008) found

that macro-institutional constraints substantially affect the role and value of social

capital in different kinds of societies and labour markets. The study had noted for

example that mainland Chinese and Taiwanese Chinese were significantly less likely

than North Americans to activate social capital during job seeking. One explanation

being offered was the greater reliance on academic credentials in Confucian societies,

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which results in job contact use becoming suppressed. Citing the case of South Korea

(conjectured to be similar to China and Taiwan), Son (2008) recounts that it is common

to see notices in government offices inscribed with following words: “Do not ask for

favours through connections.” The South Korean state often perceives particularistic

mechanisms such as school ties, regional ties and blood ties as signalling corruption.

In North America, by contrast, social networks are more actively utilized by job seekers

and less likely to be saddled with negative connotations. In fact, networks are often

perceived by North American job seekers and employers as necessary for facilitating the

best kinds of job matches (Fernandez, Castilla and Moore, 2000; Erickson, 2001; Bolles,

2009). National variations in the use and meaning of job networks suggest that social

contexts are important sources of the variations in networking practices, and that more

research should be allocated to better understanding the macro-micro link between

institutional constraints and networks (Hsung, Lin and Breiger, 2009).

More to social capital than job contacts alone

In earlier years, social capital research had focused quite predominantly on the impact

of “job contacts” on individuals’ labour market outcomes. Job contacts were established

as being important for helping people get jobs as well as enhance their occupational

status (e.g. Granovetter, 1974; Marsden and Hurlbert, 1988; see Lin, 2001 for a review of

many such studies). However, over time, with the invention of data collection methods

such as the position generator (which allowed researchers to measure respondents’

access to people from diverse occupational locations within the social structure), it

became clear that the conscious mobilization of job contacts was only one very specific

aspect of networking, and that broader forms of social capital (namely accessed social

capital), were important for job success as well (Lin, 2001; Lin and Ao, 2008).

In practice, job contacts represent only a slice or subset of the total social capital

captured by research and are therefore an inadequate representation of the total

potential of a person’s network (Lai, Lin and Leung, 1998; Lin and Ao, 2008). Whereas

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mobilized social capital (i.e. job contacts) refers to the social ties and resources that are

consciously activated in a specific event such as a job search (Granovetter, 1974; Lin,

Ensel and Vaughn, 1981), accessed social capital refers to the entire capacity of a

person’s network (Lin and Ao, 2008). Certainly, we need more research concerning

how accessed and mobilized social capital operate in tandem -- as analytically distinct

and yet integrated (Lin, 2001).

The distinction between accessed and mobilized reflects the dual way in which

individuals relate with social capital. On one hand, people are social networkers who

seek through job contacts for example, to optimize their job success (Lin, 2001). But on

another hand, people are also social networked: that is, they are embedded within

networks of social relations which they do not consciously activate, but which they

benefit from in indirect ways (Granovetter, 1985; Small, 2009).

The resources accrued from accessed social capital may often be unanticipated, since

such social capital is, by definition, not consciously activated (Small, 2009). This paper

underscores the need to examine the unanticipated consequences of networks and

argues that focusing on job contacts alone is not sufficient for measuring the impact of

social capital and job success. Interestingly, while most studies have examined

mobilized or accessed social capital on separate occasions, few have analyzed both

under the rubric of a single study. And yet to do so constitutes a highly urgent research

task (Lin and Ao, 2008). As accessed and mobilized social capital form distinct but

integrated parts of personal networks, they should be analyzed in tandem, with a view

to understanding their combined role in labour markets (Lin and Ao, 2008).

The substance of accessed social capital

According to Lin and Ao (2008), accessed social capital may often take the form of

“routine job information”: this is the information that arises from encounters and

conversations that “flow casually in a fragmented way and without explicit

expectations” (Bearman and Parigi, 2004 cited in Lin and Ao, 2008). Here, the receiver

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does not deliberately seek out such information or social resources but stumbles across

it in the course of everyday life.

But there is more to accessed social capital than routine job information. Indeed,

accessed social capital may include any kind of network-induced information and

resources that potentially affects status attainment. These include:

1) Network-induced cultural capital: The acquisition of cultural capital is a highly

social process. Families, for example, play an important role transmitting

distinguished patterns of speech, etiquette and comportment to the next

generation (Bourdieu, 1984). The persistence of legacy admissions in many elite

schools in the contemporary world serves as an excellent example of how

privileged resources, cultural capital and influential networks may often help

privileged members of society hoard opportunities (Bowles and Gintis, 1976). So

people may not have actually mobilized a job contact during the job search, but

because of their embeddedness within advantageous family and friendship

networks, get to acquire a repertoire of cultural and human capital which places

them in good stead to experience job success.

2) Having good connections may often be a job credential in itself: Employers sometimes

prefer candidates who possess a rich repertoire of networks, especially for

managerial jobs (Erickson, 2001). Having a rich network is a reflection of several

things which employers find attractive. First, a well-connected person usually

has good interpersonal skills (if not he/she would not be well-connected in the

first place) (Coser, 1975). Second, a well-connected person is an asset to a

company because his/her networks may help him/her to contribute to its

bottom-line, for example procure clients for the company (Erickson, 2001). Third,

a well-connected person is likely to have a good social support system, and this

makes him/her a physically and mentally healthy person (Pescosolido, 1992).

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Such a person is likely to be a productive worker and not burden the company

with health claims!

3) Good networks lead to good ideas: Personal networks are sources of good ideas,

especially if they consist of weak ties. Weak ties are important because they link

people to social milieus which are less familiar and therefore novel and value-

adding (Granovetter, 1973). In practice, the acquisition of good ideas is not just

about delving into the books (although a human capital approach would tend to

privilege such an argument), but the outcome of being embedded in networks

that facilitate the exchange of bright ideas (Burt, 2004). Good ideas produce

innovative workers who can contribute directly to the improvement of a

company. Erickson’s research (1996) indicates that people with diverse networks

often have a diverse repertoire of knowledge.

In an earlier paper (Chua, 2010), I demonstrated that job contacts were: 1) seldom

utilized to enter meritocratic jobs, 2) associated with lower earnings, and 3) associated

with lower increments in earnings, especially in meritocratic jobs: all these support the

idea that meritocratic constraints tended to suppress the role and value of social

networks. But this cannot be the end of the story as I had only examined job contacts,

which is the visible hand of social capital. More theorization is needed concerning the

invisible hand of social capital.

On why the invisible hand of social capital should be especially important in meritocracies

Meritocracy is a social system that seeks to reward people on the basis of merit: often-

time “educational” merit (Goldthorpe and Jackson, 2008). In Singapore as with many

other countries (particularly countries in East Asia), formal credentials are emphasized

and deployed rigorously as a means of allocating people to the best jobs. In fact, to

select workers based on any other means, such as networks, would imply some kind of

corruption and therefore according to the rhetoric of meritocracy, illegitimate.

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The puzzle in this paper is essentially this: if the active mobilization of social capital is

in the meritocracy saddled with such negative connotations as illegitimate, then what

exactly is the role and value of social capital in such societies? Surely, networks

continue to matter, but how so? How do meritocratic structures and constraints impact

the way embedded forms of social capital interface with status attainment?

The thesis which I seek to advance is that in meritocratic jobs, social capital tends to

operate in embedded ways. In a meritocracy, overt ways of social capital utilization

such as mobilizing a job contact will generally be unpopular, especially in the most

meritocratic of labour markets. Instead, embedded and diffuse network mechanisms

will be more important and leveraging in those meritocratic labour markets.

Overall, this paper demonstrates the following:

1) Social capital continues to be an important predictor of job success, even in

meritocratic jobs.

2) The primary way in which social capital facilitates job success in meritocratic jobs is

accessed of social capital (i.e. the invisible hand of social capital) rather than mobilized

social capital (i.e. the visible hand of social capital).

3) The more meritocratic the labour market, the more pronounced the role and value of

accessed social capital relative to mobilized social capital.

I argue that the lesser importance of job contacts in meritocratic labour markets is not a

sign that social capital is altogether unimportant. There are broader aspects of social

capital that contribute to status attainment, even if job contacts do not.

SINGAPORE CONTEXT

The separation of Singapore from Malaysia in August 1965 (after just twenty three

months of political merger) was due primarily to the issue of meritocracy. The

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Malaysian Prime Minister, Tunku Abdul Rahman and Singapore’s Prime Minister, Lee

Kuan Yew were divided over how exactly to allocate the resources of a newly-formed

Malaysia. Whereas Lee had pushed strongly for a society based on multiculturalism:

that is, the equal treatment of ethnic groups (Hill and Lian, 1995:93), such an approach

was at odds with Malaysia’s Malay-first (or ‘Bumiputra’) policy. The Malaysian Tunku

wanted a Malay-centered society with privileges going first to Malays as natives of the

land (Lee, 1998). The incompatibility of viewpoints and other political differences

sparked serious ethnic riots in 1964, which led eventually to Singapore being thrown

out of Malaysia a year later. Lee’s intransigent stand on meritocracy may be attributed

partly to demographic factors: as about 75% of Singaporeans are Chinese, acceding to a

‘Malay-first-policy’ would have reinforced Singapore’s position of socio-economic

disadvantage relative to their Malay neighbours, and why should Singapore, as a

predominant Chinese state, want that?

The separation, it appears, had served only to strengthen Singapore’s determination to

bring her meritocratic beliefs to an even higher level: that is, to move meritocracy

beyond the realm of ideas, into the realm of durable institutions reflected thus in its

politics, education, economy, and culture (Tan, 2008). Today, meritocracy pervades

Singapore society and is used aggressively in the administration of its economic,

political and social structures. The highly rationalized state sector, nicknamed

“Singapore Inc.” (Economist, 2002), is the most powerful promoter of this meritocracy.

While the state is not the only organization in society, its influential presence exerts

pressure on the other labour markets to conform to its meritocratic practices (DiMaggio

and Powell, 1983). No discussion of Singapore is complete without considering the

very influential role of this state apparatus (Yao, 2007). Ezra Vogel notes that “what is

unusual in Singapore is not the prominence of meritocratic administrators, but the fact

that this meritocracy extends upward to include virtually all political leaders” (cited in

Quah, 1998:111). In Singapore, the selection for political office is based upon a high-

rationalized system of merit involving academic credentials, job performance and

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character evaluation. Potential candidates go through six sieves of informal tea

meetings, formal interviews, and rigorous psychological testing (consisting over 1,000

questions) (Bellows, 2009). This stringent process of selection has the effect of

legitimating the state in the eyes of the people, thus bestowing the state with a high

level of prestige (Johnson, 1982).

Consequently, getting a good job within the state sector (which comprises the civil

service, statutory boards and government-linked companies) is highly desired among

Singaporeans. Critics have drawn attention to the fact that because the state

monopolizes the nation’s talent pool, few outstanding individuals are left to the small

business sector and multi-national companies (MNCs): that is, the state muscles out the

other labour markets (Tan, 1996). But the state’s rebuttal is that without good

leadership and governance, nothing else down the line works (Neo and Chen, 2007).

Indeed, the state has an elaborate system of rewards to attract the most talented. One

established way has been the offering of lucrative government scholarships (usually to

prestigious universities overseas) to students who have outperformed their peers in the

national examinations in exchange for some stipulated number of years of bonded

service (Barr, 2006). Another way has been the implementation of a civil service pay

structure clearly stratified by academic performance. This pay structure allocates the

most attractive rewards to the examination stalwarts. Less academically-inclined

students are likely to end up in the large but less powerful private sector. On a scale of

meritocracy, the state sector could be said to occupy the uppermost extreme position,

the MNCs the middle, and the small business sector, the bottom position.

Many Singaporeans believe that academic credentials are on their own sufficient for

securing a good job. This belief is reinforced by the pervasive rhetoric of meritocracy in

Singapore which purports to allocate resources based on academic merit rather than

ascriptive factors. In a 2004 national survey asking Singaporeans to rank how

important various resources were to them, “education” was rated most important,

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followed by “hard work” and “ability”, and then, only in fourth, “social connections”

(Tan, 2004). This finding implies the perceived ineffectiveness of social capital as a

means of social advancement in face of strong human capital idealization.

The academic system in Singapore is not just about students jostling for the best grades

and resources, but about parents being very much involved as well (Cheah, 1998).

While Confucian culture and its high emphasis on education is one source of this

competition, (and in this regard, Singapore is no different from the other East Asian and

Asian societies: Taiwan, Korea, Japan, China and India), in the case of Singapore, the

state apparatus and its propensity to tightly link wage/salary structures to academic

performance intensifies this credentialism all the more.

Part of it is culture: Singapore is a predominantly Chinese society (75%): the Chinese

themselves have had a long history of academic credentialism and knowledge

acquisition (Weber, 1983). But structure is also important (Sen, 2004). The value of

education in the mainland was since early on, bound up with an intense Mandarinate

system which selected state officials based on rigorous examinations testing knowledge

on poetry and the Confucian classics. The best candidates were co-opted to serve in the

emperor’s administration (Weber, 1983).

Corruption is strongly eschewed in Singapore’s state sector so that the taking of bribes

is one of the mortal sins. In 1986, a cabinet minister was investigated by the Corrupt

Practices Investigation Bureau (CPIB) for allegedly accepting two bribes of $500,000

each in 1981 and 1982. Although the minister maintained his innocence, he committed

suicide before being charged for the offences. In his suicide note, he wrote:

I have been feeling very sad and depressed for the last two weeks. I feel

responsible for the occurrence of this unfortunate incident and I feel I should

accept full responsibility. As an honourable oriental gentleman I feel it is only

right that I should pay the highest penalty for my mistake.

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The anti-corruption stance in Singapore is from the viewpoint of the state, not only

important for ensuring social stability in society, but also for making Singapore a place

of trustworthy institutions where citizens and foreign investors can safely invest their

money.

With meritocracy and its strong emphasis on education for social mobility, many

disadvantaged Singaporeans have been able to ascend the class structure. The

provision of government subsidies for tertiary education has greatly facilitated this

process of individual advancement (Chang, 1995). And yet, there are some aspects of

the class structure, especially in the area of relative mobility, that the meritocracy has

been less successful at equalizing. For example, tertiary subsidies were for a long time

available to all tertiary students regardless of their family background. This created a

situation where well-to-do students had access to the same incremental resources as less

well-to-do students despite already having more to begin with.

Meritocratic intentions do not always lead to meritocratic outcomes. The fact that

people inherit unequal starting lines in life and compete unequally based on them is

seldom highlighted in the discourse of meritocracy (Gillis, 2005). In the end, merit-

based systems are often likely, even if unintentionally, to pick people who are already

advantaged in terms of their family background (also see Tan, 2008; Barr and Skrbis,

2008).

While many Singaporeans from humble backgrounds have excelled in the national

examinations, such meritocratic occurrences may get increasingly rare as society

develops and stratification between cosmopolitan rich and local poor becomes

increasingly evident.

As to whether any society can be truly meritocratic at all is inherently debatable (Tilly,

1998; Gillis, 2005). But, the belief in meritocracy is itself a powerful force; and belief

systems often culminate in institutional structures (Redding, 2008). In Singapore, the

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contradictions of a meritocratic system are seldom discussed at the level of the nation.

Instead, meritocracy is, as a pristine principle, venerated throughout society. To the

Singapore state, meritocracy is the best way of administering society. One of the ruling

party’s most influential members, S. Rajaratnam, once said: “I believe in a hierarchy of

merit simply because I cannot think of any other way of running a modern society, for

that matter even a primitive tribal society” (Chan and Haq, 1987 cited in Bellows, 2009).

HYPOTHESES

The question that drives this research is specifying the role of social capital in such a

strong state and credentialistic society as Singapore. The main argument being

advanced is that meritocratic constraints tend to suppress (in lieu of their anti-

corruption stance) the role and value of “mobilized” social capital (i.e. job contacts), but

they cannot suppress the role and value of “accessed” social capital. While a

meritocracy may tend to suppress overt forms of network mobilization (e.g. Chua,

2010), it cannot prevent social capital from working in more embedded ways. My data

will demonstrate that social capital matters very much, even in meritocratic jobs. In a

merit-based society that generally frowns upon job recruitment based on overt network

mechanisms, the role of accessed social capital, being more embedded, becomes

especially important.

My hypotheses will be stated as follows:

H1: Social capital facilitates entry into highly-meritocratic jobs primarily through the

invisible hand of social capital (i.e. accessed social capital) rather than the visible hand of

social capital (i.e. use/mobilization of job contact).

H2: The invisible hand of social capital (i.e. accessed social capital) is on average a more

powerful facilitator of job success than the visible hand of social capital (i.e.

use/mobilization of job contact).

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H3: The positive impact of the invisible hand of social capital (i.e. accessed social capital)

on job success is especially pronounced in labour markets that emphasize meritocracy

(e.g. in the state sector).

H3 implies interaction effects. Based on the argument that embedded forms of social

capital continue to matter greatly in meritocratic labour markets, we should expect to

see accessed social capital being especially effective as a generator of earnings in

meritocratic jobs. Statistically, this means that relative gains in earnings accrued from

using accessed social capital should be significantly greater in meritocratic jobs than in

non-meritocratic jobs. A possible explanation (concerning why accessed social capital

should be more efficacious in meritocratic sectors) is that meritocratic jobs may tend to

be more challenging, and hence people with better social resources would tend to do

better.

DATA AND METHODS

Data sources and sample

I analyze representative data from the 2005 Project Network Survey, using a sub-sample

of 656 currently employed Singaporean adults aged between 25 and 55. As labour

markets and current earnings are important variables in the analysis, I included only

part-time employed (9%) and fully employed (91%) respondents, excluding

homemakers, students and the retired (Table 1).

Men and women contributed to 58.4% and 41.6% of the sample respectively. The

uneven gender distribution is due to men’s greater participation in paid work relative

to women. As the numerically dominant ethnic group, Chinese make up the majority

67.8% of the sample, while Malays and Indians were oversampled to make up 18.6%

and 13.6% respectively.

The survey distinguished between three educational groups: 25.0% have ‘low’ level

education (i.e. no formal education or some secondary education), 40.9% have ‘middle’

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level education (i.e. completed secondary school, technical school or pre-university),

and 34.2% have ‘high’ level education (i.e. polytechnic or university graduate).

Of the 656 respondents, 24.3% were employed in the state sector (comprising the civil

service, statutory boards and government-linked companies), 20.3% in the MNC sector

and 55.4% in the small business sector. 48.9% were employed as professionals,

managers or technicians (PMT), 25.6% as clerical or service workers and 25.5% as

workers in production, plant, and cleaning etc.

As in Fischer’s Northern Californian study (Fischer, 1982), this survey used a range of

name generators (e.g. who do you discuss important matters) to delineate the personal

networks of the respondents. The name generators were followed up with name

interpreters (Marsden, 2005), which elicited information about each network member

and the nature of their relationship with their respondent. These name interpreters

included items such as network members’ gender, race, age, education, housing type, in

addition to tie information such as the role relationship (e.g. whether child, parent,

spouse, sibling, co-worker etc.) closeness, and tie longevity.

The name generators were designed to cover a range of emotional, social and

instrumental scenarios with the exact wordings modified to suit the Singapore context.

The data was collected by a reputable and experienced survey research company in

Singapore, AC Nielsen, and conducted in three possible languages, English, Mandarin

or Malay. Each interview lasted about an hour, and was conducted at the door of the

respondents’ homes.

Accessed and mobilized social capital

I used three measures of accessed social capital: 1) number of university graduates 2)

number of private housing dwellers and 3) number of Chinese. Given that university

education, private property and Chinese ethnicity are all high status resources in

Singapore (Lee, 2006), they make excellent measures of social capital. The first two are

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high on the SES ladder while the third is high on the ethnic status ladder (Weber, 1946).

Even though education, private property and Chinese are statistically interrelated, they

are by no means perfectly correlated. These distinguishable measures offer an excellent

opportunity to evaluate the extent to which different kinds of high-status social capital

affect job success.

TABLE 1. SAMPLE CHARACTERISTICS (N = 656)

PERSONAL CHARACTERISTICS OF RESPONDENTS PERCENTAGE (%)

AGE:

25-29 years 11.9 30-34 years 16.2

35-39 years 17.4

40-44 years 23.3 45-49 years 17.7

50-55 years 13.6

GENDER: Male 58.4

Female 41.6

ETHNIC GROUP:

Chinese 67.8

Malay 18.6 Indian 13.6

EMPLOYMENT STATUS:

Full-time 91.0 Part-time 9.0

EDUCATION: ‘Low’ education (No formal education or some secondary ) 25.0

‘Middle’ education (Completed secondary, technical school

or pre-university)

40.9

‘High’ education (Polytechnic or university graduate) 34.2

JOB SECTOR:

Small business sector (SMEs) 55.4 Multinational companies (MNCs) 20.3

State sector (civil service, statutory boards and GLCs) 24.3

OCCUPATION:

Professional, Managerial, Technical (PMT) 48.9

Clerical and Service 25.6

Production, Plant, Cleaning etc. 25.5

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Mobilized social capital is operationalized as a dichotomous variable measuring

whether (1) or not (0) the respondent had activated a job contact during his/her job

search. Following Granovetter’s original design (1974), the survey asked respondents to

report how they had obtained their current jobs. The options were: 1) I saw an

advertisement in a newspaper (or other sources of media) 2) I found out through an

employment agency 3) I submitted an application 4) Someone I didn’t know contacted

me and said that I had been recommended 5) I asked friend/person who told me about

the job 6) A friend/person who knew I was looking for a job contacted me 7) A

friend/person who didn’t know I was looking for a job contacted me and 8) Others.

Respondents who indicated options 5, 6 or 7 were assigned ‘1’ on the job contact

variable; the rest were assigned ‘0’.

Job sector

The job sector variable includes three kinds of labour markets, each differing by the

extent to which meritocracy is enforced. The most meritocratic job sector is the state

sector, followed by the multinational companies (MNCs), and then the small business

sector (SMEs), in that order. Depending on the hypothesis being tested, job sector is

either a dependent (H1) or independent variable (H2 and H3).

The testing of H1 evokes a series of multinomial logistic regression models estimating

the impact of accessed social capital (the three kinds) and mobilized social capital on the

logged odds of being in the various job sectors.

Earnings

Earnings is used as a dependent variable and deployed in several OLS regressions. To

transform the skewed distribution, I applied a square root to the numeric codes

representing each of seventeen earning categories. These OLS regressions are used to

test H2, which hypothesizes that in Singapore’s meritocratic society, accessed social

capital is a more powerful facilitator of job success than mobilized social capital.

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Other predictors of earnings

Additional predictors of earnings include education, gender, race, age, employment

(part time or full time), occupation, job sector, and participation in voluntary

organizations.

Education is computed as two dummy variables: ‘education (middle)’ and ‘education

(high)’, with education (low) being the reference category. ‘Female’ is a dummy

variable for self-reported gender: 1 for female and 0 for male. Race is represented by

two dummy variables: ‘Chinese’ and ‘Indian’, with Malay being the reference category.

As earnings tend to peak in midlife and taper off after, age is entered in linear and

quadratic forms. Employment status is a dummy variable for whether the respondent

is part time or full time employed, 1 for part time and 0 for full time. Occupation is

represented by two dummy variables: ‘PMT’ (Professional, Managerial and Technical)

and ‘Clerical/Service’; the omitted category is Production, Plant and Cleaning etc. Job

sector is represented by two dummy variables: ‘state sector’ and ‘MNC sector’, with

small business sector assigned the reference category. ‘Social participation’ is a dummy

variable for participation in voluntary associations, 1 for participation and 0 for nil.

Interaction effects

H3 (that the positive impact of accessed social capital on job success is especially

pronounced in labour markets which emphasize meritocracy) implies interaction

effects. Taking the small business sector as the reference category, I computed the

following interaction terms: [accessed social capital] X [state sector], [accessed social

capital] X [MNC sector] and [mobilized social capital] X [state sector], [mobilized social

capital] X [MNC sector]. Assuming that H3 is supported, we would expect 1) [accessed

social capital] X [state sector] to be positive and significant, and 2) [mobilized social

capital] X [state sector] to be either negative and significant, or less positive and

significant.

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RESULTS

1) Accessed social capital is more likely than mobilized social capital (i.e. use of job contact) to

facilitate entry into meritocratic job sectors

Tables 2, 3 and 4 are multinomial logistic regressions estimating the impact of accessed

and mobilized social capital on entry into the various job sectors.

These tables test H1 across three different types of accessed social capital: number of

university graduates (Table 2), number of private housing dwellers (Table 3) and

number of Chinese (Table 4).

Control variables have been added in order to isolate the independent effects of

accessed and mobilized social capital on job sector. Let me discuss Table 2 in detail and

then (discuss) Tables 3 and 4 in relation to Table 2.

Table 2 indicates that:

1) Accessed social capital (.48***) is associated with entry into the state sector

(versus small business sector).

2) Accessed social capital (.25*) is associated with entry into the MNC sector

(versus small business sector).

3) Accessed social capital (.23) is associated with entry into both the state and

MNC sectors.

4) Mobilized social capital (- 1.01***) is associated with entry into the small

business sector (versus state sector).

5) Mobilized social capital (- .20) is associated with entry into the MNC and small

business sectors.

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6) Mobilized social capital (- .81**) is associated with entry into the MNC sector

(versus state sector).

Bringing these results together, we may discern three interesting patterns: 1) accessed

social capital goes with state sector jobs, 2) mobilized social capital goes with small

business sector jobs, and 3) MNC jobs go with both accessed and mobilized social

capital.

These are important results because they illustrate how different kinds of social capital

go with different kinds of job sectors. For example, the more meritocratic the labour

market, the more salient the role of accessed social capital (i.e. the invisible hand of

social capital). In comparison, the less meritocratic the labour market (e.g. in small

business sector jobs), the more salient the role of contact use (which is the visible hand

of social capital). The reason why MNCs straddle both accessed and mobilized social

capital is that MNCs are most likely (relative to state and small business sectors) to

comprise a combination of formal and informal structures (Ritchie, 2009).

As the data is cross-sectional, we run into the problem of causality. That is, there is no

guarantee that the networks being examined (e.g. accessed social capital) were formed

prior to respondents’ entry into paid work. In fact, it may be argued that the networks

of older workers must be in part formed through their jobs. Hence one important

limitation of this study is the absence of longitudinal data.

The results in Table 3 (where accessed social capital is number of ‘private housing

dwellers’) replicate those in Table 2. Although the exact coefficients differ, their

patterning and therefore conclusions are exactly the same. A plausible reason for this is

the high correlation between education and private housing as high SES resources in

Singapore.

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The results in Table 4 are different from those in Tables 2 and 3. The most salient

difference is the null association between Chinese social capital and entry into state

sector jobs (.05). This result suggests that ethnicity in itself is not a resource (for

entering the lucrative state sector), whereas education and wealth are. As there can be

many disadvantaged individuals within a single high status ethnic group such as

Chinese, high ethnic group status is not a direct enough measure/proxy of resources.

TABLE 2. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF

ACCESSED (# OF UNIVERSITY GRADUATES) AND MOBILIZED SOCIAL CAPITAL

(CONTACT USE) ON JOB SECTORS

PREDICTORS

Logged odds of being in the state

sector versus small

business sector

Logged odds of being in the MNC sector

versus small business

sector

Logged odds of being in the state sector

versus MNC sector

Accessed social capital

(as # of university graduates)

.48***

(1.62)

.25*

(1.29)

.23

(1.26)

Mobilized social capital

(Job contact)

- 1.01***

(.37)

- .20

(.82)

- .81**

(.44)

Education (mid) .93** .27 .66†

(2.53) (1.32) (1.93)

Education (high) .88* .72* .16

(2.42) (2.05) (1.17)

Female .26 .00 .26

(1.30) (1.00) (1.30)

Chinese - 1.01*** - .21 - .80* (.37) (.82) (.45)

Indian .35 .31 .04 (1.42) (1.37) (1.04)

Age .20** .01 .19*

(1.23) (1.01) (1.21)

Intercept - 1.61 - 1.05

Change in -2LL 120.12*** 120.12***

N = 654 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low).

*P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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All the above results generally strongly support H1: that social capital facilitates entry

into highly-meritocratic jobs through the invisible hand of social capital rather than the

visible hand of social capital, however, with an important caveat: it is high-SES social

capital (education and wealth) rather than high ethnic status social capital that is

especially likely to facilitate entry into those meritocratic jobs.

That is, being ‘Chinese’ is not a factor in entering a meritocratic job, but rather being

well-educated or its high correlate, being wealthy is. On its own, the category Chinese

is not valuable unless accompanied by high-SES resources. It appears at least in the

context of Singapore, that it is predominantly class and SES resources that more fully

explain variations in life chances, rather than more diffusely, ethnic culture per se.

2) Accessed social capital is on average a more powerful facilitator of job success than mobilized

social capital (i.e. contact use)

Tables 5 to 7 are a series of step-wise OLS regression models estimating the effects of

accessed and mobilized social capital on earnings. Each table estimates the impact of a

different kind of accessed social capital, beginning with ‘number of graduates’ (Table 5),

followed by ‘number of private housing dwellers’ (Table 6), followed by ‘number of

Chinese’ (Table 7).

Each table estimates five models, the first three are main effects models, the last two are

models which incorporate interaction effects. Concerning the main effects models,

Model 1 estimates the effects of accessed and mobilized social capital (without controls).

Model 2 inserts the effect of education as a control, because 1) theoretically, education

should be all that matters in a meritocracy and 2) because education is highly correlated

with access to social capital. The point is to test if there are any social capital effects on

earnings independent of education effects. Model 3 includes other control variables

which potentially impact earnings (such as gender, ethnicity, age, age square as a proxy

for work experience etc.).

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TABLE 3. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF

ACCESSED (# OF PRIVATE HOUSING DWELLERS) AND MOBILIZED SOCIAL CAPITAL

(CONTACT USE) ON JOB SECTORS

PREDICTORS

Logged odds of being in the state

sector versus small

business sector

Logged odds of being in the MNC sector

versus small business

sector

Logged odds of being in the state sector

versus MNC sector

Accessed social capital

(as # of private housing

dwellers)

.28**

(1.33)

.21*

(1.24)

.07

(1.07)

Mobilized social capital

(Job contact)

- 1.04***

(.36)

- .23

(.79)

- .81**

(.44)

Education (mid) .89** .23 .66

(2.43) (1.26) (1.93)

Education (high) 1.34*** .88** .46

(3.80) (2.41) (1.58)

Female .32 .04 .28

(1.38) (1.04) (1.32)

Chinese - .93*** - .22 - .71*

(.39) (.80) (.49)

Indian .41 .33 .08

(1.51) (1.39) (1.08)

Age .15* - .02 .17* (1.16) (.98) (1.19)

Intercept - 1.66 - .95 Change in -2LL 109.10*** 109.10***

N = 653 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low).

*P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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TABLE 4. MULTINOMIAL LOGISTIC REGRESSION ESTIMATING THE EFFECTS OF

ACCESSED (# OF CHINESE) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON

JOB SECTORS

PREDICTORS

Logged odds of being in the state

sector versus small

business sector

Logged odds of being in the MNC sector

versus small business

sector

Logged odds of being in the state sector

versus MNC sector

Accessed social capital

(as # of Chinese)

.05

(1.05)

.04

(1.04)

.01

(1.01)

Mobilized social capital

(Job contact)

- 1.02***

(.36)

- .21

(.81)

- .81**

(.44)

Education (mid) 1.03*** .32 .71

(2.79) (1.37) (2.03)

Education (high) 1.70*** 1.13*** .57

(5.48) (3.11) (1.77)

Female .31 .04 .27 (1.37) (1.04) (1.31)

Chinese - 1.01** - .31 - .70 (.37) (.73) (.50)

Indian .40 .31 .09 (1.49) (1.36) (1.09)

Age .20** .01 .19*

(1.22) (1.01) (1.21)

Intercept - 2.43 - 1.50

Change in -2LL 100.68*** 100.68***

N = 654

OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low).

*P < .05 **P < .01 ***P < .001 (two tailed tests) (Odds ratio in parentheses)

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Table 5 provides compelling evidence that accessed social capital (as number of

university graduates) is a more powerful facilitator of job success than mobilized social

capital. For example, model 2 indicates that net of education, accessed social capital is

linked with higher earnings (.10***), while mobilized social capital is associated with

lower earnings (- .09**). With still further controls added in model 3, the positive and

significant effect of accessed social capital remains (.08***), suggesting that accessed

social capital (in the form of number of university graduates) has a highly independent

effect on status attainment.

Table 6 indicates similar results. Accessed social capital (this time as ‘number of private

housing dwellers’) is associated with greater earnings (.12*** in model 3), while

mobilized social capital is associated with lower earnings (- .06* in model 3).

The results in Table 7 are similar to Tables 5 and 6, in that net of education, accessed

social capital (as ‘number of Chinese’) is linked with higher earnings (.01* in model 2)

and mobilized social capital is linked with lower earnings (- .11** in model 2).

However there are important differences: for example, the effect of number of Chinese

on earnings (.01* in model 2 of Table 7) is less prominent than the effects of university

graduates (.10*** in model 2 of Table 5) and private housing dwellers (.14*** in model 2

of Table 6). And in fact, the relationship between number of Chinese and earnings

disappears when further controls are added (.01, model 3 of Table 7).

The latter results suggest that high ethnic status social capital is a less powerful source

of status attainment than high SES social capital. They also suggest that direct measures

of resources (such as access to contacts with education and wealth) are better predictors

of job success than are indirect measures of resources such as high status ethnic group

membership. That is, it is not Chinese culture (as a symbolic form of power per se) that

influences labour market outcomes, but access to education and wealth that matters.

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TABLE 5. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF

UNIVERSITY GRADUATES) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON

EARNINGS

PREDICTORS 1 2 3 4 5 Accessed social capital

(as # of university graduates)

.22*** .10*** .08*** .04† .08***

Mobilized social capital

(Job contact)

- .16*** - .09** - .05 - .04 - .03

Education (middle) .32*** .23*** .23*** .23*** Education (high) .69*** .54*** .55*** .54*** Female - .18*** - .18*** - .18*** Chinese .02 .02 .01 Indian .01 .01 .00 Age .06*** .06*** .06*** Age squared - .02*** - .02*** - .02*** Employed (part time) - .43*** - .43*** - .42*** PMT .32*** .33*** .32*** Clerical/service .11* .11* .11* MNC sector .11** .16*** .10* State sector .06 .11** .08* Social participation .00 .00 .01 [Accessed SC] X [MNC] .07* [Accessed SC] X [State] .08** [Mobilized SC] X [MNC] .04 [Mobilized SC] X [State] - .13 Constant 2.62 2.14 2.14 2.08 2.14 R square .29*** .42*** .60*** .61*** .60***

N = 656 OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low), No involvement in

voluntary organizations, small business sector. †P < .10 *P < .05 **P < .01 ***P < .001 (two tailed

tests) (Standard errors upon request)

3) Accessed social capital is especially valuable in highly-meritocratic job sectors

Tables 5, 6 and 7 indicate (in their respective model 4) positive interaction effects on

[accessed social capital] x [MNC], and [accessed social capital] x [state], suggesting that

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the invisible hand of social capital (i.e. university graduates, private housing dwellers

and Chinese) is especially likely to facilitate job success in meritocratic jobs.

TABLE 6. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF PRIVATE

HOUSING DWELLERS) AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON

EARNINGS

PREDICTORS 1 2 3 4 5

Accessed social capital

(as # of private housing dwellers)

.24*** .14*** .12*** .09*** .12***

Mobilized social capital

(Job contact)

- .23*** - .12*** - .06* - .05† - .06

Education (middle) .30*** .21*** .21*** .20***

Education (high) .69*** .54*** .54*** .54***

Female - .17*** - .17*** - .17***

Chinese - .00 .00 - .01 Indian .02 .03 .02

Age .05*** .05*** .05***

Age squared - .02*** - .02*** - .02***

Employed (part time) - .42*** - .41*** - .41*** PMT .31*** .32*** .31***

Clerical/service .10* .10* .10*

MNC sector .10** .14*** .08† State sector .06† .10** .08*

Social participation - .02 - .02 - .01

[Accessed SC] X [MNC] .05*

[Accessed SC] X [State] .06*

[Mobilized SC] X [MNC] .06

[Mobilized SC] X [State] - .11

Constant 2.65 2.19 2.20 2.16 2.20

R square .30*** .47*** .63*** .64*** .63***

N = 655

OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low), No involvement in

voluntary organizations, small business sector. †P < .10 *P < .05 **P < .01 ***P < .001 (two tailed tests)

(Standard errors upon request)

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TABLE 7. OLS REGRESSION ESTIMATING THE EFFECTS OF ACCESSED (# OF CHINESE)

AND MOBILIZED SOCIAL CAPITAL (CONTACT USE) ON EARNINGS

PREDICTORS 1 2 3 4 5

Accessed social capital (as # of Chinese)

.04*** .01* .01 - .00 .01

Mobilized social capital

(Job contact)

- .26*** - .11** - .05 - .04 - .03

Education (middle) .34*** .23*** .24*** .23***

Education (high) .86*** .66*** .65*** .66***

Female - .17*** - .17*** - .17***

Chinese .03 .02 .02 Indian .01 .02 .01

Age .06*** .06*** .06***

Age squared - .02*** - .02*** - .02***

Employed (part time) - .42*** - .42*** - .41*** PMT .35*** .35*** .34***

Clerical/service .12** .12* .12*

MNC sector .12** .01 .12* State sector .09* - .01 .11**

Social participation .02 .02 .02

[Accessed SC] X [MNC] .02*

[Accessed SC] X [State] .02*

[Mobilized SC] X [MNC] .01

[Mobilized SC] X [State] - .12

Constant 2.34 1.96 1.98 2.02 1.97

R square .09*** .40*** .59*** .59*** .59***

N = 656

OMITTED CATEGORIES. – Did not use job contact, Male, Malay, Education (low), No involvement in

voluntary organizations, small business sector. †P < .10 *P < .05 **P < .01 ***P < .001 (two tailed tests) (Standard errors on request)

There are no significant interaction effects concerning [mobilized social capital] x

[MNC] and [mobilized social capital] x [state] in all three tables (model 5). However,

the negative coefficients of [mobilized social capital] x [state] appear to be quite sizable

across them (i.e. - .13, - .11 and - .12 in Tables 5, 6 and 7 respectively with p-values

ranging from .12 to .15), suggesting that mobilized social capital (in the form of contact

155

use) tends to be rather useless, particularly in meritocratic jobs. These latter findings

juxtaposed with the positive interaction effects on accessed social capital, reinforce the

idea that embedded forms of social capital are much more leveraging than overt forms

of network mobilization in meritocratic jobs.

The greater relative payoffs to accessed social capital in meritocratic job sectors may be

due to meritocratic jobs being in general more challenging, and thus people who are

well-connected are more likely to do well on the job. But another explanation, which I

have emphasized in this paper, is that social capital, particularly in the embedded form,

continues to be highly leveraging under meritocratic conditions.

DISCUSSION

The goal of this paper has been to understand the interrelationship between labour

markets varying by levels of meritocracy and the role and payoffs to social capital in

those labour markets. Evoking the case of Singapore, a society characterized by a

highly-meritocratic core of labour markets, but supplemented by a ring of less

meritocratic labour markets, I ask: how do meritocratic constraints influence the role

and value of mobilized and accessed social capital? In labour markets that emphasize

formal credentials and meritocratic ways of recruitment, does social capital in fact cease

to matter? If social capital continues to matter, how so?

In a previous paper (Chua, 2010), I discovered three important characteristics regarding

the utilization of job contacts in Singapore. I found that 1) job contacts were rarely

utilized to enter highly-meritocratic jobs; 2) they were associated with lower earnings

and 3) they were associated with lower levels of education. I reasoned that job contacts

were not popular because of the high value and attention paid to academic credentials

in highly-meritocratic jobs. This current paper provides an important addendum: the

fact that job contacts are seldom used to enter meritocratic jobs does not automatically

mean that social capital has no role in meritocratic jobs. Job contacts may not matter

much in meritocratic hiring, but broader forms of social networking certainly do.

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Granted, education is important in the meritocracy, but social networks are themselves

strong predictors of education (Coleman, 1988, Erickson, 1996): we learn from our

networks how to do well in school, how to present ourselves during interviews, how to

be an effective employee on the job, how to file an application etc, and all these help to

facilitate entry into a meritocratic job. Taking an embedded view of social networks

means that social capital and meritocracy need not be mutually exclusive.

On the question of meritocracy, the multinational companies (MNCs) pose an

interesting case as they comprise a combination of formal and less formal elements. On

one hand, they do not have the strict formality of state bureaucracies. On the other

hand, they are not like small-scale businesses, that is, they straddle a middle ground

between formal bureaucracies and small businesses. If accessed social capital goes with

high meritocracy and mobilized social capital goes with low meritocracy, then we

would expect MNCs to go with a combination of accessed and mobilized social capital.

And that is exactly what I find.

Embedded social resources facilitate job success

According to the OLS regressions in Tables 5, 6 and 7, accessed and mobilized social

capital lead to significantly better and lower earnings respectively, suggesting that the

leveraging power of social networks manifests primarily through embedded rather than

overt social capital.

Although the list could be endless, embedded social capital may be thought to imply

the following resources: 1) unsolicited routine job information (Lin, 2000; Lin and Ao,

2008), 2) network-induced human capital (Coleman, 1988), 3) network-induced cultural

capital (Bourdieu, 1986), 4) network-induced diverse knowledge (Erickson, 1996), and 5)

network-induced bright ideas (Burt, 2004) -- all of which could help facilitate job success

significantly.

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The point here is that people may often benefit from networks without consciously

seeking to do so. Their enhanced job success is not the result of a conscious angling for

advantage, but an unanticipated outcome of being embedded in good connections

(Small, 2009). That is, people are reaping social networking benefits without actually

intending to do so.

Direct measures of high status resources, such as ‘number of graduates’ and ‘number of

private housing dwellers’, are especially likely to facilitate job success. Correlated

measures such as ‘number of Chinese’ are less powerful predictors, probably because of

sizable education and wealth heterogeneities within high status ethnic groups. Being

Chinese is not a resource on its own, unless accompanied by high education and

personal wealth.

Embedded social resources especially efficacious in meritocratic jobs

The positive interaction effects involving accessed social capital and the marginally

negative interaction effects involving mobilized social capital in Tables 5, 6 and 7

constitute strong evidence that social capital works primarily through the invisible hand

of accessed social capital rather than the visible hand of mobilized social capital in

meritocratic labour markets.

Meritocratic constraints do not spell the end of social capital. If we are prepared to

consider the role of embedded network resources, in addition to job contacts, we will

see how important the former are in facilitating job success. Indeed, meritocratic

constraints do not relegate social capital to a marginalized role, but inflects it with a role

that is at once embedded, but pervasive, and effective.

The embedded yet effective role of the invisible hand of social capital implies

contradictions within a system of meritocracy. If we go by the logic that education

should be all that matters in an ideal-typical meritocracy, then the fact that social capital

158

effects show up as positive and significant (despite controls for education), suggests

that meritocracies are networked societies.

The fact that job contacts tend to be ineffective in the most meritocratic of job sectors,

does not mean that other forms of networking are lacking or absent. As my data has

shown, accessed social capital is an important predictor of job success, even and

especially so in jobs which stress meritocracy. So then, in a real-life meritocracy,

unequal labour market outcomes are not just the result of unequal access to education

alone, but unequal access to broad bases of social capital as well.

The rhetoric of meritocracy in its striving for legitimation tends to privilege the

important role of human capital, while at the same time, downplaying the role and

value of social networking. Yet as this paper has shown, social capital contributes

significantly to status attainment (and hence inequality reproduction) even in the most

meritocratic of job settings.

CONCLUSION

When analyzing social capital, it is important to consider not only the networks that are

consciously mobilized in specific situations such as job searches, but also the broader

networks which people do not mobilize, but have access to (Lin, 2001). Indeed, the use

of a contact in a job search is at best a small and partial representation of a network, and

thus is not representative of the total capacity of a person’s social resources (Lin and Ao,

2008:111). The task of this present paper has been to understand how mobilized and

accessed forms of social capital jointly operate to affect status attainment in the context

of labour markets varying by levels of meritocracy.

Theoretically, this paper emphasizes the importance of institutional forces influencing

the role and value of social capital in labour markets. Evoking Singapore as a case

study, I show that in labour markets that emphasize meritocracy, social capital tends to

facilitate job success through accessed resources rather than mobilized resources. That

159

is, in labour markets that allocation rewards by fair-play and merit, the workings of

social capital tend to be more subtle than overt.

This paper stresses a contextual element to the study of social capital. At the end of the

day, it is not just social resources per se that influence status attainment, but equally

important, the a priori role of institutional factors impacting how much or how little

those social resources pay off. To add to the conventional ‘investments’ rhetoric of

social capital research (Lin, 2001), a more comprehensive study of social capital would

have to include an analysis of the conditional role of institutional constraints on social

capital, in addition to individual factors.

160

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Chapter 6 Conclusion

Context matters

When Granovetter (1985) wrote his important theoretical article on economic sociology,

he argued that sociologists, and in particular economists, needed a more relationally

focused view of economic action extending beyond individual action and rational

choice models. The fact that markets are often characterized by human cooperation and

competition, rather than atomism or social isolation (Uzzi, 1996) signals a need for

economic theories that are more relationally constituted.

But this invites a further question -- are analyzing networks in themselves sufficient for

generating a comprehensive understanding of economic action? The broad aim of my

three essays has been to verify the importance of networks, but also to extend the works

of Granovetter (1985), by suggesting that the study of networks be further anchored to

broader socio-historical frames of reference. By evoking aspects of social organization:

politics, economy, culture and society, my essays have sought to underscore the

importance of institutions as sources of the distribution, role and value of social capital.

The first paper (Chapter 3) highlighted two interesting results: 1) dominant gender and

ethnic groups tend to have more social capital than less dominant gender and ethnic

groups; and 2) ethnic and gender groups tend to access distinctive forms of social

capital. Distinctive patterns of network inequalities by gender and ethnicity are shown

to be partially due to the distinctive patterns of access that gender and ethnic groups

have to organizational settings such as schools, paid work and voluntary association.

These organizational settings may sometimes generate social capital more efficaciously

for some individuals/social groups.

165

The second paper (Chapter 4) moved from analyzing sources of social capital to

analyzing consequences of social capital. The paper showed that in certain sectors, such

as the state bureaucracy, social networking brings no distinctive advantages as

appointments are made exclusively on the basis of the academic credentials of the

candidates. That is, personal contacts are not always useful, especially in labour

markets that rely heavily on the signalling role of academic credentials to match people

to jobs.

The third paper (Chapter 5) is a build-up from the second paper. It argued that the

ineffectiveness of job contacts in meritocratic labour markets is not necessarily a sign

that social capital is irrelevant in contexts of meritocracy. The data showed that in

meritocratic job sectors, social capital facilitates status attainment primarily through

“accessed” social capital rather than “mobilized” social capital. That is, the status

attainment role of social capital in contexts of meritocracy tends to be more embedded

than overt.

Singapore as an excellent case study reflecting broader theoretical concerns

The interesting characteristics of Singapore society: as 1) meritocratic and yet elitist, 2)

multicultural and yet racially-ordered and 3) progressive and yet patriarchal, provided

an excellent opportunity for studying the link between macro-level conditions and

individuals’ experiences with social capital. My papers demonstrated that structural

factors are important aspects of the distribution, role and value of social capital, and

that what appear as cultural differences may in fact be institutional differences.

Although I have focused on Singapore as an anchoring case, my papers have at various

points, evoked data from countries such as the United States to provide a comparative

lens. While specifying the macro-micro link forms the overarching task and basis of the

dissertation, each paper contains finer theoretical contributions that speak to specific

issues in the literature on social capital. Broadly, the dissertation had delved into two

166

sets of research questions. The first set of questions pertain to sources of social capital:

how is social capital distributed among gender and ethnic groups and more

importantly, what is it about the social organization of gender and race that result in

social capital being stratified along gender and racial lines?

The second set of questions pertain to consequences of social capital: what does social

capital accomplish for people? What are the role and payoffs to different kinds of social

capital in different kinds of labour markets? Does social capital cease to be important in

labour markets that are meritocratic? To what extent does social capital work through

the invisible hand rather than the visible hand in meritocratic markets?

Unequal networks

Organizational settings such as schools, paid work and voluntary associations are fertile

ground for the accumulation of social capital. The unequal access to social capital

among gender and ethnic groups is really a function of their unequal access to

organizations that matter for network formation. In addition to having more social

capital in general, dominant gender and ethnic groups may often access distinctive

forms of social capital respectively.

My data showed that whereas men tend to have higher access to forms of social capital

such as non-kin and weak ties (but not well-educated and wealthy social capital),

dominant ethnic groups tend to have greater access to forms of social capital such as

well-educated and wealthy ties (but not non-kin). How should we explain such

distinctive patterns: that is, how and why do ascriptive forms of stratification lead to

such characteristic forms of network inequalities?

My data illustrated that ethnic groups’ unequal access to education (but equal access to

paid work) and gender groups’ unequal access to paid work and voluntary associations

(but equal access to education) account for much of why men and women, Chinese,

Malays and Indians tend to have such distinctive forms of social capital.

167

To be sure, the exact nature of the relationship between ascriptive categorical forms of

stratification and access to organizations will be expected to vary depending on the

actual conditions of specific societies. In countries like Japan, inequalities in education

continue to be quite strong among gender groups, while in the United States,

inequalities in education are especially stark among ethnic groups (especially between

blacks and whites) (Kao, 1995). There will be variations in the characteristic types of

social capital that gender and ethnic groups have access to, depending on societal

variations in gender and ethnic groups’ access to organizational settings where social

capital is formed.

The involved nature of my results signals a need for going deeper into the details,

because in reality, the distribution of social capital is more complex than simple. There

are several kinds of social capital that are potentially useful in labour markets, and

powerful gender and ethnic groups have greater access to only specific kinds of them.

So then, questions concerning the distribution of social capital should be posed in a

more nuanced way: instead of asking: who has more social capital? (as if there was only

one type of social capital), researchers should ask more carefully: who has more of what

types of social capital and why?

Job contacts, accessed social capital and status attainment

It is difficult to know the effects of social capital on status attainment without first

asking at least three questions: 1) what kinds of social capital are we talking about? 2)

what kinds of labour markets are being analyzed? and 3) who benefits from social

capital?

The contingent nature of the role of social capital is exemplified by my data showing

that whereas job contacts are often useless in meritocratic labour markets, they remain

substantially useful in less meritocratic labour markets. Job contacts are more useful

among low-educated job seekers and for entering jobs in industries such as wholesale,

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retail, hotels, restaurants and construction. By contrast, highly-educated job seekers are

more likely to rely on their credentials than their contacts for entering jobs.

The theoretical distinction between liberal and coordinated markets (Hall and Soskice,

2001) provides a useful framework for explaining the conditional role and value of job

contacts in labour markets varying by levels of meritocracy. Meritocratic labour

markets are coordinated structures because credentials are so closely tied to

employment outcomes. As employers in CME job sectors tend to emphasize

educational qualifications, job contacts have little room to influence the recruitment and

remuneration process. The situation is different in LME job sectors, where a

combination of formal qualifications and networks are invoked in the hiring process.

The liberal-coordinated distinction also sheds light on why job contacts are more likely

to be mobilized in countries like the United States as compared to Singapore. While the

active use of job contacts in the United States may often present itself on the surface as a

culture of networking, factors such as the loosely-coupled link between education and

labour markets are structural foundations of this networking ‘culture’ (Swidler, 1986).

Invisible networks and meritocracy

The meritocratic discourse -- that only effort and ability matter for getting ahead -- is

contradicted by evidence showing that accessed forms of social capital remain

extremely important for entering meritocratic jobs, even as mobilized forms of social

capital may often be less useful.

This invites the question: why does social capital work subtly in contexts of

meritocracy? One answer is the conceptual incompatibility between meritocracy and

networking as value systems. Overt ways of social networking often imply negative

characteristics such as: unethical, ulterior and schmoozing -- and these meanings are

antithetical to the ideological tenets of meritocracy where themes such as impartiality,

hiring based on ability not connections, and fairness, are upheld.

169

In a meritocratic world, embedded forms of social capital, possibly taking the form of

unsolicited job information and network-induced forms of cultural capital (and parental

influence) are much more likely to facilitate status attainment than overt forms of

network mobilization. Indeed, the politics of getting ahead in life in the context of a

meritocracy is not solely a matter of angling or manipulating networks for some specific

advantage, but more about being embedded in networks that in the routine course of

everyday life turn out to be beneficial and important for the person.

A meritocratic society is not a place where individuals are single-mindedly engaged in a

Hobbesian struggle for academic rewards, but more likely a society where connections

are established in schools, work and voluntary associations, and where individuals who

are embedded in them, find themselves with better life chances. Indeed, embedded

forms of social capital are significant sources of social advantage and should be further

researched, in addition to overt forms such as job contacts (Lin and Ao, 2008).

As access to human capital and social capital are closely intertwined with family

background and upbringing (Coleman, 1988), network and cultural disadvantages

originating from birth are often highly durable and difficult to eradicate, even as

meritocratic processes aim to equalize opportunities for as many as possible (Tilly,

1998). Individuals with influential family backgrounds are often able to secure big

advantages through social capital. In turn, these networks facilitate academic

achievement. When someone does well in school, it is not always due to his/her own

efforts alone, but the social and academic support that he/she receives from peers,

family, teachers and professors, in addition to personal effort.

Reproduction of inequalities through social capital

In a merit-based system, the invisible hand of social capital is a significant source of

social stratification. That is, the winners in a meritocracy are not those with sterling

academic results alone, but those who also have sterling results and networks. Human

capital and social capital, while analytically distinct, are really much more integrated in

170

everyday life. A good education and having highly-educated networks make for a

powerful combination in meritocracies as the two are highly leveraging resources

(Coleman, 1988).

In this regard, lower-educated individuals are doubly disadvantaged. First, low levels

of education do not augur well in a merit-based system. Second, based on the principle

of homophily, lower-educated individuals are significantly less likely (than their

higher-educated counterparts) to have access to well-educated networks (McPherson,

Smith-Lovin and Cook, 2001). The practice of early academic streaming in Singapore

gives rise to a situation where the bright are put together with others like them, just as

the non-achievers are put with others like them. The result is segregated classrooms,

schools, and eventually networks.

Michael Young (1958) was right in predicting the widening gulf of elites and masses in

meritocratic society. A significant contribution of social capital research is the

demonstration that social networks have a substantial role to play in fostering this

widening gulf. To be sure, educational systems have, to an admirable extent, closed the

gap in access to educational resources, but many wealthy families have mobilized

education as a vehicle (e.g. legacy admissions) to reproduce cultural, network and

educational advantages (Bowles and Gintis, 1976).

In the end, a meritocratic system can only be partially meritocratic. If we delve deeper

into the dynamics of a merit system, we see that inequalities of opportunities (i.e.

unequal starting lines) are pervasive, and indeed, it is difficult, if not practically

impossible, to ensure a level playing field. A meritocracy is purest in a hypothetical

‘first generation’ when everyone starts out equal, but once societies advance and

families have accumulated wealth: certainly unevenly, then the mantra of equal

opportunities can only be a myth. While meritocracies have helped many to climb out

of their situations, they have also ensured that privileged children have pulled ahead

171

from the less fortunate by sizable amounts because of family resources (e.g. the child

who gets to be educated overseas because the parents can afford it).

Next steps

An obvious next step in my analysis would be to ascertain the extent to which network

inequalities account for wage inequalities between gender groups and ethnic groups,

and this is what I intend to work on most immediately after the PhD. Some of my

preliminary analyses show that some significant portion of ethnic inequalities in wages

can be explained by ethnic differences in access to social capital, suggesting that ethnic

inequalities in earnings cannot be attributed to education alone (as a meritocratic

discourse would predict), but must evoke ethnic inequalities in social capital as well.

Limitations

This dissertation was not without limitations. The most general weakness is that the

results are based upon cross-sectional data, rather than more ideally, longitudinal data.

The issue of causality invariably crops up in situations like this. For example, in the

first paper, is it work that generates social capital or social capital that generates work?

Similarly, for the third paper, did accessed social capital come before the current job and

therefore facilitated entry into it, or did it come only as a result of the current job?

Another limitation is the reliance on a single case study rather than more ideally, data

from multiple source countries. It would have been ideal to have comparative data, but

given the current circumstance, my partial solution was to position Singapore as an

anchoring case and analyze and discuss it with reference to earlier research on countries

such as the United States.

A third limitation is the reliance on name generator data, which according to a previous

study (Marin, 2004) tends to elicit stronger ties rather than weaker ties. My study deals

partially with this problem by incorporating a broad range of name generators (fourteen

172

altogether). That is, I cast a wide net over multiple social domains so that the extent of

the strong-tie bias will not be so severe. Strong ties and name generators may be

strongly correlated, but it is not name generators per se that cause strong ties. If the

name generators deployed are widely-ranging, the elicited ties will likely include weak

ties as well.

As these three limitations are design and budget limitations, they are not an actual

indictment of the quality of the data itself. The data was collected by a professional

research company, AC Nielsen, using a group of experienced mostly middle aged

women trained to do interviews in the Singapore context. Logic checks were done by

the company and verified by the Singapore university research team of which I was an

instrumental part. Overall, the data was valuable and rich for advancing our theoretical

understanding concerning the nature of social capital in a contemporary social context.

Final words

If there is a single take-home message in this dissertation, it would be that social capital

does not exist in a vacuum, but is bound up with social contexts which substantially

influence its distribution, role and value. These essays have suggested that

investigations into social capital should move beyond a purely network approach, but

deal with networks as being intertwined within larger aspects of social structure such as

politics, economy, culture, education, ideology and society.

This dissertation has focused primarily on Singapore, but its broader theoretical

relevance is that it highlights an instance of how larger socio-structural factors may

often affect people’s experiences with social capital. Of course, given that each society

is qualitatively different, the nature of the interplay between context and social capital

will be different. That should not faze us. In my opinion, the future of social capital

research is not with trying to come up with a grand theory of how social capital works,

but more contextually, our aim should be to understand how diverse social

environments give rise to correspondingly diverse experiences with social capital.

173

References

Bowles, Samuel and Herbert Gintis. 1976. Schooling in Capitalist America: Educational Reform and the Contradictions of Economic Life. New York: Basic Books.

Coleman, James S. 1988. “Social Capital in the Creation of Human Capital.” American Journal of Sociology 94:S95-S120.

Erickson, Bonnie H. 2004. “The Distribution of Gendered Social Capital in Canada.” Pp. 27-50 in Creation and Returns of Social Capital: A New Research Program, edited by Henk Flap and Beate Volker. New York, NY: Routledge.

Feld, Scott L. 1981. “The Focused Organization of Social Ties.” American Journal of Sociology 86:1015-1035.

Gamoran, Adam. 2001. “American Schooling and Educational Inequality: A Forecast for the 21st Century.” Sociology of Education (Extra Issue):135-53.

Granovetter, Mark. 1985. “Economic Action, Social Structure, and Embeddedness.” American Journal of Sociology 83: 1420-1443.

Hall, Peter A. and David Soskice. 2001. Varieties of Capitalism: The Institutional Foundations of Comparative Advantage. Oxford: Oxford University Press.

Kao, Grace. 1995. “Asian Americans as Model Minorities? A Look at their Academic Performance.” American Journal of Education 103:121-59.

Lin, Nan. 2000. “Inequality in Social Capital.” Contemporary Sociology 29:785-95.

Lin, Nan and Dan Ao. 2008. “The Invisible Hand of Social Capital: An Exploratory Study.” Pp. 107-132 in Social Capital: An International Research Program, edited by Nan Lin and Bonnie H. Erickson. Oxford: Oxford University Press.

Marin, Alexandra. 2004. “Are Respondents More Likely to List Alters with Certain Characteristics?” Social Networks 26: 289-307.

McPherson, J. Miller, Lynn Smith-Lovin & Cook, J. M. 2001. “Birds of a Feather: Homophily in Social Networks.” Annual Review of Sociology 27: 415-444.

Swidler, Ann. 1986. “Culture in Action: Symbols and Strategies.” American Sociological Review 51: 273-286.

Tilly, Charles. 1998. Durable Inequality. Berkeley, CA: University of California Press.

174

Uzzi, Brian. 1996. “The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect.” American Journal of Sociology

61:674-698.

Young, Michael. 1958. Rise of the Meritocracy. London: Thames & Hudson.

175

Appendices

Appendix A -- List of name generators

1) Looking back over the past six months, who were the people with whom you discussed matters that are important to you?

2) You mentioned that you would ask someone you know to lend the money to you. Can you tell me who would this person be?

3) Suppose you feel just a bit down or depressed. And you wanted to talk to someone about it. Who could you turn to?

4) You mentioned that you came to know about this job through a friend/person. Can you tell me what is the name or initials of this friend/person?

5) You mentioned that someone in the company helped you get this job. Can you tell me what is the name or initials of this person?

6) Other than your spouse and you, who is your main childcare giver?

7) Can you give me the name or initials of the person whom you will ask or have asked to look after your house?

8) Can you tell me the name or initials of the person who you get together with to discuss about hobbies or spare-time interests?

9) Thinking of the past six months, who were the two or three people with whom you spent the most time doing social activities with?

10) Can you please give me the name or initials of one of the army friends whom you still keep in contact with?

11) Can you tell me the name or initials of your most regular sports or exercise partner?

12) From among the people in these voluntary associations, who have you spoken to most recently?

13) Can you tell me the name or initials of important people whose names are currently missing from the list?

14) Do you know people who are from a different ethnic group as yours – people whom you could talk to, laugh with, have a good time?

176

Appendix B – Questionnaire Q’naire No : _____________

English/ Chinese

Study ID

42161

(101-105)

Resp. No.

(106-109)

Interviewer No.

(113-117)

Interview Length

(118-119)

No. Of Queries

(120-121)

Reference No.

(122-126)

ACNielsen Research (Singapore) Pte Ltd 55 Newton Road #15-01 Revenue House Singapore 307987 Tel: 6252 8595 Feb 2005 (CCM)

Name: ___________________________________________________ Address: ___________________________________________________ ___________________________________________________ Tel No: ___________________________________________________ Interviewer's Name: ___________________________________________________ Date of Interview: ___________________________________________________ Time Started/ Ended : _________________________to _________________________ Q1 RECORD POSTAL DISTRICT

(R1) Postal Code (127-132)

Q2 RECORD FLOOR LEVEL

(R1) FLOOR LEVEL (133-134)

177

SECTION A: DEMOGRAPHICS Q3 ASK ALL

SHOWCARD May I know your age group?[SA]

请问你是属于哪个年龄组？ [SA]

Code (135)

Route

19 years or below 1 CLOSE

20 - 24 years 2 CLOSE

25 - 29 years 3 Q4

30 - 34 years 4 Q4

35 - 39 years 5 Q4

40 - 44 years 6 Q4

45 - 49 years 7 Q4

50 - 55 years 8 Q4

56 years and above 9 CLOSE

Q4 RECORD GENDER[SA]

Code (136)

Route

Male 1

Female 2

Q5 ASK ALL

SHOWCARD May I know what is your marital status? [SA] 请问你的婚姻状况是什么？[SA]

Code (137)

Route

Single - currently attached 1

Single - currently not attached 2

Engaged 3

Married 4

Separated 5

Divorced 6

Widowed 7

Refused 8

Q6 ASK ALL

Do you have any children? (include adopted children) [SA] 你有没有孩子？(包括领养的孩子)[SA]

Code (138)

Route

Yes 1 Q7

No 2 Q8

178

Q7a ASK ALL WHO HAVE CHILDREN - CHECK Q6 CODE 1

Can you please tell me what is the age of your child/ children? Interviewer : List from oldest to youngest. 可不可以告诉我你的孩子的年龄?

Q7a

Record age of child

(139-140)

(R1) RECORD AGE OF CHILD 1: _ _

(141-142)

(R2) RECORD AGE OF CHILD 2: _ _

(143-144)

(R3) RECORD AGE OF CHILD 3: _ _

(145-146)

(R4) RECORD AGE OF CHILD 4: _ _

(147-148)

(R5) RECORD AGE OF CHILD 5: _ _

(149-150)

(R6) RECORD AGE OF CHILD 6: _ _

(151-152)

(R7) RECORD AGE OF CHILD 7: _ _

(153-154)

(R8) RECORD AGE OF CHILD 8: _ _

(155-156)

(R9) RECORD AGE OF CHILD 9: _ _

(157-158)

(R10) RECORD AGE OF CHILD 10: _ _

Q8 ASK ALL

SHOWCARD May I know what is your nationality? [SA] 请问你的国籍是什么？[SA]

Code (164)

Route

Singapore Citizen 01 Q10

Citizen of China 02 Q9

Citizen of Hong Kong 03 Q9

Citizen of India 04 Q9

Citizen of Indonesia 05 Q9

Citizen of Malaysia 06 Q9

Citizen of Taiwan 07 Q9

179

Q9 ASK ALL WHO ARE NOT SINGAPORE CITIZENS - CHECK Q8 CODES 2 or 6

Can you please tell me what is your current residency status in Singapore? [SA] 请问你在新加坡目前的居留身份是什么？ [SA]

Code (166)

Route

Permanent Resident (PR) 1

Dependent Pass Holder 2

Employment Pass Holder 3

Student Pass Holder 4

Social Visit Pass Holder 5

Work Permit Holder 6

Q10 RECORD ETHNIC GROUP[SA]

Code (167)

Route

Chinese 01

Malay 02

Indian 03

Others (pls. specify) ____________________ 04

Q11 ASK ALL

SHOWCARD May I know what is your religion?[SA] 请问你信仰哪个宗教？ [SA]

Code (170)

Route

Buddhism 01

Taoism/ Chinese traditional beliefs 02

Islam 03

Hinduism 04

Sikhism 05

Protestant 06

Roman Catholic 07

Free-thinker 08

Others (pls. specify) ____________________ 09

Christianity 10

Refused 20

180

Q12 ASK ALL

Can you please tell me what is your housing type?[SA] 请问你住在哪一类的房子？[SA]

Code (172)

Route

HDB 1 to 2-room 01

HDB 3-room 02

HDB 4-room 03

HDB 5+-room 04

HDB Executive/ Mansionette 05

Executive Condominium/HUDC 06

Private Apartment/Condominium 07

Landed Property (Bungalow, Semi-Detached/ Terrace) 08

Shophouse 09

Others (pls. specify) ____________________ 10

Refused 11

Q13 ASK ALL

Do you, or anyone else in your family living in this house or elsewhere, own this house?[SA] 你或者住在这里或其它地方的家人是否拥有这所房子？[SA]

Code (174)

Route

Yes, we own this house 01 Q14

No, we rent this house (i.e. we pay rent) 02 Q15

Others (pls. specify) ____________________ 03 Q15

Refused 10 Q15

Q14 ASK ALL WHO OWN THEIR HOUSE - CHECK Q13 CODE 1

Can you please tell me what is the PRESENT VALUE OF YOUR HOUSE? By this, I mean the amount of money that this house will bring you if you sold it today. It does not matter if you do not know the exact value that this house is worth, we just need an estimation. INSTRUCTION TO INTERVIEWER: If the respondent says 'Don't know/ Not sure/ Can't say', please record '99999 99999' in the space provided below. If the respondents refuses to give an answer, please record '88888 88888' in the space provided below. 可不可以告诉我你的房子目前的价值多少？换句话说，如果你现在把这所房子卖掉，可以卖多少钱。如果你不知道这房

子确实的价值也无所谓，我们只想知道大概的估计。

(R1) RECORD ESTIMATED PRESENT VALUE OF HOUSE: S$

(175-216)

Q15 ASK ALL

Does anyone in this household own a car? [SA] 这房子有没有任何人拥有汽车？[SA]

Code (222)

Route

Yes 1

No 2

181

Q16 ASK ALL Can you please tell me what is the highest level of education you have attained? [SA]

请问你的最高学历是什么？[SA]

Code (223)

Route

No formal education 01

Some Primary 02

Completed Primary (PSLE) 03

Some Secondary 04

Completed Secondary ('O'/ 'N' Levels) 05

ITE/ Vocational Institute 06

Completed Pre-U/ Junior College ('A' levels) 07

Polytechnic (Diploma) 08

Professional Qualifications/ Other Diplomas 09

University Graduate (Basic Degree/ Honors Degree) 10

University Postgraduate (MA, MSc, MBA, PhD, Graduate Diploma) 11

Refused 12

Q17 ASK ALL

What is your current occupational status?[SA] 你目前的就业情况是什么？[SA]

Code (225)

Route

UNEMPLOYED: Unemployed - for more than one week but less than six months 01 Q19

Unemployed - for more than six months 02 Q19

Retired 03 Q19

Student 04 Q19

Housewife/ Home-maker 05 Q19

Student on school attachment 06 Q19

EMPLOYEE: Employed part-time 07 Q19

Employed full-time 08 Q19

SELF-EMPLOYED: Self-employed WITHOUT any business partners/ workers under me 09 Q19

Self-employed WITH business partners/ workers under me 10 Q18

Refused 11 Q19

Q18 ASK ALL WHO ARE SELF-EMPLOYED WITH BUSINESS PARTNERS/ WORKERS UNDER THEM - CHECK Q17 CODE 10 How many PAID EMPLOYEES do you have (excluding yourself)? INSTRUCTION TO INTERVIEWER: If the respondent refuses to provide an answer, please record '999' in the space provided.

你有几位受薪的职员(不包括你自己)？

(R1) RECORD NO. OF PAID EMPLOYEES: (227-229)

182

Q19 ASK ALL FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: Can you please tell me what was your last occupation? FOR THOSE WHO ARE CURRENTLY EMPLOYED: Can you please tell me what is your present occupation? INSTRUCTION TO INTERVIEWER: Please record the exact job designation mentioned: ________________________________________[SA]

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: 请问你最近的一份职业是什么？ FOR THOSE WHO ARE CURRENTLY EMPLOYED: 请问你目前的职业是什么？

Code (235)

Route

Legislators, Senior Officials and Managers 01

Professional 02

Associate Professionals and Technicians 03

Clerical Workers 04

Service Workers and Shop and Market Sales Workers 05

Agricultural and Fishery Workers 06 Production Craftsmen and Related Workers 07

Plant and Machine Operators and Assemblers 08

Cleaners, Labourers and Related Workers 09

Others 10

Never worked before 11 Q22

183

Q20 ASK ALL WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1-10

FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: Which industry did you work in previously? FOR THOSE WHO ARE CURRENTLY EMPLOYED: Which industry do you currently work in? INSTRUCTION TO INTERVIEWER: Please record the exact industry description mentioned: ________________________________________ [SA] FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: 请问你以前在哪个行业工作？ FOR THOSE WHO ARE CURRENTLY EMPLOYED: 请问你目前在哪个行业工作？ [SA]

Code (245)

Route

Agriculture & Forestry 01

Fishing 02

Mining & Quarrying 03

Manufacturing 04

Electricity, Gas & Water 05

Construction 06

Wholesale & Retail Trade 07

Hotels & Restaurants 08

Transport, Storage & Communications 09

Financial Intermediation 10

Real Estate, Renting & Business Activities 11

Public Administration & Defence 12

Education 13

Health & Social Work 14

Other Community 15

Social & Personal Service Activities including repair of vehicles 16

Others (pls. specify) ____________________ 17

Domestic Work Activities 18

Refused 30

184

Q21 ASK ALL WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1-10

SHOWCARD FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: Please look at this showcard and tell me which organization type does the company that you worked for previously, fall under. FOR THOSE WHO ARE CURRENTLY EMPLOYED: Please look at this showcard and tell me which organization type does the company that you are currently working for, fall under. [SA] FOR THOSE WHO ARE CURRENTLY UNEMPLOYED:

请看这张卡，然后告诉我你以前工作的那间公司属于哪种机构？ FOR THOSE WHO ARE CURRENTLY EMPLOYED: 请看这张卡，然后告诉我你目前工作的那间公司属于哪种机构？[SA]

Code (255)

Route

Singapore-owned private firm 01

Government-linked corporation 02

Multi-national corporation 03

Statutory board 04

Civil service/ Military 05

Non-profit organization 06

Overseas Company 07

Don't know/ Not sure/ Can't say/ Can't remember 19

Refused 20

185

Q22 ASK ALL

SHOWCARD On average, how much do the people in your household earn altogether in a month? 你全家人每个月的平均总收入是多少？ [SA]

Code (257)

Route

No income 01

Below S$750 02

S$751 - 1,000 03

S$1,001 - 1,500 04

S$1,501 - 2,000 05

S$2,001 - 2,500 06 S$2,501 - 3,000 07

S$3,001 - 3,500 08

S$3,501 - 4,000 09

S$4,001 - 5,000 10

S$5,001 - 6,000 11

S$6,001 - 7,000 12

S$7,001 - 8,000 13

S$8,001 - 9,000 14

S$9,001 - 10,000 15

S$10,001 - 11,000 16

S$11,001 - 12,000 17

S$12,001 - 13,000 18

S$13,001 - 14,000 19

S$14,001 - 15,000 20

Above S$15,000 21

Don't know/ Not sure/ Can't say/ Can't remember 22

Refused 23

186

Q23 ASK ALL WHO WORKS OR WORKED BEFORE CHECK Q19 CODE 1-10

SHOWCARD FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: Can you please tell me on average, how much did you yourself earn in a month previously? FOR THOSE WHO ARE CURRENTLY EMPLOYED: Can you please tell me on average, how much do you yourself currently earn in a month?[SA] FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: 请问你以前每个月的平均收入是多少？ FOR THOSE WHO ARE CURRENTLY EMPLOYED: 请问你目前每个月的平均收入是多少？ [SA]

Code (260)

Route

No income 01

Below S$500 02

S$501 - 750 03

S$751 - 1,000 04

S$1,001 - 1,500 05

S$1,501 - 2,000 06

S$2,001 - 2,500 07

S$2,501 - 3,000 08

S$3,001 - 3,500 09

S$3,501 - 4,000 10

S$4,001 - 5,000 11

S$5,001 - 6,000 12

S$6,001 - 7,000 13

S$7,001 - 8,000 14

S$8,001 - 9,000 15

S$9,001 - 10,000 16

Above S$10,000 17

Can't remember 18

Refused 19

187

SECTION B: LIFE SITUATIONS AND EVENTS

Q24 ASK ALL

SHOWCARD Now, I would like you to give me a rough idea of some of the things that have taken place in your life over the past one year. Please take a look at the items listed on this showcard and tell me if any of these things have happened to you or any person in your household in the past one year. INSTRUCTION TO INTERVIEWER: If the respondent selects Code 31, he/ she is not allowed to select any other responses. 现在，我想大概知道在过去一年内，你生活中发生的一些事物？ 请看这张卡上列出的事项，请问你或你家里任何人在过去一年内有没有经历过这里的任何事件？ [MA]

Code (262)

Route

JOB/ MAKING A LIVING: Got a new job 01

Got a promotion or pay raise at work 02

Got retrenched or lost a job 03

Searched for a new job 04

Experienced problems with own business 05

Experienced financial problems 06

Experienced employment discrimination 07

NEW EXPERIENCES: Got married/ engaged 08

Found a new close friend 09

Found a new hobby or sport 10

Found a new religious experience 11

Went for a holiday outside of Singapore 12

Bought a new car 13

Became pregnant/ Had a baby 14

Issues related to child/ children's schooling needs (e.g. needed to find a school for child etc.) 15

HOUSE MAINTENANCE: Moved house 16

Tried to move house or buy a home 17

Needed help to carry heavy furniture 18

Had broken/ spoilt appliances 19

Needed home repairs or renovations 20

Experienced problems with a neighbour 21

Did not have enough help with housework 22

DIFFICULT TIMES: Experienced serious illnesses or health problems/ injuries 23

Experienced the death of a family member/ friend 24

Was a victim of crime 25

Experienced serious relationship problems (boyfriend/ girlfriend, spouse) 26

Experienced difficulties at school (e.g. with people, grades etc.) 27

Was 'played out' by others (e.g. sabotaged etc.) 28

Lost something precious (e.g. handphone etc.) 29

Experienced difficulties at work (e.g. being scolded by boss, engulfed by office politics etc.) 30

188

Q24 ASK ALL SHOWCARD Now, I would like you to give me a rough idea of some of the things that have taken place in your life over the past one year. Please take a look at the items listed on this showcard and tell me if any of these things have happened to you or any person in your household in the past one year. INSTRUCTION TO INTERVIEWER: If the respondent selects Code 31, he/ she is not allowed to select any other responses.

现在，我想大概知道在过去一年内，你生活中发生的一些事物？ 请看这张卡上列出的事项，请问你或你家里任何人在过去一年内有没有经历过这里的任何事件？ [MA]

Code (262)

Route

NONE OF THE ABOVE 31 Q26

Q25 ASK ALL WHO GAVE A RESPONSE IN Q24- SELECTED ANY RESPONSE BETWEEN

CODES 1 TO 30 When these things happened [READ OPTIONS SELECTED IN Q24], did you discuss them with anyone? [SA]

当你[READ OPTIONS SELECTED IN Q24]的时候，你有没有跟任何人谈论过这事情？ [SA]

Code (266)

Route

Yes 1

No 2

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent Now, I will ask you about some of the people in your life. Depending on the question asked, they may include your relative, boss, co-worker, neighbor, friend, or even an acquaintance. Please provide me with their names or initials. Let's start with a general question. 我们想了解你生活中的一些人物。根据个别的问题，他们有可能包括你的亲戚、老板、同事、邻居、朋友或者只是认识的人。请

告诉我他们的名字或简称。我们先问一个基本的问题。 Q26 ASK ALL

From time to time, most people DISCUSS IMPORTANT MATTERS with others, and what these IMPORTANT MATTERS are, differ and vary from one person to another. It can be about anything - your job situation, new experiences, happenings in the family, relationships etc.; as long as it is something that is IMPORTANT to you. If you look back at the past six months, who were the people with whom you DISCUSSED MATTERS THAT ARE IMPORTANT TO YOU?. Please provide me with two names. 多数人会时不时跟别人谈论重要的事情。至于重要的事情是什么，每个人的看法各有不同。它可以是任何事情，包括你

的工作、新的体验、家里发生的事情、人际关系等等，只要是你自己觉得重要的事情。 请回想过去的6个月，你曾跟哪些人谈论过你觉得重要的事情？请告诉我两个名字。

(R1) RECORD NAME/ INITIALS OF PERSON 1:

________________________________________________________________________________ ________________________________________________________________________________

189

Q26 ASK ALL From time to time, most people DISCUSS IMPORTANT MATTERS with others, and what these IMPORTANT MATTERS are, differ and vary from one person to another. It can be about anything - your job situation, new experiences, happenings in the family, relationships etc.; as long as it is something that is IMPORTANT to you. If you look back at the past six months, who were the people with whom you DISCUSSED MATTERS THAT ARE IMPORTANT TO YOU?. Please provide me with two names. 多数人会时不时跟别人谈论重要的事情。至于重要的事情是什么，每个人的看法各有不同。它可以是任何事情，包括你

的工作、新的体验、家里发生的事情、人际关系等等，只要是你自己觉得重要的事情。

请回想过去的6个月，你曾跟哪些人谈论过你觉得重要的事情？请告诉我两个名字。

(267-268)

(R2) RECORD NAME/ INITIALS OF PERSON 2:

________________________________________________________________________________ ________________________________________________________________________________

(269-270)

190

Q27 ASK ALL

In the course of living, some people run into financial problems while others are lucky enough not to. Now, let's assume that you need to get a large sum of money together to save your business or to repay some debts. What would you do? Would you... [READ LIST]? [SA] 在生活中，有些人会不幸遇到经济问题。现在，假设你需要一大笔钱来援助你的生意或偿还一些债

务。请问你会怎么做？你会不会... [READ LIST]?

Code (271)

Route

Ask someone you know to lend it to you 找你认识的人借钱给你

1 Q28

Go to a bank or credit union to get a loan 到银行或信贷机构去贷款

2 Q29

Ask someone you know to lend it to you AND go to a bank or credit union to get a loan 找你认识的人借钱给你，也到银行或信贷机构去贷款

3 Q28

Do something else 做其它的事情

4 Q29

Q28 ASK ALL WHO WILL ASK SOMEONE THEY KNOW TO LEND MONEY TO THEM - CHECK Q27 CODES 1 OR 3

You mentioned that you would ask someone you know to lend the money to you. Can you please tell me who would this person be? 你说你会跟你认识的人借钱。请问你会跟谁借呢？

(R1) RECORD NAME/ INITIALS OF PERSON 3:

________________________________________________________________________________ ________________________________________________________________________________

(272-273) Q29 ASK ALL(SKIP TO Q30 IF IMMEDIATE FAMILY WAS MENTIONED IN Q28

Let's just say that you face a financial crisis of some kind one day. Do you think your IMMEDIATE FAMILY would be willing to help you out? [SA] 假如说有一天你遇到经济困难。你认为你的家人会不会愿意帮助你？[SA]

Code (274)

Route

Yes 1 No 2

Don't know/ Not sure/ Can't say 3

Q30 ASK ALL (SKIP TO Q31 IF RELATIVES WERE MENTIONED IN Q28

What about any of your RELATIVES? Do you think they will be willing to help you out? 那么你任何的亲戚呢？你认为他们会不会愿意帮助你呢？[SA]

Code (275)

Route

Yes 1

No 2

Don't know/ Not sure/ Can't say 3

Some relatives will help while others will not 4

I don't have any relatives 5

Q31 ASK ALL

Did you borrow a large amount of money from someone over the past 12 months? [SA] 你在过去12个月内有没有跟人借过一大笔钱？[SA]

Code (276)

Route

Yes 1

No 2

191

SECTION C: MENTAL STATE AND WELL-BEING Q32 ASK ALL

DROPCARD We have talked about life events, situations and circumstances so far. Now, let's talk about how you have been FEELING over the PAST ONE WEEK. For each of the following statements, please select a score between 1 to 4, that best describes HOW OFTEN you felt this way DURING THE PAST ONE WEEK. [SA] 我们谈过了生活中发生的事、状况和机遇。现在，我们谈谈你在过去一个星期内的心情感觉。 针对以下各个句子，请从1到4之中选一个号码来说明你在过去一个星期内多常有这种感觉。 [SA]

During the past week …….

Rarely or none of the

time (< 1 day)

Some or a little of the time (1 - 2

days)

Occasionally or a

moderate amount of time (3 - 4

days)

Most or all of the time (5 - 7 days)

(277)

(R1) I was bothered by things that usually don't bother me 1 2 3 4

(278)

(R2) I had trouble keeping my mind on what I was doing 1 2 3 4

(279)

(R3) I felt depressed 1 2 3 4

(280)

(R4) I felt like everything I did was an effort 1 2 3 4

(313)

(R5) I felt hopeful about the future 1 2 3 4

(314)

(R6) I felt fearful 1 2 3 4

(315)

(R7) My sleep was restless 1 2 3 4

(316)

(R8) I was happy 1 2 3 4

(317)

(R9) I felt lonely 1 2 3 4

(318)

(R10) I felt tired and could not get going 1 2 3 4

192

Q33 ASK ALL

Now, suppose you feel just a bit down or depressed. And you wanted to talk to someone about it. Who could you turn to? 现在，假设你感到有点消沉或抑郁，而且你想向别人倾诉。你可以向谁倾诉？

(R1) RECORD NAME/ INITIALS OF PERSON 4:

________________________________________________________________________________ ________________________________________________________________________________ (319-320)

(R2) RECORD NAME/ INITIALS OF PERSON 5:

________________________________________________________________________________ ________________________________________________________________________________

(321-322) Q34 ASK ALL

Generally speaking, how would you feel if you had to go for some form of counseling to deal with a personal problem? Would you be...[READ LIST]? [SA] 一般而言，如果你需要寻求某些形式的辅导来解决一些个人的问题，你会感觉如何？你会不会...[READ LIST]?[SA]

Code (323)

Route

Very ashamed to let others know 很羞于让人知道

1

Ashamed to let others know 羞于让人知道

2

A bit ashamed to let others know 有一点羞于让人知道

3

Not ashamed at all to let others know 完全不会羞于让人知道

4

Q35 ASK ALL Can you please tell me if you have gone for some form of formal counseling over the past 12 months?[SA] 请问你在过去12个月内有没有去寻求过专业的辅导？[SA]

Code (324)

Route

Yes 1

No 2

193

INSTRUCTION TO INTERVIEWER: Please read out the following text to the respondent: So far, we have talked about your general life situation, some of your present day feelings as well as your well-being as a whole. Now, let's focus on more specific areas of your life. Let's start with your WORK. 我们已经谈过了你一般的生活、你最近的心情和你整体的状况。现在，我们专注谈你生活中的各方面。就从你的工作开始吧。 Q36 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10

Generally speaking, how much would you say you like your present job? Do you... [READ LIST]? [SA]

一般而言，你有多喜欢你目前的工作？你是不是... [READ LIST]?[SA]

Code (325)

Route

Don't like it at all 完全不喜欢

1

Don't like it 不喜欢

2

Like it 喜欢

3

Like it very much 非常喜欢

4

Q37 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 How satisfied would you say you are with your current salary? Are you... [READ LIST]?[SA] 你对你目前的薪金有多满意？你是不是... [READ LIST]?[SA]

Code (326)

Route

Not satisfied at all 完全不满意

1

Not satisfied

不满意

2

Quite satisfied 相当满意

3

Very satisfied 很满意

4

Q38 ASK ALL WHO ARE CURRENTLY UNEMPLOYED - CHECK Q17 CODE 2

How long have you been unemployed/ stop working? [SA] 你没有受雇/停止工作已经多久了？[SA]

Code (327)

Route

Less than 6 months 不到6个月

1

6 months to 1 year 6个月到1年内

2

1 - 3 years 1 – 3 年

3

4 - 6 years 4 – 6 年

4

7 - 9 years 7 – 9 年

5

10 - 15 years 10 – 15 年

6

More than 15years 超过15 年

7

194

Q39 ASK ALL SHOWCARD FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: Looking at this showcard, can you please tell me how did you get hired for your last job? FOR THOSE WHO ARE CURRENTLY EMPLOYED: Looking at this showcard, can you please tell me how did you get hired for your current job? [SA] FOR THOSE WHO ARE CURRENTLY UNEMPLOYED: 请看这张卡，请问你最近那份工作是如何找到的？ FOR THOSE WHO ARE CURRENTLY EMPLOYED: 请看这张卡，请问你目前这份工作是如何找到的？ [SA]

Code (328)

Route

I was HIRED from outside the organization 01

I was TRANSFERRED from another division within the organization 02

I was PROMOTED from another position within the same division 03

I started MY OWN BUSINESS 04 Q50

Never worked before 05 Q61

Others (pls. specify) ____________________ 06

Family business 07

Serve National Service 08

Bonded 09 Can’t remember 19 Refused 20

Q40 ASK ALL WHO HAVE WORKED BEFORE- CHECK Q39 CODE 1-3, 6-9, 19-20

How did you come to know about this job? 你是从哪里知道有这份工作的？[MA] If respondent has few positions with the same company, ask his or her 'first' position with the company[MA]

Code (331)

Route

I saw an ADVERTISEMENT in a newspaper (magazine, trade, technical journal etc.) 01 Q42

I found out through an EMPLOYMENT AGENCY (or personnel consultant, head-hunter etc.) 02 Q42

I SUBMITTED AN APPLICATION before anyone told me about the job 03 Q42

Someone I didn't know contacted me and said that I had been RECOMMENDED 04 Q42

I asked a FRIEND/ PERSON who told me about the job 05 Q41

A FRIEND/ PERSON who knew I was looking for a job contacted me 06 Q41

A FRIEND/ PERSON who didn't know I was looking for a job contacted me 07 Q41

Others (pls. specify) ____________________ 08 Q42

Family business 09 Q41

Signed on after National Service 10 Q44

Bonded 11 Q44

Not sure/ Can't say/ Can't remember 19 Q42

Refused 20 Q42

195

Q41 ASK ALL WHO FIRST CAME TO KNOW ABOUT THE JOB VIA A FRIEND/ PERSON - CHECK Q40 CODES 5 – 7 & 9 You mentioned that you came to know about this job through a friend/ person. Can you please tell me what is the name or initials of this friend/ person? INSTRUCTION TO INTERVIEWER: Please record the name or initials of this friend/ person 你说你是通过一个朋友/人知道这份工作的。可不可以告诉我这个朋友/人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 6: (333-334)

Q42 ASK ALL WHO HAVE WORKED BEFORE - CHECK Q39 CODE 1-3, 6-7, 19-20

Was there someone IN THE COMPANY WHO HELPED YOU get this job? [SA] 是不是这间公司里有人帮助你获得这份工作？ [SA]

Code (335)

Route

Yes 1 Q43

No 2 Q44

Q43 ASK ALL WHO MENTIONED THERE WAS SOMEONE IN THE COMPANY WHO HELPED THEM GET THE JOB -

CHECK Q42 CODE 1 You mentioned that someone in the company helped you get this job. Can you please tell me what is the name or initials of this person? INSTRUCTION TO INTERVIEWER: Please record the name or initials of this person. 你说是公司里有人帮助你获得这份工作。可不可以告诉我这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 7:

________________________________________________________________________________ ________________________________________________________________________________

(336-337) Q44 ASK ALL WHO ARE CURRENTLY EMPLOYED CHECK Q17 CODE 6-10

And for how long have you been in the company? 那么你在这间公司有多久了？

(R1) RECORD NO. OF YEARS RESPONDENT HAS BEEN IN COMPANY: (338-339)

Q45 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10

Of your colleagues at work, has there been anybody who has been QUITE DIFFICULT TO GET ALONG WITH?[SA] 你工作的同事当中，有没有任何人是相当难相处的？[SA]

Code (345)

Route

Yes 1 Q46

No 2 Q49

196

Q46 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG WITH - CHECK Q45 CODE 1 How is he/ she related to you? Is he/ she your...[READ LIST]? [SA] 他跟你是什么关系？他是不是你的...[READ LIST]?[SA]

Code (346)

Route

Boss/ Manager/ Supervisor

老板/经理/上司

1

Co-worker 同阶层的同事

2

Subordinate 下属

3

Just someone else at work 只是工作上的某一个人

4

Q47 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG WITH - CHECK Q45

CODE 1 How long has this person been in the company? INSTRUCTION TO INTERVIEWER: If the respondent says 'Don't know/ Not sure/ Can't say/ Can't remember', please record '99' in the space provided below. 这个人在这间公司有多久了？

(R1) RECORD NO. OF YEARS PERSON HAS BEEN IN COMPANY: (347-348)

Q48 ASK ALL WHO HAS A COLLEAGUE WHO HAS BEEN QUITE DIFFICULT TO GET ALONG

WITH - CHECK Q45 CODE 1 Between this person and you, who would you say is more knowledgeable in your area of work? [SA] 你觉得在你的工作方面，你和这个人之间谁懂得比较多？ [SA]

Code (354)

Route

Me 1

Him/ Her 2

Same 3

Don’t know 4

Q49 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10 In your opinion, how easy would it be for you to find a job with another employer that provides approximately the same income and fringe benefits as what you have now? Would you say it is...[READ LIST]? [SA] 在你看来，你如果要找跟你现在大概一样薪金和福利的另一份工作，

这有多容易？你会说这是...[READ LIST]?[SA]

Code (355)

Route

Not easy at all 根本不容易

1

Not easy 不容易

2

Somewhat easy 算是容易

3

Very easy 非常容易

4

197

SECTION D: WORKPLACE CENSUS INSTRUCTION TO INTERVIEWER: Please read out the following text: Now, I am going to collect some information about the people whom you work with. 现在，我想知道跟你一起工作的人的资料。

Q50 ASK ALL WHO ARE CURRENTLY EMPLOYED - CHECK Q17 CODES 6 - 10

Do you WORK DIRECTLY with anyone?[SA] 你的工作是否跟任何人有直接的接触？ [SA]

Code (356)

Route

Yes 1 Q51

No 2 Q61

Q51 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1

Do you SUPERVISE the work of others or tell other employees what work they should do?[SA] 你是否监督其他人的工作或指示其他雇员他们应该做些什么？ [SA]

Code (357)

Route

Yes 1

No 2

Q52 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1

How many people are there in your WORK GROUP (DEPARTMENT) in total? 你的工作组(部门)总共有几个人？

(R1) RECORD NO. OF PEOPLE IN WORK GROUP/ DEPARTMENT: (358-360)

Q53 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1

How many CO-WORKERS do you need to deal with on a DAILY BASIS ON AVERAGE? 你在工作上每天通常需要跟几个同事一起做事？

(R1) RECORD NO. OF CO-WORKERS DEAL WITH ON DAILY BASIS: (366-368)

198

Q54 ASK ALL WHO WORK DIRECTLY WITH SOMEONE - CHECK Q50 CODE 1 Can you please tell me how many of these co-workers of yours do you deal with on a daily basis on average, fit the profile of being a ...[READ LIST]? INSTRUCTION TO INTERVIEWER: Please read the following options: 1. Singapore Chinese. 2. Singapore Malay. 3. Singapore Indian. 4. Chinese National. 5. Indian National. 6. Members of other ethnicity/ nationality. R1 to R6 should add up to Q53 请告诉我你在日常工作接触的同事当中有几位是...[READ LIST]? INSTRUCTION TO INTERVIEWER: Please read the following options: 1. 新加坡的华人

2. 新加坡的马来人

3. 新加坡的印度人

4. 中国国籍的人

5. 印度国籍的人

6. 其他种族/国籍的人

(R1) RECORD NO. OF SINGAPORE CHINESE: (374-376)

(R2) RECORD NO. OF SINGAPORE MALAYS: (377-379)

(R3) RECORD NO. OF SINGAPORE INDIANS: (380-414)

(R4) RECORD NO. OF CHINESE NATIONALS: (415-417)

(R5) RECORD NO. OF INDIAN NATIONALS: (418-420)

(R6) RECORD NO. OF PEOPLE OF OTHER ETHNICITY/ NATIONALITY: (421-423)

Q55 ASK ALL WHO GAVE A RESPONSE TO R1 IN Q54 Can you please tell me how many of these SINGAPORE CHINESE are Males? And how many of them are Females? R1 + R2 should add up to R1 in Q54 请问这些新加坡华人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (429-431)

(R2) RECORD NO. OF FEMALES: (432-434)

199

Q56 ASK ALL WHO GAVE A RESPONSE TO R2 IN Q54

Can you please tell me how many of these SINGAPORE MALAYS are Males? And how many of them are Females? R1 + R2 should add up to R2 in Q54 请问这些新加坡马来人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (440-442)

(R2) RECORD NO. OF FEMALES: (443-445)

Q57 ASK ALL WHO GAVE A RESPONSE TO R3 IN Q54

Can you please tell me how many of these SINGAPORE INDIANS are Males? And how many of them are Females? R1 + R2 should add up to R3 in Q54 请问这些新加坡印度人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (451-453)

(R2) RECORD NO. OF FEMALES: (454-456)

Q58 ASK ALL WHO GAVE A RESPONSE TO R4 IN Q54

Can you please tell me how many of these CHINESE NATIONALS are Males? And how many of them are Females? R1 + R2 should add up to R4 in Q54 请问这些中国人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (462-464)

(R2) RECORD NO. OF FEMALES: (465-467)

Q59 ASK ALL WHO GAVE A RESPONSE TO R5 IN Q54 Can you please tell me how many of these INDIAN NATIONALS are Males? And how many of them are Females? R1 + R2 should add up to R5 in Q54 请问这些印度人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (473-475)

(R2) RECORD NO. OF FEMALES: (476-478)

Q60 ASK ALL WHO GAVE A RESPONSE TO R6 IN Q54

Can you please tell me how many of these members of other ethnicity/ nationality are Males? And how many of them are Females? R1 + R2 should add up to R6 in Q54 请问这些其他种族/国籍的人当中，有几位是男性？那么有几位是女性？

(R1) RECORD NO. OF MALES: (516-518)

200

Q60 ASK ALL WHO GAVE A RESPONSE TO R6 IN Q54 Can you please tell me how many of these members of other ethnicity/ nationality are Males? And how many of them are Females? R1 + R2 should add up to R6 in Q54 请问这些其他种族/国籍的人当中，有几位是男性？那么有几位是女性？

(R2) RECORD NO. OF FEMALES: (519-521)

201

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: We have talked about your work place. Now, let's move on and talk about your FAMILY LIFE.

我们已经谈过了你的工作。现在，我们谈谈你的家庭生活。

Q61a ASK ALL

First of all, I would like to collect some information about your IMMEDIATE AND EXTENDED FAMILY. Can you please tell me how many of each of the following types of relatives do you currently have? By that, I mean those relatives whom are alive. (INTERVIEWERS: PLEASE READ TYPES OF RELATIVES. FOR AUNTS/UNCLES/COUSINS DO NOT NEED TO ASK FOR TOTAL NUMBER. AUNT/UNCLES ARE DEFINED AS 'SIBILINGS OF PARENTS)

首先，我想知道你的直属家人和远亲的资料。可不可以告诉我你目前有几位以下的各种亲戚？我指的是，还在世的那些亲戚。

Q61b And can you please tell me if any of your ____________________ [READ TYPE OF RELATIVES RESPONDENT GAVE A RESPONSE FOR IN Q61a] LIVE IN THE SAME HOUSE as you? [SA]

那么，请问你的任何___________ [READ TYPE OF RELATIVE RESPONDENT GAVE A

RESPONSE FOR IN Q61a] 有没有跟你住在一起？ [SA]

Q61c Do any of them LIVE IN THE SAME NEIGHBOURHOOD (i.e. within a 10-minute walk)?[SA]

他们有没有任何人住在同一个邻里区呢(就是走路10分钟内可以到)？ [SA]

Q61d Do any of them LIVE OUTSIDE SINGAPORE? [SA] 他们有没有任何人是住在国外的？[SA]

Q61a Q61b Q61c Q61d

Record no. of relatives

Yes No Yes No Yes No

(527-528) (547) (557) (567)

(R1) RECORD NO. OF PARENTS: _ _ 1 2 1 2 1 2

(529-530) (548) (558) (568)

(R2) RECORD NO. OF BROTHERS: _ _ 1 2 1 2 1 2

(531-532) (549) (559) (569)

(R3) RECORD NO. OF SISTERS: _ _ 1 2 1 2 1 2

(533-534) (550) (560) (570)

(R4) RECORD NO. OF SONS: _ _ 1 2 1 2 1 2 (535-536) (551) (561) (571)

(R5) RECORD NO. OF DAUGHTERS: _ _ 1 2 1 2 1 2

(537-538) (552) (562) (572)

(R6) RECORD NO. OF GRANDPARENTS: _ _ 1 2 1 2 1 2

(539-540) (553) (563) (573)

(R7) RECORD NO. OF PARENTS-IN-LAW: _ _ 1 2 1 2 1 2

(554) (564) (574)

(R8) RECORD NO. OF AUNTS: 1 2 1 2 1 2

(555) (565) (575)

(R9) RECORD NO. OF UNCLES: 1 2 1 2 1 2

(556) (566) (576)

(R10) RECORD NO. OF COUSINS: 1 2 1 2 1 2

202

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: The following questions are with regards to the things pertaining to FAMILY MAINTENANCE and YOUR CHILDREN (IF ANY). 接下来的问题是有关维持家庭和有关你的孩子。 Q62 ASK ALL

Does your household employ a maid? INSTRUCTION TO INTERVIEWER: If the respondent is MARRIED and selects Code 2 here, please proceed to Q64. If the respondent is SINGLE/ ENGAGED/ SEPARATED/ DIVORCED/ WIDOWED/ REFUSED and selects Code 2 here, please proceed to Q65 .[SA] 你的家有没有聘请女佣？ [SA]

Code (614)

Route

Yes 1 Q63

No 2 Q64

Q63 ASK ALL WHOSE HOUSEHOLD EMPLOYS A MAID - CHECK Q62 CODE 1

Generally speaking, how much housework does the maid in your household do? [SA]

一般来说，你家的女佣需要做多少工作？ [SA]

Code (615)

Route

All of it 01

Most of it, someone in the household helps along with some tasks (e.g. cooking etc.) 02

Just some of it, someone in the household does the bulk of it 03

Others (pls. specify) ____________________ 04

Don't know/ Not sure/ Can't say 20

Q64 ASK ALL WHO ARE MARRIED - CHECK Q5 CODE 4 Does your spouse work?[SA] 你的妻子/丈夫有没有工作？[SA]

Code (617)

Route

Yes 1

No 2

203

Q65 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CODE 1

Other than your spouse or you, who else takes care of your child/ children? For example, when both your spouse and you work? [SA] 除了你的配偶和你之外，还有谁照顾你的孩子？例如，当你和妻子/丈夫都在工作的时候？ [SA]

Code (618)

Route

Nobody, our child/ the children are old enough to take care of themselves 01

We take them with us to work 02

Another relative who lives in the same house 03

Another relative who lives in a different house 04

The maid 05

A neighbour 06

A childcare organization 07

A tuition centre/ school 08

This situation does not apply to me/ has not happened to me yet 09

Others (pls. specify) ____________________ 10

Don't know/ Not sure/ Can't say 30

Q66 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CODE 1

What about when your spouse and you have to leave the house for a few hours (e.g. shopping etc.)?[SA]

那么，当你和妻子/丈夫需要离开家里几个小时的的时候呢(例如去购物)？[SA]

Code (621)

Route

Nobody, our child/ the children are old enough to take care of themselves 01

We take them along with us 02

Another relative who lives in the same house 03

Another relative who lives in a different house 04

The maid 05

A neighbour 06

A childcare organization 07

A tuition centre/ school 08

This situation does not apply/ has not happened to me yet 09

Others (pls. specify) ____________________ 10

Don't know/ Not sure/ Can't say 30

Q67 ASK ALL WHO HAVE CHILD/ CHILDREN - CHECK Q6 CODE 1

Other than your spouse and you, who is your main childcare giver? INSTRUCTION TO INTERVIEWER: Please ensure that the response that appears here, appears in either Q65 or Q66.

除了你的配偶和你之外，谁是主要看顾你的孩子？

(R1) RECORD NAME/INITIALS OF PERSON 8

________________________________________________________________________________ ________________________________________________________________________________ (624-625)

204

Q68 ASK ALL

Have you ever provided child care for someone else? [SA] 你是否曾经给别人看顾孩子？ [SA]

Code (642)

Route

Yes 1 Q69

No 2 Q70

Q69 ASK ALL WHO PROVIDE CHILD CARE FOR SOMEONE ELSE - CHECK Q68 CODE 1 When was the last time you provided such child care? [SA] 你最近一次给别人看顾孩子是什么时候？ [SA]

Code (643)

Route

Within the last two days 1

Within the last week 2

Within the last month 3

Within the last six months 4

Longer ago than that 5

Q70 ASK ALL

When people go out of Singapore for a while, they sometimes ask someone to TAKE CARE OF THEIR HOUSE for them, for example, to water the plants, pick up the mail, feed a pet, bring in the newspapers or simply just to check on things. If you and your family went out of Singapore for a while, such that the whole house is empty, would you ask someone to take care of your house for you in any of the above-mentioned ways while you are away? [SA] 有些人出国的时候，他们会叫别人帮忙照顾他们的家，例如浇花、收信件、喂宠物、收报纸或者只

是检查家里有没有问题。 如果你和全家人出国一阵子，整个家里没有人的话，你会不会请别人在你不在家的时候帮你照顾你

的家呢？例如以上那些方式。 [SA]

Code (644)

Route

Yes 1 Q71

No 2 Q72

Q71 ASK ALL WHO MENTIONED THEY WILL GET SOMEONE TO LOOK AFTER THEIR HOUSE - CHECK Q70 CODE

1 Can you give me the name or initials of the person whom you will ask or have asked to look after your house? Kindly note that the person that you name, must not be anyone who is currently living in the same house as you.

请问你会找谁照顾你的家，可不可以告诉我他的名字或简称？不过，你提到的这个人不应该是目前跟你住在同一个屋子

的人。

(R1) RECORD NAME/ INITIALS OF PERSON 9:

________________________________________________________________________________ ________________________________________________________________________________ (645-646)

205

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: So far, we have talked about your general life situation, your work place and your family. Now, let us talk about about some informal aspects of socializing, including what you enjoy doing during your free time and with whom you spend your free time etc. 我们已经谈过了你一般的生活状况、你的工作和你的家庭。现在，我们来谈谈你较随兴的社交生活，包括了你喜欢在休闲时间做

些什么及你和谁度过你的消闲时间。

Q72 ASK ALL

Sometimes, people get together with others to DISCUSS ABOUT HOBBIES OR SPARE-TIME INTERESTS THEY HAVE IN COMMON. Do you ever do this with anyone? [SA] 有的时候，人家喜欢聚在一起谈他们共同的嗜好或休闲的兴趣。你有没有跟别人一起这样做呢？ [SA]

Code (647)

Route

Yes, discuss with someone 1 Q73

No, never discuss with anyone 2 Q74

I do not have any hobbies or spare-time interests 3 Q74

Q73 ASK ALL WHO GET TOGETHER WITH OTHERS - CHECK Q72 CODE 1

Can you please tell me the name or initials of the person whom you get together with to discuss about hobbies or spare-time interests? 请问你会跟谁在一起谈嗜好或休闲的兴趣呢？可不可以告诉我他的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 10:

________________________________________________________________________________ ________________________________________________________________________________ (648-649)

206

Q74 ASK ALL

Thinking of the past six months, who were the two or three people with whom you spent the most time DOING SOCIAL ACTIVITIES with? Such as going out for drinks, watching a movie, window shopping, going for meals, playing mahjong, drinking with a group of friends, meeting friends at coffee shop for a chat, family 'get together' etc. Can you please give me the names or initials of two persons? 在过去6个月内，你最常跟哪两三个人一起进行社交活动呢？例如出去喝饮料、看电影、逛街、去吃饭、打麻将、跟一

群朋友喝东西、在咖啡店跟朋友见面聊天、家人相聚等。可不可以告诉我两个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 11:

________________________________________________________________________________ ________________________________________________________________________________ (650-651)

(R2) RECORD NAME/ INITIALS OF PERSON 12: ________________________________________________________________________________ ________________________________________________________________________________ (652-653)

Q75 ASK ALL

When was the last time you socialized with someone outside your family? [SA] 你最近一次和家人以外的人一起进行社交活动是在什么时候？ [SA]

Code (654)

Route

Within the last two days 1

Within the last week 2

Within the last month 3

Within the last six months 4

Longer ago than that 5

207

INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: Now, let's move on to talk about the more formal aspects of socializing. What follows is a set of questions about: 1. Your national service experience [READ ONLY TO ALL MALE RESPONDENTS]. 2. Your participation in various kinds of voluntary organizations. 现在，让我们来谈谈比较正式的社交活动。接下来的问题是有关：

1。你服役的经验 [READ ONLY TO ALL MALE RESPONDENTS].

2。 你参与各类自愿团体的经验。

SECTION E: NATIONAL SERVICE ASK ALL MALE RESPONDENTS

Q76 ASK ALL MALE RESPONDENTS Did you perform any National Service duties? [SA] 你有没有履行国民服役？[SA]

Code (655)

Route

Yes 1 Q77

No 2 Q82

Q77 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1

Do you presently have an assigned reservist unit?[SA] 你目前是否属于哪个战备军人单位？ [SA]

Code (656)

Route

Yes 1

Yes, but I have yet to go for my first ICT 2

No 3

I finished my reservist duties already 4

Q78 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1

Do you still keep in touch with any of your army friends?[SA]

你还有没有跟你军中的朋友保持联络？[SA]

Code (657)

Route

Yes 1 Q79

No 2 Q80

208

Q79 ASK ALL WHO KEEP IN TOUCH WITH HIS ARMY FRIENDS - CHECK Q78 CODE 1

Can you please give me the name or initials of one of the army friends whom you still keep in touch with? INSTRUCTION TO INTERVIEWER: Please record the name or initials of this army friend. Skip to Q81 请问你跟哪些军中的朋友保持联络，可不可以告诉我其中一人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 13:

________________________________________________________________________________ (658-659)

Q80 ASK ALL WHO PERFORMED NATIONAL SERVICE DUTIES - CHECK Q76 CODE 1 OR ALL WHO HAVE AN

ASSIGNED RESERVIST UNIT OR FINISHED HIS RESERVIST - CHECK Q77 CODES 1 OR 4 When we go back for In-Camp Training (ICT), we often re-unite with our fellow unit personnel. We are more familiar with some of our camp-mates and less with others. For those whom we are more familiar with, we often stick together throughout the in-camp training period (e.g. go for breaks together etc). FOR THOSE WHO HAVE AN ASSIGNED RESERVIST UNIT, ASK Can you please tell me who is your CLOSEST CAMP MATE? Can you please provide me with a name or initial of this person? FOR THOSE WHO HAVE FINISHED HIS RESERVIST DUTIES, ASK Can you please tell me who was your CLOSEST CAMP MATE? Can you please provide me with a name or initial of this person? INSTRUCTION TO INTERVIEWER: Please record the name or initials of this person. 当我们回营受训(ICT)的时候，我们通常被安排跟同一组人在一起。在同一个营的同伴当中，我们会跟一些人比较熟。

在受训期间，我们通常会跟那些较熟的人聚在一起(例如一起去小休等) FOR THOSE WHO HAVE AN ASSIGNED RESERVIST UNIT, ASK 请问谁是你军营中最亲密的同伴呢？可不可以告诉我这个人的名字或简称？ FOR THOSE WHO HAVE FINISHED HIS RESERVIST DUTIES, ASK

请问谁是你以前在军营中最亲密的同伴呢？可不可以告诉我这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 13:

________________________________________________________________________________ (660-661)

Q81 ASK ALL WHO GAVE A NAME/ INITIAL IN Q79 or Q80 Thinking of your closest camp-mates, do you ever do things together outside of your ICT? For example, meeting up for a meal, engage in games, train for the IPPT, chit-chat etc.[SA] 想想你最亲密的军营同伴，你们除了回营受训之外，有没有在一起做其它的事呢？例如，相约吃饭

、一起玩游戏、一起锻炼身体以应付体能测验（IPPT）、聊天等。 [SA]

Code (662)

Route

Yes 1 No 2

209

Q82 ASK ALL

Do you currently PLAY ANY FORM OF SPORTS or EXERCISE ON A REGULAR BASIS, meaning at least once a fortnight? [SA] 你目前有没有进行任何体育活动或者运动，就是说至少每两个星期一次？ [SA]

Code (663)

Route

Yes 1 Q83

No 2 Q84

Q83 ASK ALL WHO PLAY SPORTS OR EXERCISE REGULARLY - CHECK Q82 CODE 1

Can you please tell me the name or initials of your MOST REGULAR SPORTS OR EXERCISE PARTNER? INSTRUCTION TO INTERVIEWER: Please record the name/ initials of this person.

请问最常跟你一起进行体育活动或运动的人是谁？可不可以告诉我他的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 14:

________________________________________________________________________________ ________________________________________________________________________________ (664-665)

210

SECTION F: VOLUNTARY ORGANIZATIONS Q84 ASK ALL

SHOWCARD Over the past six months, have you ATTENDED A GET-TOGETHER OR MEETING in any of these types of organizations? [MA] 在过去6个月内，你有没有参加过以下任何机构的聚会或会议？ [MA]

Code (666)

Route

Religious groups (e.g. cell group in churches, Islamic religious classes, The Soka Association etc.)

01

Charity or welfare organizations (e.g. Singapore Cheshire Home, The Salvation Army, Homes for the Aged etc.)

02

Community centres and clubs 03

Country clubs (e.g. CDANS, Punggol Marina etc.) 04

Sports associations (e.g. SAFRA branches, Marine Castle Football Club, Kallang Sea Sports Club etc.)

05

Private educational institutions (e.g. night courses for private degrees, Yamaha Music Academy, Tertiary institutions etc.)

06

Ethnic, racial or national organizations (e.g. The People's Association, MENDAKI, CDAC etc.) 07

Special interest groups (e.g. issue-oriented and lobby groups like AWARE, Nature Society etc.) 08

Neighbourhood associations (e.g. Citizen Consultative Committee, Residents' Committee, Grassroot Club etc.)

09

Parent-Teacher associations 10

Professional organizations/ groups (e.g. AMP, The Singapore Law Society etc.) 11

Political Party (e.g. PAP, PAP youth) 12

Others (pls. specify) ____________________ 13

Cultural Exchange 14

Not sure/ Cant' say/Can't remember 29

None of the above 30

Q85 ASK ALL WHO GAVE A RESPONSE IN Q84 - SELECTED CODES 1 - 14 IN Q84

From among the people whom you see or meet in these organizations, who have you spoken to most recently? Please give me the names or initials of these people. INSTRUCTION TO INTERVIEWER: Please record the names/ initials of people mentioned. 你在这些机构见到或遇到的人当中，你最近一次跟谁谈过话？请告诉我这些人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 15:

________________________________________________________________________________ ________________________________________________________________________________

(669-670)

(R2) RECORD NAME/ INITIALS OF PERSON 16: ________________________________________________________________________________ ________________________________________________________________________________ (671-672)

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SECTION G: OTHER NAMES/ ETHNIC PROBE INSTRUCTION TO INTERVIEWER: Please compile a list of all the names that were mentioned in all the questions thus far, in the separate sheet of paper.

Q86 ASK ALL

SHOW COMPILED LIST OF NAMES Please take a look at this list. Is there anyone who is important or close to you but whose name does not show up on this list? INSTRUCTION TO INTERVIEWER: If the respondent selects Code 2 here, please evaluate which option in Q88 should be asked. [SA] 请看这里列出的人。有没有任何对你重要或跟你亲近的人的名字没有列在这里？ [SA]

Code (673)

Route

Yes 1 Q87

No 2 Q88

Q87 ASK ALL WHO MENTIONED THAT THE NAME OF SOMEONE IMPORTANT IS MISSING FROM THE LIST - CHECK Q86 CODE 1. ASK RESPONDENTS TO NAME THE MOST IMPORTANT TWO IF THERE ARE MORE THAN TWO. Can you please tell me the name or initials of this person whose name is currently missing from this list? 可不可以告诉我目前这里没有列出的这个人的名字或简称？

(R1) RECORD NAME/ INITIALS OF PERSON 17:

________________________________________________________________________________ ________________________________________________________________________________ (674-675)

(R2) RECORD NAME/ INITIALS OF PERSON 18: ________________________________________________________________________________ ________________________________________________________________________________ (676-677)

INSTRUCTION TO INTERVIEWER: Please record the ethnicity of all the names that were mentioned in all the questions thus far, in the separate sheet of paper and proceed to ask Q88 .

212

Q88 ASK ALL I see that you HAVE NOT NAMED ANY ____________[READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S AND THAT IS MISSING FROM THE LIST - START FROM TICK] persons. Do you know people who are [READ FROM TICK] whom you could include in this list. [READ FROM TICK] people whom you can talk to, laugh, joke or just have a good time? INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean FOR ALL NON-CITIZEN, PLEASE READ OUT ‘SINGAPOREAN’ AS AN ETHNIC GROUP TO THE RESPONDENT OR I see that you HAVE NAMED A FEW _____________ [READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S - START FROM TICK] persons. Do you know people who are [READ FROM TICK} whom you could include in this list. [READ FROM TICK] people whom you can talk to, laugh, joke or just have a good time? INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean PROBE Is there anyone else? Any others?

我看你这里并没有列出任何HAVE NOT NAMED ANY _____________________ [READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S AND THAT IS MISSING FROM THE LIST - START FROM TICK]人。请问你是否认识任何[READ FROM

TICK]人，可以把他的名字放在这里吗？就是，你可以跟他一起谈话、开玩笑或一起玩乐的[READ FROM TICK]人？ INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean FOR ALL NON-CITIZEN, PLEASE READ OUT ‘SINGAPOREAN’ AS AN ETHNIC GROUP TO THE RESPONDENT OR 我看你这里列出了几位HAVE NAMED A FEW _____________________ [READ ETHNIC GROUP THAT IS OPPOSITE OF THE RESPONDENT'S - START FROM TICK] 人。你还认不认识其他人？你还可以告诉我更多的名字或简称吗？请问你是否认识任何[READ FROM

TICK]人，可以把他的名字放在这里吗？就是，你可以跟他一起谈话、开玩笑或一起玩乐的[READ FROM TICK]人？ INSTRUCTION TO INTERVIEWER: Please rotate the ethnic group to be read, starting from tick: ( ) Chinese ( ) Malay ( ) Indian ( ) Non-Singaporean Probe 还有其他人吗？还有其他的吗?

213

(R1) RECORD NAME/ INITIALS OF PERSON 19: ________________________________________________________________________________ ________________________________________________________________________________ (678-679)

(R2) RECORD NAME/ INITIALS OF PERSON 20: ________________________________________________________________________________ ________________________________________________________________________________ (680-713)

Q89 RECORD ETHNIC GROUP READ OUT TO THE RESPONDENTS IN Q88 [SA]

Code (714)

Route

Chinese 1

Malay 2

Indian 3

Non-Singaporean 4

Singaporean 5

Q90 RECORD NO. OF TIMES YOU HAD TO PROBE THE RESPONDENT FOR AN ANSWER IN Q88

(R1) RECORD NO. OF TIMES YOU HAD TO PROBE RESPONDENT: (715-716)

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SECTION H: IDENTITY INSTRUCTION TO INTERVIEWER: Please read the following text to the respondent: In the last half an hour or so, I have asked you several questions about your job, family, social life etc. Now, I am going to ask you some questions pertaining to your SENSE OF IDENTITY. 刚才我们谈过了你的工作、家庭、社交生活等。现在，我要问你一些有关自我认同的问题。

Q91 ASK ALL

DROPCARD I am going to read to you, a list of things that different people value. Some people say these things are very important to them while others say they are not as important. Using a scale of 1 to 5 where '1' represents 'Not at all important' and '5' represents 'Especially important', please tell me how important each of these statements is to you. [SA] 我要念出一些人们重视的东西。有些人觉得这些东西对他们很重要，有些人却觉得不重要。请你用1到5的评分表来告诉

我以下各项对你有多重要。这里1表示完全不重要，而5表示特别重要。[SA]

Not at all

important - 1

Not too important -

2

Quite important -

3

Very important -

4

Especially important -

5 (722)

(R1) Being financially secure 1 2 3 4 5

(723)

(R2) Being married 1 2 3 4 5

(724)

(R3) Having children 1 2 3 4 5

(725)

(R4) Having faith in God 1 2 3 4 5

(726)

(R5) Having nice things 1 2 3 4 5

(727)

(R6) Being cultured 1 2 3 4 5

(728)

(R7) Having a fulfilling job 1 2 3 4 5

(729)

(R8) Being self-sufficient and not having to depend on others

1 2 3 4 5

(730)

(R9) Having friends 1 2 3 4 5

(731)

(R10) Being myself 1 2 3 4 5

(732)

(R11) Being able to speak the language of my ancestors 1 2 3 4 5

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Q92 ASK ALL

DROPCARD Using a scale of 1 to 5 where '1' represents ‘Strongly disagree’ and '5' represents ‘Strongly agree’, can you please tell me to what extent do you agree or disagree with the following statements? [SA] 请用1到5的评分表，告诉我你有多同意或不同意以下的句子？这里1表示非常不同意，而5表示非常同意。 [SA]

Strongly

disagree - 1 Disagree - 2 Neither

agree nor disagree - 3

Agree - 4 Strongly agree - 5

(733)

(R1) I would rather be a citizen of Singapore than a citizen of any other country in the world

1 2 3 4 5

(734)

(R2) There are some things about Singapore today that make me feel ashamed of Singapore

1 2 3 4 5

(735)

(R3) Generally speaking, Singapore is a better country than most other countries

1 2 3 4 5

Q93 ASK ALL

DROPCARD Now, using a scale of 1 to 5 where '1' represents 'Strongly disagree' and '5' represents 'Strongly agree', can you please tell me to what extent do you agree or disagree with the following statements? [SA] 现在，请用1到5的评分表，告诉我你有多同意或不同意以下的句子？这里1表示非常不同意，而5表示非常同意。 [SA]

Strongly

disagree - 1 Disagree - 2 Neither

agree nor disagree - 3

Agree - 4 Strongly agree - 5

(736)

(R1) To a great extent, my life is controlled by accidental happenings - I take things as they come

1 2 3 4 5

(737)

(R2) I feel that what happens in my life is mostly determined by powerful people

1 2 3 4 5

(738)

(R3) In life, I determine what I do 1 2 3 4 5

(739)

(R4) When I need help, I can organize and request for people to help me

1 2 3 4 5

(740)

(R5) In life, I am quite willing to trust people 1 2 3 4 5

216

Q94 ASK ALL

If you have the opportunity, would you migrate overseas? [SA] 如果你有机会，你会不会移民海外？ [SA]

Code (741)

Route

Yes 1

No 2

Maybe 3

Don't know/ Not sure/ Can't say 4

Q95 ASK ALL

SHOWCARD How would you describe the Singapore society today? Please read through the following statements and let me know which one/s you agree with.[MA] 你会怎样形容现在的新加坡社会？请仔细读以下的句子，然后告诉我你同意哪个/哪些。[MA]

Code (742)

Route

Singapore is undergoing enormous transformations 1

The pace of change is fast 2

The next few years will be stressful 3

The next few years will be stressful but exciting 4

I feel the pressure to upgrade my skills to stay relevant 5

We are in for tough times 6

I am looking forward to better days 7

None of the above 8

Q96 ASK ALL

In comparison to five years ago, would you say that life today is better, worse or the same for you? [SA]

跟5年前相比，你会说你现在的生活比较好、较差，还是一样？[SA]

Code (743)

Route

Better 1

Same 2

Worse 3

Don't know/ Not sure/ Can't say 4

INSTRUCTION TO INTERVIEWERS: Please proceed to record the personal particulars of the respondent's network members in the separate sheet of paper. CLOSE INTERVIEW - THANK RESPONDENT

217

INTERVIEWERS: PLEASE REMEMBER TO COMPLETE QUESTIONS ON SECTION I ( INTERVIEW CONDITIONS) BELOW. SECTION I: INTERVIEW CONDITIONS TO BE ANSWERED BY THE INTERVIEWER. Q97 ALL INTERVIEWERS

Where was the interview carried out? [SA]

Code (744)

Route

Immediately outside the person's home (at the doorway) 1

In the person's home 2

At another place other than the person's home 3

Q98 ALL INTERVIEWERS

Was anyone else present during the interview? 'Present' means in the same room.[SA]

Code (745)

Route

Yes, for most of the interview 1

Yes, for some of the interview 2

Yes, but only for a minute or two 3

No, not at any time 4

Q99 INTERVIEWERS ANSWER THIS QUESTION IF CODE 1 & 2 SELECTED IN Q98

Who else was present?[MA]

Code (746)

Route

Spouse 1

Other adult household member (18 or over - roughly by observation) 2

Teenager (13 - 18) 3

Child or infant (under 13) 4

Friends, visitor 5

Others (Please specify:_______________) 6

Q100 ALL INTERVIEWERS

Did the respondent have difficulty understanding the questions?[SA]

Code (747)

Route

Yes, great difficulty 1

Yes, some difficulty 2

No, none at all 3

Q101 ALL INTERVIEWERS

What was the respondent's attitude during the interview?[SA]

Code (748)

Route

Friendly, eager, volunteered information 1

Cooperative, but not particularly enthusiastic 2

Indifferent or bored 3

Often irritated or hostile - seemed anxious to get it over with 4

Hard to tell 5

218

Q102 ALL INTERVIEWERS

How would you describe the respondent's mood during the interview? [SA]

Code (749)

Route

Elated 1

Happy 2

Neutral 3

Sad 4

Depressed 5

Declaration by Survey Officer I hereby certify that this interview carried out and recorded by me today, is true and accurate, and in accordance with the survey methodology, specified instructions, and the ESOMAR Code of Practice. ______________________________ Signature of Survey Officer

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