FACTORS AFFECTING WOMEN REPRESENTATION IN PUBLIC

PARTICIPATION ON DECISION-MAKING: A CASE STUDY OF

THARAKA NITHI COUNTY IN KENYA

BY

KIMANI RACHEL WANJIRU

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

FALL 2019

FACTORS AFFECTING WOMEN REPRESENTATION IN PUBLIC

PARTICIPATION ON DECISION-MAKING: A CASE STUDY OF

THARAKA NITHI COUNTY IN KENYA

BY

KIMANI RACHEL WANJIRU

A Research Project Report Submitted to the Chandaria School of

Business in Partial Fulfillment of the Requirement for the Degree of

Masters in Business Administration (MBA)

UNITED STATES INTERNATIONAL UNIVERSITY – AFRICA

FALL 2019

ii

STUDENT’S DECLARATION

I, the undersigned, declare that this is my original work and has not been submitted to any

other college, institution or university other than the United States International University

in Nairobi for academic credit.

Signed: ____________________________Date: _____________________________

Rachel Kimani (Student ID 622552)

This research project report has been presented for examination with my approval as the

appointed supervisor.

Signed: ____________________________Date: ______________________________

Timothy C. Okech, PhD

Signed: ____________________________Date: ______________________________

Dean, Chandaria School of Business

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DEDICATION

I dedicate this work to Hannah & Herman Kimani, Kiarie, Tony, Lilian, Mwenda, friends

and lecturers, especially Prof. Okech. To all thank you for your invaluable support.

iv

TABLE OF CONTENTS

STUDENT’S DECLARATION ........................................................................................ ii

DEDICATION................................................................................................................... iii

LIST OF TABLES ........................................................................................................... vii

LIST OF FIGURES ........................................................................................................ viii

ABBREVIATIONS AND ACRONYMS ......................................................................... ix

ABSTRACT ...................................................................................................................... xii

CHAPTER ONE ................................................................................................................ 1

1.0 INTRODUCTION........................................................................................................ 1

1.1 Background of the Study ............................................................................................ 1

1.2 Statement of the Problem ........................................................................................... 3

1.3 Purpose of the Study .................................................................................................. 4

1.4 Research Questions .................................................................................................... 4

1.5 Importance of the Study ............................................................................................. 5

1.5.2 Scholars ................................................................................................................... 5

1.5.4 Civic Educators ....................................................................................................... 5

1.6 Scope of the Study...................................................................................................... 5

1.7 Definition of Terms .................................................................................................... 6

1.8 Chapter Summary ....................................................................................................... 6

CHAPTER TWO ............................................................................................................... 7

2.0 LITERATURE REVIEW ........................................................................................... 7

2.1 Introduction ................................................................................................................ 7

2.2 Effect of Socioeconomic Factors on Women Decision – Making at Public

Hearings ........................................................................................................................... 7

2.3 Effect of Economic Empowerment on Decision Making at Public Hearings .......... 11

2.4 Influence of Inclusion on Women Decision Making at Public Hearings ................. 15

2.5 Chapter Summary ..................................................................................................... 19

CHAPTER THREE ......................................................................................................... 20

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3.0 RESEARCH METHDOLOGY ................................................................................ 20

3.1 Introduction .............................................................................................................. 20

3.2 Research Design ....................................................................................................... 20

3.3. Population and Sampling Design ............................................................................ 21

3.4 Data Collection Methods .......................................................................................... 24

3.5 Research Procedures ................................................................................................ 24

3.6 Data Analysis Methods ............................................................................................ 25

3.7 Chapter Summary ..................................................................................................... 25

CHAPTER FOUR ............................................................................................................ 26

4.0 RESULTS AND FINDINGS ..................................................................................... 26

4.1 Introduction .............................................................................................................. 26

4.2 Response Rate and Background ............................................................................... 26

4.3 Effect of Socioeconomic Factors on Decision-Making in Women at Public

Participation Hearings .................................................................................................... 30

4.4 Effect of Women Economic Empowerment on Public Participation ....................... 34

4.5 Effect of Inclusivity in Public Participation Hearings on Decision-Making ........... 38

4.7 Chapter Summary ..................................................................................................... 41

CHAPTER FIVE ............................................................................................................. 42

5.0 DISCUSSION, CONCLUSION AND RECOMMENDATION ............................. 42

5.1 Introduction .............................................................................................................. 42

5.2 Summary .................................................................................................................. 42

5.3 Discussion ................................................................................................................ 44

5.4 Conclusion ................................................................................................................ 51

5.5 Recommendation ...................................................................................................... 51

REFERENCE ................................................................................................................... 53

APPENDICES .................................................................................................................. 62

Appendix I: Introductory letter ...................................................................................... 62

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Appendix II: Questionnaire ............................................................................................ 63

Appendix III: Research Permit ....................................................................................... 68

Appendix IV: Attendees ................................................................................................. 69

Appendix V: 2018-19 Budget Calendar ......................................................................... 73

Appendix VI: Map of Tharaka Nithi County ................................................................. 79

Appendix VII: Population Projections as per the wards ................................................ 80

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LIST OF TABLES

Table 3.1: Population Distribution and Density by Constituency/Sub County ................. 21

Table 3.2: Overall Employment by Education Levels in Tharaka Nithi County............... 22

Table 3.3: Sample Distribution .......................................................................................... 23 Table 4.1: Healthcare Access ............................................................................................. 29

Table 4.2: Socioeconomic Factors ..................................................................................... 32

Table 4.3: Correlation Between Socioeconomic Factors and Decision-Making ............... 33

Table 4.4: Regression on Socioeconomic Factors and Decision-Making ......................... 33

Table 4.5: ANOVA on Socioeconomic Factors and Decision-Making ............................. 34

Table 4.6: Coefficient on Socioeconomic Factors and Decision-Making ......................... 34

Table 4.7: Women Economic Empowerment .................................................................... 36

Table 4.8: Correlation between Women Economic Empowerment and Decision-Making

............................................................................................................................................ 36

Table 4.9: Regression on Women Economic Empowerment and Decision-Making ........ 37

Table 4.10: ANOVA on Women Economic Empowerment and Decision-Making .......... 37

Table 4.11: Coefficient on Women Economic Empowerment and Decision-Making ...... 38

Table 4.12: Inclusivity in Public Participation Hearings ................................................... 39

Table 4.13: Correlation between Inclusivity in Public Participation Hearings and Decision-

making................................................................................................................................ 39

Table 4.14: Model Summary on Inclusivity in Public Participation Hearings and Decision

............................................................................................................................................ 40

Table 4.15: ANOVA on Inclusivity in Public Participation Hearings and Decision......... 40

Table 4.16: Coefficients on Inclusivity in Public Participation Hearings and Decision ... 41

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LIST OF FIGURES

Figure 4.1: Respondents’ Gender ...................................................................................... 27

Figure 4.2: Academic Qualification ................................................................................... 27

Figure 4.3: Employment Status ......................................................................................... 28

Figure 4.4: Public Participation Knowledge ...................................................................... 28

Figure 4.5: Involvement in Public Participation ................................................................ 29

Figure 4.6: Community/Political Group Membership ....................................................... 30

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ABBREVIATIONS AND ACRONYMS

ASDSP Agricultural Sector Development Support Programme

BPO Business Process Outsourcing

CADP Annual Development Plan

CAMER County Annual Monitoring and Evaluation Report

CBO Community Based Organization

CEC County Executive Committee

CFA Community Forest Association

CFSP County Fiscal Strategy Paper

CIDP County Integrated Development Plan

CIMES County Integrated Monitoring and Evaluation

CO Chief Officer

COG Council of Governors

CPSB County Public Service Board

CRA Commission on Revenue Allocation

DRM Disaster Risk Management

ECDE Early Childhood Development Education

EDE Ending Drought Emergencies

FBO Faith Based Organization

GDP Gross Domestic Product

GIS Geographic Information System

GIZ German Society for International Cooperation

HDI Human Development Index

HIV/AIDS Human Immunodeficiency Virus/Acquired Immune Deficiency Syndrome

HR Human Resource

x

HSC Health Sciences Center

ICT Information and Communication Technology

IFMIS Integrated Financial Management Information Systems

IGAs Income Generating Activities

KFS Kenya Forest Service

KNBS Kenya National Bureau of Statistics

Ksh. Kenya Shilling

KWS Kenya Wildlife Service

M&E Monitoring and Evaluation

MDGs Millennium Development Goals

MIS Management Information System

MoDP Ministry of Devolution and Planning

MP Member of Parliament

MSMEs Micro, Small, and Medium Enterprises

MTEF Medium Term Expenditure Framework

MTP Medium Term Plan

NDMA National Drought Management Authority

NEMA National Environmental Management Authority

NG-CDF National Government - Constituency Development Fund

NGO Non-Governmental Organization

NIMES National Integrated Monitoring and Evaluation System

OVC Orphans and Vulnerable Children

PBO Public Benefits Organization

PDHPE Personal Development, Health and Physical Education

PEM Public Expenditure Management

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PFMA Public Financial Management Act

PMC Project Management Committee

PPIs Programmes, Projects Initiatives

PPP Public Private Partnership

PSH Public Sector Hearings

PWD Persons with Disability

SACCOS Savings and Credit Cooperative Society

SCM Supply Chain Management

SDGs Sustainable Development Goals

SIR Social Intelligence Report

SWGs Sector Working Groups

TIVET Technical and Vocational Education and Training

TNCG Tharaka Nithi County Government

TTI Technical Training Institute

TWGs Technical Working Groups

UN United Nations

UNDP United Nations Development Programme

USAID United States Agency for International Development

UTaNRMP Upper Tana Natural Resources Management Project

WRMA Water Resource Management Authority

WRUA Water Resource Users Association

xii

ABSTRACT

The purpose of the study was to examine the effect of women representation in public

participation on decision-making. The study was constructed on three research questions

which include, what is the effect of women socioeconomic factors on decision – making at

public hearings? what is the effect of women economic empowerment on decision – making

at public hearings? How does women inclusion influence decision – making at public

hearings? This study used a mixed method research design including, action research and

exploratory design. The study population included women and men from Tharaka Nithi

County. This study used purposive sampling and random sampling technique to obtain

participants for the study. A total of 400 respondents were selected to participate in the

study. Questionnaire were used to collect data that was analyzed through descriptive and

inferential statistics.

Findings on the first research question showed that there was a significant positive

correlation between decision making in women in public participation and socioeconomic

factors, r=0.213, p<.001. The regression analysis showed that socioeconomic factors,

predicted 4.5% of decision making of women in public participation. Findings on the

second research question showed that there was a significant positive correlation between

decision making and women economic empowerment, r=.146, p<0.024. The regression

analysis showed that women economic empowerment, predicted 2.1% of decision making

of women in public participation. Findings on the third research question showed that there

was a significant positive correlation between decision making and women inclusivity,

r=.396, p<.000. Regression analysis showed that women inclusivity in public participation

hearing, predicted 15.7% of decision making.

This study concludes that socioeconomic factors, influence women participation in public

decision making. This study concludes that women economic empowerment significantly

contributes to women decision making in public participation. This study concludes that

women inclusivity significantly affected thier decision making in public participation. This

study proposes that the socioeconomic factors that affect women such as housing,

education, health and employment be given priority in local government. This will enable

women to come out into the public and be involved in public issues some of which affect

them directly. This study recommends that the new county government should uplift the

economic conditions of women at the grassroot. They should support women in their

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economic ventures that would empower them and drive them into public participation. This

study proposes for stronger policies in the government to include more women in public

activities. Women should be supported with policies that guarantees thier participation in

the public.

1

CHAPTER ONE

1.0 INTRODUCTION

1.1 Background of the Study

Public participation is defined as a revered continuum of interaction between citizens and

their governments, with activities ranging from listening and informing to implementing

solution agreed upon and these interactions occur at three main levels: information access,

consultation, and active dialogue and partnership. Governments should never apply

measures that prevent the public from acquiring information. Further, it should properly

define issues that affect the broader public and foster situations where the public is in line

with the common goals of the entire process (European Urban Knowledge Network, 2019).

Public participation is also defined an activity or series of activities that people undertake

to involve themselves in affairs of government or their communities, according to Uraia

Trust (2016). Examples of activities cited by Uraia include voting, attending meetings,

participating in political discussion in private or public settings, debating on issues,

endorsing petitions regarding policy, volunteering in community activities, fundraising and

lobbying, and supporting political candidates.

Though time consuming and labor intensive, public participation activities have proven to

bring notable impact on management of people affairs. The reason for this is embedded in

the fact that the numerous roles leaders have for facilitating public participation are broad

and based on common pre-defined deliverable results such as absorption of development

allocations. They also include ensuring that these duty bearers are accessible to the citizens

they represent, ensuring the forums and opportunities for citizens are available frequently,

providing civic education, developing channels for communication, issuing timely

information on all decision-making matters, and accounting for public resources to

facilitate public participation. All these actions have positive impact on citizens and their

countries such as creation of progressive citizens who are enlightened of their community

needs and how governments respond to these needs (Uraia, 2016).

Citizens yearn for improved delivery of services, better credibility on important issues, and

opportunities to address many community concerns that public officials possess

information about. Governments are expected to involve their citizens in identifying

capital-intensive projects that will create employment, empower marginalized groups, and

strengthen democratic processes. Participation in governance remains far from balanced,

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and there is a proven lower proportion of women in the political decision-making realm.

According to UN Women, women accounted for less than 10% of parliamentarians in

approximately 38 counties. The Convention on the Elimination of Discrimination Against

Women (CEDAW) is one of the innovative international bills drafted circa 1979 to lobby

for the rights of women (CEDAW, 2007). Its general recommendations include

discouraging any acts of exclusion or restriction based on sex and supports civil human

rights, and access to civic engagement (CEDAW, 2007). To date, there are over 180 states

that instituted the women’s bill of rights, attending to their interests, such as elimination of

all forms of discrimination (CEDAW, 2007). These early initiatives in minimizing

incidences of discrimination support activism and advocacy by organizations such as UN

Women.

In the United States, the government, engages citizens in direct participation to solve public

problems and is an active democracy (Holzer, Hu & Song, 2004). Women are encouraged

to participate in politics to fight exclusion and injustice in other parts of the world such as

the Middle East and Africa. However, they do not always engage in this form of active

citizenship and as such, the number of women actively attending public sector hearings

around the world is relatively lower than that of their counterparts (Parpart, Connelly,

Connelly & Barriteau, 2000).

In Kenya, public participation is outlined in the Constitution of Kenya, 2010 in Article 118

(1) (GoK, 2010). Article 1(1-4) of the Constitution of Kenya 2010 empowers citizens to

participate in public affairs directly or through elected representatives (Constitution of

Kenya, 2010). The government invites conduction of parliamentary business in an open

manner to the public through committees. Article 232 (1) (d) highlights transparency in

policy making on a timely basis. The PFM Act, 2012, further compels county governments

to establish structures, mechanisms and guidelines for citizen participation (The Public

Finance Management Act, 2012). Kenya’s journey to devolving government services to

the people has been a long one characterized by inequality and in some cases, violent

opposition to women in leadership despite being one way of addressing socio-economic

challenges in society (Kamau, 2010).

In Tharaka Nithi the development of policy documents has been used to address challenges

in making progress towards devolution, as is done at national level (The Government of

Tharaka Nithi County, 2014). These documents have been used to develop local laws that

3

promote equity and inclusivity. They include the County Fiscal Strategy Papers (CFSP),

Budget Review and Outlook Papers (CBROP), Program Based Budgets (PBB), Integrated

Development Plans (CIDP), and Annual Budget. All these documents contain details on

development projects that shall take place in the counties for a five-year period. The process

through which these projects are prioritized for each ward requires improvement through

improved planning, multi-sectoral partnerships, and better citizen engagement frameworks.

Policy documents provide insight on resource distribution for each sector, where the

interests of women and vulnerable groups such as healthcare, education, and

entrepreneurship opportunities lie (The Government of Tharaka Nithi County, 2014).

1.2 Statement of the Problem

Holistic and inclusive decision-making has always been a complex process at all

institutional levels, be it in households, small organizations or multinational organizations,

where prioritization and management of available resources is crucial for sustenance. The

need to ensure the involvement of all affected individuals using criteria such as ethics,

shared concerns, rationality, bias, information availability, Prior to multiparty democracy

in Kenya, organized groups represented women’s preferred platform to push for

constitutional transformation in a patriarchal system. For decades, they have contributed

to institutional change, conflict management, and representation matters among other

issues that influenced today’s political arena (Otieno, 2013). Later, participation in the

electoral process became possible as a result of these efforts. This in turn led to more

Kenyan women recorded as participants in public hearings increased after the introduction

of the county governments from a dismal few. However, the number of women attending

hearings are still fewer than men registered in the same sittings in Tharaka Nithi County

(The Government of Tharaka Nithi County, 2014). County governments are responsible

for consistent inclusion of as many members of the public in decision making as possible

to drive progressive democracy. It is a difficult and expensive process. However, timely

advertising and publicizing of public sector hearings to all demographic groups simplifies

this process. Some of these demographic groups include youth, people with special needs,

women, and children, all of whom require understanding of opportunities are available in

their communities through government programs on a timely basis in a dynamic decision-

making environment (The Government of Tharaka Nithi County, 2014).

4

For years, enlightening the public has been through media channels such as radio,

newspapers, television and social channels. While these options provide information daily

to the public, not all reports on public spending are accurate. Hajli (2018) emphasizes that

many questions frequently arise over ethical aspects in the online communities including

social media, influencing information credibility and perceived usefulness of shared

content despite its increasing popularity.

Shaping decision-making through public channels requires the involvement of

government-endorsed experts in some cases, especially in the wake of social networking

as a tool of empowerment in Kenya. Tharaka Nithi county has 15 wards: Muthambi, Ganga,

Chogoria, Mitheru, Mwimbi, Nkondi, Marimanti, Gatunga, Chiakariga, Mukothima,

Mariani, Karingani, Igambang’ombe, Magumoni and Mugwe. These wards are distributed

across three constituencies: Maara, Tharaka, and Chuka Igambang’ombe. Every ward is

visited annually for citizen engagement through public hearings, monitoring and

evaluation. However, counties continually face social and economic challenges that

influence the proportion of men and women attending public participation. The inability to

include various constituents including women has some effect on. This study endeavors to

examine the effect of women participation in decision making on the issues affecting them

(The Government of Tharaka Nithi County, 2014).

1.3 Purpose of the Study

The purpose of the study was to examine the effect of women representation in public

participation on decision-making.

1.4 Research Questions

The following research questions guided the study.

1.4.1 What is the effect of women socioeconomic factors on decision – making at public

hearings?

1.4.2 What is the effect of women economic empowerment on decision – making at

public hearings?

1.4.3 How does women inclusion influence decision – making at public hearings?

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1.5 Importance of the Study

This study will benefit a number of stakeholders key among them are, policy makers,

scholars, county planning committee and civic educators. These benefits are illustrated in

the following sub-sections.

1.5.1 Policy Makers

The information in this document will be useful to policy makers in Tharaka Nithi county

government and other counties to improve their already-informed processes for the future.

Devolved governments are encouraged to create community development committees

which have the potential to lead wards in the process of presenting development proposals

to county executive level.

1.5.2 Scholars

It will also contribute to the studies that academic scholars will pursue under devolution

and equality.

1.5.3 County Planning Committee

This study provides suggestions on how information collected from vulnerable groups can

be collected and analyzed to provide meaningful advice to county planning committee on

sustainable and utilizable projects in health, economic planning, agriculture, education, and

infrastructure departments. These departments have high capital expenditure and were

devolved with little support from the national government.

1.5.4 Civic Educators

Enhancing civic education and creating awareness to stakeholders has the potential of

improving leadership and inclusive citizen engagement. According to the author of this

report, when women’s participation is significantly improved, community development

committees are likely to succeed in the long term because the number of informed

participants will increase.

1.6 Scope of the Study

Tharaka Nithi County was the preferred location for this study. Although it consists 15

wards, this study will focus on three wards namely Magumoni, Igambang’ombe, and

Karingani. They were three densely populated wards located in the upper and lower zones

of the county. Research focused on employed and unemployed residents who lived and

6

worked in this county, especially actively participated in daily community management

and information sharing, which made them ideal respondents for. Data was collected in the

from August 2019 to September 2019. There were a number of limitations encountered

including, time constraints and resources constraints. The researcher however use a sample

that could be handled with the limited resources and the limited time the researcher had.

1.7 Definition of Terms

1.7.1 Public participation

Public participation is the process of engagement in governance, in which ‘people

participate together for deliberation and collective action within an array of interests,

institutions and net-works, developing civic identity, and involving people in governance

processes (Uraia, 2016).

1.7.2 Socio-economic factors

These are related to economic factors and influence one another. Examples of

socioeconomic factors are access to healthcare, availability of income, employment, and

education levels (Ramirez-Hurtado, Berbel-Pineda & Palacios-Florencio, 2018).

1.7.3 Civic Engagement

This is the political system that works to provide, produce, distribute and allocate public

goods and services to the people (Ross & Savage, 2013)

1.7.4 Economic Empowerment

It is a means through which civilians take part in the development of their communities to

enhance their living standards for the future (Adler & Goggin, 2005).

1.8 Chapter Summary

This chapter has presented the research background information, the problem statement and

the research objective. It has also included, research questions, importance of the study,

study scope and definition of terms. Chapter two presents literature review based on the

research questions. This is followed by the research methodology in chapter three, results

and findings in chapter four and finally summary, discussion, conclusion and

recommendations in chapter five.

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CHAPTER TWO

2.0 LITERATURE REVIEW

2.1 Introduction

This chapter covers literature from some of the sources that contributes to the research on

public participation and women involvement. Literature is reviewed in line with the

research questions.

2.2 Effect of Socioeconomic Factors on Women Decision – Making at Public Hearings

Socio-economic factors are defined as the societal factors that are related to economic

factors and influence one another. Examples of socioeconomic factors are access to

healthcare, availability of income, employment and education levels (Ramirez-Hurtado,

Berbel-Pineda & Palacios-Florencio, 2018). Social development is defined as progress

made in agriculture, rural communities, technology, access to basic needs, and self-

reliance.

Development has become a trendy topic that have steered the conversation from civic

unrest to funding of these initiatives to meet Sustainable Development Goals (SDGs), the

current Millennium Development Goals (MDGs) and the new international economic order

in the short term (Szirmai, 2015). An example of a universal goal that directly addresses

the plight of women is MDG 3 which promotes gender equality and empowerment of

women. These goals were set to be achieved by the end of 2015, but many countries are

yet to achieve these targets. Socio-economic factors impact individuals’ lives who vary in

access for skilled and unskilled employment, availability of basic amenities such as shelter,

likelihood to participate in crime and investing in higher education (Credit Suisse, 2018).

The likelihood of inequality in nations has led to the development index being a measure

of the socio-economic factors highlighted in this study. Businesses therefore take socio-

economic issues as a major contributor to their success and governments. They are the key

proponents to ensuring inclusivity as a method of wealth creation and combating wealth

and income inequality. Credit Suisse (2018) reported that global household wealth rose by

4.6% to $317 trillion and the number of ultra-high net-worth individuals increased. This

indicates that there is now a higher number of women who account for 40% of wealth

according to the same report, among the 42 million millionaires registered worldwide with

an average wealth of $63,100.

8

Social indicators are important because they supplement the feedback obtained from studies

on economic indicators and they enhance the results obtained from qualitative studies on

demographic characteristics of a nation. For example, studies in health examining life

expectancy, energy consumption, literacy levels, access to clean water and equal

opportunities for both genders provide insight to researchers on societies (Szirmai, 2015).

These are all qualitative aspects of communities that are important for comparison purposes

for global analysis of development. As such, UNDP publishes the Human Development

Index (HDI), in a comprehensive report which focuses on different development themes

each year.

2.2.1 Approaches to Improving the State of Socio-Economic

Sustainable approaches to improving the state of socio-economic factors such as education

levels in developing countries include citing nations as case studies that can be used on a

comparative basis to help improve conditions in home counties devising policies to

improve their existing conditions. For example, Tanzania introduced free primary

education in 2001 and improved literacy levels by easing access to universities (Wiafe -

Amoako, 2018). The development was significant because the county depends on coffee

which is a major forex earner, with over 20 levies, taxes and licenses charged to farmers.

Kenya in comparison exported a higher amount of coffee per acre and did not impose such

high taxes. According to Hine (2018), the gender gap in girls’ education in Kenya is slowly

being reduced through increased prioritization of the cost of education to keep girls

enrolled. This comes at the cost of reducing early marriage and the perceived economic

benefits that come with the tradition. As such, the transition of girls moving from secondary

school to universities is still low in some parts of Kenya such as Trans Mara West, and

Narok North (Hine, 2018). However, if farmers access public participation forums, they

can provide cultural insight to the approaches selected by economic planners, rather than

adopt approaches selected from advanced economies. This is what Siala (2015) describes

as an increased degree of citizen engagement, which endorses socioeconomic and cultural

behavior. It also enables core tenets of structure and systems to provide motivation behind

each practice (Siala, 2015).

Developed nations used for comparison in North America, Europe and Asia, such as the

United States, United Kingdom and Malaysia (Szirmai, 2015). Evaluating the historical

processes in economic growth for modest but numerous savings made by citizens have

9

contributed to the income considerations that governments, entrepreneurs and innovators

consider for the improvement of socio-economic conditions. Therefore, both social and

economic factors that contribute to progress in civic education which requires analysis of

existing problems in a realistic and critical manner. This is one way of mitigating the

decline in social and economic inequality which focuses on the benefit of the masses, rather

than a chosen few (Szirmai, 2015).

A strong correlation was found between enhanced socio-economic status and lower fertility

rates, as a result of improved education levels and employment opportunities. Increased

equality between men and women in general led to a reduced rate of childbearing. The

sacrifices that women make to pay for their education are also related to the access to

information on family planning services which include birth control alternatives.

Governments are responsible for imposing social discipline, which ensures that

developmental targets are attained by citizens (Szirmai, 2015). Targets such as minimizing

environmental pollution, equitable distribution of resources, poverty reduction and

inclusion are some of the factors that this research highlights. These specific goals can be

sustainably addressed through involving citizenry consistently and carefully considering

suggestions and proposals presented.

Social capabilities include the technical competence a nation’s population owns. That

includes the availability of basic education, managerial expertise, financial services, access

to capital, infrastructure availability (power, transport, and communication), and access to

supporting services (Szirmai, 2015). Kenya is working towards attainment of free primary

education to address availability of basic education in the 47 counties.

In addition to this, establishment of personal identity that maps out attributes, traits, belief

system, interests and competencies can improve the success rate of women willing to

venture into economic activities (Greene & Brush, 2018). Encouraging women to own their

identity and aspirations through social entrepreneurship enhances economic growth and

diversity in addition to solving pressing societal problems. Women can also analyze social

and psychological issues that can identify behavior that can improve previously wrongly

prescribed situations in society. This ability can help align social norms to improve decision

making and improve outcomes.

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The cultural and institutional factors that influence the decisions that men and women make

come after considerations such as social prestige, beyond religious preferences.

Considering future comfort influences the number of children women chose to have. For

example, the conviction that better education and employment opportunities lay ahead can

influence family sizes. Government programs influencing polices and legislation,

expenditure and taxation are therefore major determinants of socio-economic wellbeing.

Policies and legislation aimed at changing matters such as marriage, consent, breastfeeding,

birth control, and abortion are currently highlighted in current affairs around the world. In

Kenya, Mosley’s model proves that child mortality is directly influenced by education level

of the mother whose behavioral tendencies are likely to include basic hygiene and proper

nutrition practices (Szirmai, 2015).

2.2.2 Social Networks

Social obligations in African countries influence the social networks established for better

access to economic success and bonding is reinforced during leisure activities that build

social cohesion (Szirmai, 2015). Public participation forums are examples of gatherings

that can provide platforms for women to learn about new approaches to accessing jobs and

trading activities. Cultural practices encouraging social activities enable women to have

opportunities to accessing incentives likely to prevent default on obligations. One such

obligation is active participation in civic affairs, solidarity, and civic participation (Szirmai,

2015).

One study focusing on healthcare policy development observed that researchers could

associate the high performing health indicators with women who enjoy higher social status

and relatively higher education levels (Szirmai, 2015). Enlightenment on the importance of

hygiene, medical facility access to obtain treatment was realized among women with the

enhanced awareness of women. The link to religion also contributed to the rate of

acceptance of better health choices.

Sexual discrimination against women occurs at different levels in the world’s religions and

diverse cultures. For example, the Indian caste system propagates underproductivity. The

reason for this is occupational discrimination which restricts the talents women have. As a

result, women hold fewer jobs in health and education (Szirmai, 2015).

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Threats to inequality alleviation include gender discrimination and violence which are both

rampant in Islamic culture - women face restriction on the education level they attain. This

is bound to affect their access to the trading, entrepreneurship, and influence the wellbeing

of children. Violence is an inhibitor of women’s political empowerment, impeding civil,

economic cultural rights, and can be contributed to by socioeconomic factors (Alesina,

Brioschi & Ferrara, 2016). Examples of nations that have provisions inhibiting violence

towards females include Malawi, South Africa and Zimbabwe in Africa. Preventing

harmful practices and norms such as the asymmetric burden on women addressing

household responsibilities is important in the development of better approaches to

increasing empowerment of communities and should be carried out in line with

international legal framework regarding public and political life (Rueschemeyer, 2016).

One such way is through increased civic education among women and girls, which can

improve their likelihood of political success, as was done in Poland.

Better civic education leads to an increased likelihood of participation in governance issues

and 5 improved selection of priority county-funded projects among citizens who believe

the priorities listed in each sector as a good fit to the needs of various social classes (Siala,

2015). Further, identification of opportunities to increase entrepreneurship among women

and youth can be done better when elevated levels of social inclusion endear towards the

financial implications of budgeting and economic planning. A reduced likelihood of

financial exclusion in hard to reach areas is minimized and tendencies towards

manipulation are avoided, according to Arnstein’s ladder of citizen participation

(Arnstein,2015). Strengthening democracy at county level can be done by the eight levels

of citizen participation proposed by Arnstein (2015): manipulation, therapy, informing,

consultation, placation, partnership, delegated power, and citizen control.

2.3 Effect of Economic Empowerment on Decision Making at Public Hearings

For the first section of this review, we shall begin by defining terms around civic

engagement. Adler and Goggin (2005) define it as means through which civilians take part

in the development of their communities to enhance their living standards for the future.

The definition that the author of this proposal relies on to define the public sector is a

combination of functions and institutions that are performed by government bodies (Levac

& Cowper-Smith, 2016). Ross and Savage (2013) defined it as a political system that works

12

to provide, produce, distribute and allocate public goods and services to the people. Both

definitions capture the core activities involved in many government agencies.

However, the practices and norms associated with public service provide methods of

carrying out civic education, according to public administration scholarship and practice

(Denhardt & Denhardt, 2015). Continuous education is one of the tools used to ensure that

civilians benefit from learning resources in the form of policy documents, presentations by

seasoned public servants, and international organizations dedicated to improving

information exposure levels of participants. The movement has particularly emphasized

efforts to empower previously unreachable sections of women and youth.

2.3.1 Empowering Citizens

In a 2016 report, Hivos committed to empowering citizens in Kenya through supporting

the government (Hivos, 2016). One of their proposed approaches was through the Dutch

Ministry of Foreign Affairs which supports civic engagement through open contracting.

Hivos has also aided in supported the establishment of safe spaces online that do not support

online harassment of women and improving working conditions for women in flower

farms, where women constitute 70% of the labor force (Hivos, 2016). Their work through

the SDG 8 promotes sustained, inclusive and sustainable economic growth, full and

productive employment and decent work for all. The organization runs programs and

projects internationally in establishing inclusive platforms and rights, agriculture, energy

development, sexual rights, and diversity, investing over 6.474 million Euros just in 2015.

Africa is considered a resource-rich continent, with 54 different countries endowed with

labor, capital, mineral and other resources that are unequally distributed. For example,

Oxfam (2019) reported that Africa’s richest control more than over 650 million people

within the same continent. The continent is plagued by dilemmas such as inability to

educate children and unsustainable debt in nations such as Ghana, Egypt, Cameroon,

Mozambique and Nigeria. The same report states that females have a higher likelihood of

being poor in the continent, and a lower probability of advancing in their studies (Oxfam

International, 2019). Unpaid labor is characteristic in nations such as Kenya where

healthcare costs, where 50% of the population hold approximately $22.98 billion.

Major challenges that arise in the computation of economic growth include pegging all

progress in monetary terms. Developing countries focus on subsistence production which

13

only partly regards money as national income. Further, Gross National Product (GNP)

calculation inadequately factors in results of the informal sector, which dominates the

developing world (Szirmai, 2015).

2.3.2 Women in Leadership

According to research, the challenges women face when attempting to participate in

governance include constant downplaying by male counterparts and the presumption that

women are second class citizens (Otieno 2013). Of course, this remains a debatable point

of view considering the impressive accomplishments that women have made when granted

the opportunity to build their nations.

According to the International Knowledge Networks of Women in Politics, when women

are enabled to become leaders in political realms, their nations enjoy higher living

standards, improved infrastructure, education, and health services. The conclusion is based

on the observation that in 2016 when the number of national women leaders was only 6.9%,

but since then, steady increase in participation by women has led to the improvements

previously discussed.

The widening stream of women becoming heads of state, members of parliament and

representatives is due to continuous adult training and capacity building designed

specifically to improve female skills in a male-dominated field. When measuring

socioeconomic indicators is done, quantifiable variables are usually considered for

researchers to understand demographic factors better. Measurement of growth and

development is done through evaluating changes in indicators to each variable (Szirmai,

2015). For example, increments and decreases in national income can be calculated through

computing all incomes, which include wages, profits, interest, dividends, and rent.

Alternatively, it can be calculated through calculating the national product. For each of the

indicators, it should be observed that there is little or no distinction between male and

female contribution to the indicator. This is just one of the technical problems involved in

measurement of economic growth and shows that growth and development are neutral to

the self-imposed distinctions that individuals make. An increase in these indicators is

therefore a product of the collective efforts of a nation’s people (Szirmai, 2015).

Demographic characteristics vary in developing counties. They include population size,

population density and population growth rates. In the data provided in this research, the

14

proportion of female and male population is skewed towards women. Fluctuations in

demographics influence regional characteristics and therefore differences in experiences

are seen in regions of Sub-Saharan Africa, South Asia, East Asia and Latin America

(Szirmai, 2015). These in turn are influenced by socioeconomic factors such as income

levels because the size of income gaps between countries and regions is based on economic

interests and trade which may be dependent of independent, especially in developing

nations. Wilkinson and Pickett (2017) argue that inequality in income can even cause

prevalent health and social problems.

Vuleta (2018) asserts that an increasingly precarious political and geographic environment

exists. Women such as Theresa May, Christine Lagarde, and Angela Merkel have the

potential to steer European economies through their participation in the EU and German

government respectively. The former ranked first of twenty - two influential women around

the globe, while the later ranked second on the same ranking according to Forbes Magazine.

Despite the success that they enjoy, they are also subject to numerous setbacks in politics

and policy development. Hilary Clinton for instance, was the subject of severe criticism

over decisions that she made throughout her career. Indeed, women are subject to higher

levels of scrutiny in contemporary media culture, especially when they exhibit social

influence.

2.3.3 Improve the Livelihoods

With regards to socioeconomic impact and policy development, third world countries are

still looking for ways to improve the livelihoods of their people. Developing nations have

a range of similarities such as large shares of agricultural production and smaller

proportions of industrial production which have been utilized for many years as a means of

economic empowerment. This has led to devolved governments prioritizing key sectors

considered the drivers of development and presenting healthcare, education, water, and

agriculture agendas in manifestos (Njuki, 2017).

Agricultural developments over the past 12,000 years have led to the spread of inequality

due to the egalitarian origins of both political and economic features in societies (Mattison,

Smith, Shenk, & Cochrane, 2016). Additionally, developing nations also experience a wide

gap between the modern and traditional sectors, characterized by adaptive and primitive

technology approaches in the economy and these areas of interest impact the appeal of

specific careers for females in comparison to their counterparts (Szirmai, 2015). Otieno

15

further argues that women lack tools creating access to power. One could argue that perhaps

this is one of the reasons why women refrain from active participation in politics in Kenya:

they see their contributions as means with no fruitful ends.

Inevitably, income available to households must be computed after statutory

responsibilities (such as taxes and licenses) have been met and for years, these taxes have

been excessive (Wiafe -Amoako, 2018). This in turn leads to the economic resources

available to sustain wellbeing becoming fewer in the developing world. Low income levels

influence life expectancy, mortality and infant mortality rates (Wilkinson and Pickett,

2017). By participating in discussions around the economy, participants can learn more

about the policies in their counties, their history and their direct impact on their lives. This

is particularly important in regions that depend on agriculture, tourism, and mining:

Tharaka Nithi is an example of a county that fits this description (CIDP, 2017/18-2021/22).

Major challenges that arise in the computation of economic growth include pegging all

progress in monetary terms. Developing countries focus on subsistence production which

only partly regards money as national income. Further, Gross National Product (GNP)

calculation inadequately factors in results of the informal sector, which dominates the

developing world (Szirmai, 2015). Opinions on appearance, beauty, intelligence are

relentlessly highlighted in addition to attention-drawing opinions (Elias, Gill & Scharff,

2017). Does this phenomenon increase oppression? The author of this proposal believes

so because the diversity of choices that women make is based on their willingness to be

criticized despite the economic, industrial, financial, religious and social benefits that come

with participating in decision-making in employment (Hakim, 2016).

2.4 Influence of Inclusion on Women Decision Making at Public Hearings

According to Percy (2018), policy development is plagued by vague mandates that

influence the rate of development specifically in the infrastructure sector, education, and

employment practices. These are sectors that directly affect women and their performance.

Policy development plays a major role in wealth distribution and equality, impacting the

roles that women play in society. Public participation is a political principle whose ideals

are embedded in inclusivity in terms of access to the previously discussed socioeconomic

factors and access to leadership.

16

2.4.1 Inclusivity

Inclusion allows fair sharing of opinions despite differences in ethnic backgrounds. It can

therefore be included that inclusion in the digital age improves the competence of citizens

based on their access to various forms of media (Schulz, Ainley, Fraillon, Losito, Agrusti,

& Friedman, 2018). Experts argue that religion helps popularize inclusive values that

enhance the process of political participation in an era where there is always room for

improvement especially in citizenship education for the youth. Religion promotes access

to early opportunities in politics and molds the ideals of a nation such as environmental

awareness and collective efforts to combat current issues such as climate change (Schulz,

Ainley, Fraillon, Losito, Agrusti, & Friedman, 2018).

Inclusive societies are also reported to have better levels of peace, tolerance in their

education systems and high achieving students with strong civic and citizenship capacities.

This further enhances the level of autonomy in institutions such as schools and encourage

experiences in decision-making. Attitudes towards democracy, equal opportunities,

perceptions to global issues are fostered in learning institutions where youth first learn

about foreign affairs: past leaders seeking to mentor future generations of political experts

have an interest in ensuring inclusivity at academic level (Schulz, Ainley, Fraillon, Losito,

Agrusti, & Friedman, 2018). Further, authors argue that just before 1990, over 80% of

participants of one Gallup Poll were convinced that those living with disabilities in the U.S.

received insufficient support. The situation had improved since the 1960s, but not

significantly (Percy, 2018). This is case of America’s policy development processes

illustrates how policy implementation and public services are both overwhelmed by low

levels of women engagement.

For 2019, the HDI Report will focus on inclusivity, in addition to providing an international

ranking on the income levels, education and health – all major socioeconomic indicators

highlighted in this paper. SDG 10 which covers inequality is at the core of the discussions

on the HDI report, which also factors the critical role families play as incubators of

individual social development (UNDP, 2019). Szirmai (2015) delves further and

conceptualizes approaches to development into two: fighting against poverty and analysis

of long-terms economic and social development in his argument for developing countries

and the importance of understanding of socio-economic development. For the billions of

individuals living on $1.25 a day (Banerjee, Duflo, Goldberg, Karlan, Osei, Pariente &

17

Urdy, 2015) to experience an improvement in their living standards, a great deal of progress

must be made. If more educational opportunities are awarded to women, the costs

associated with childbearing and raising children (Szirmai, 2015).

2.4.2 Inequality

One of the reasons for the imbalance witnessed in socioeconomic factors and achievement

of development goals is inequality (Wilkinson & Pickett, 2017). Socio-economic factors

have a significant effect on the contributions to household income and therefore

opportunities to improve inclusivity. For example, African housewives still require the

assistance of children to provide food. Based on the family structures that exist in the

society, the distribution of costs and benefits limit family size and therefore the ability of

women to provide for their nuclear and extended families (Szirmai, 2015).

Conceptualization of formal and informal political spaces for women and potentially

increase the entrepreneurship pool and skilled workforce (Hakim, 2004). Innovative

creation and design of public policy includes the involvement of all available stakeholders.

However, this balancing act has taken organizations and governments years to improve.

The devolution system in Kenya committed to increase the capacity of women through the

minimum of one third gender rule (Mudi & Waswa, 2018).

Admittedly, the male-dominated parliament still requires an objective means of managing

employment opportunities for women in Kenyan society and women in politics continue to

gain interest and scrutiny (Biegon, 2016). Having at last 33% of women appointed to

leadership roles would significantly improve the roles that females play in leadership.

Today, only two of the forty-seven county governors are women. The overall effect of this

shows sluggish progress from the first MTEF period where none of the 47 governors were

women (Kivoi, 2014). Satisfaction of both male and female citizens of all ages is less than

satisfactory, despite the masculine political ideologies spread by the media to date,

questioning the effectiveness of empowering women.

2.4.3 Ethnic Politics

One study asserts that in addition to the slow pace of change, ethnic politics in multiethnic

societies present opportunities and conditions hindering even the most fundamental forms

of participation by women in sub-Saharan Africa (Arriola & Johnson, 2014). Researchers

also discovered that in the 34 countries in the study, those with highly politicized ethnic

18

groups had fewer female MPs. This study utilizing data from 1980 to 2005 argued that the

proportion of women representatives rises in more democratized nations. In Uganda,

researchers found that basic need security and wellbeing increased in families where a

woman was a member of an agricultural cooperative and bore knowledge of agronomic

practices. The quasi-experimental study examined women in the north-eastern region and

found that women’s empowerment bridges the gender inequality gap (Lecoutere, 2017).

For decades, governments have been requested to revolutionize their approach towards

engaging the public through value addition (Hassan, 2017) in order to enhance an otherwise

dull and boring activity of increasing social competence. This has led to the development

of development groups, unions, and other groups designed to improve the bargaining

capital of interested parties.

Social movements have gained influence over the past decade as a result of the

development of coordinated factions that better understanding of the needs of the nations

including water, sanitation, hygiene, labor management, and youth engagement. In 2012,

Canadians took protests to Quebec presenting their discomfort with labor laws and austerity

measures (Collombat, 2016). This is an example of a dialectical approach that organized

groups resort to once formal communication channels become ineffective and when a

government and its people fail to reach compromise.

2.4.4 Contribution of Women in Leadership

Some research suggests that women provide diversity and intersectionality when involved

in leadership and in order to counter under-representation, females should be involved in

decision-making (Cook & Glass, 2014). Strengthened negotiating capacity and access to

justice for communities comes from inclusion of women. This is the only way in which

organized change can be planned for (Maracle, 2018). Findings on inclusive leadership in

six countries (India, Germany, Mexico, USA, Australia, and China) show that innovation

levels improved under inclusive environments. Further, the study concludes that the more

people felt involved, the better their sense of duty became: team objectives were met

quicker and a sense of belongingness and endearment improved the workplace (Prime &

Salib, 2014).

Unique skills provided by women include human resource management, professional

competence, risk management, and business sustainability. They all improve firm value

19

(Kim & Starks, 2016). Government and non-government agencies benefit from these

aspects of strength. In corporate boards, gender diversity with a preference for women is

argued by these authors to lead to high firm value and stronger market value. Performance

mechanisms chosen by female directors in leadership are also hypothesized to be of better

quality and long-lasting impact in business.

Once focused on governance, the skill sets positively impact forgotten populations such as

poor and vulnerable young people who face more risk factors in comparison to their peers

(Arora, Shah, Chaturvedi, & Gupta, 2015). These factors and indicators are health related

factors, social factors, and family problems. Women can address these challenges through

their participation in governance and well-respected leaders have exhibited their

competence in and their employment could improve governance.

Increasing autonomy through increasing the formal education of women has been proven

to improve decisions in reproductive health in Nepal. Safer sex practices among married

women was high for women and their ability to negotiate and take part in decision making

and asset acquisition (Atteraya, Kimm, & Song, 2014). It is important for women to

empower women to make simple and complex decisions in every aspect of national growth.

Women provide additional skills to the negotiation table. For example, women are

described to have budgeting, multi-tasking, persuasive and negotiation skills once they

become entrepreneurs (Greene & Bush, 2018). “Mumpreneurs” posit experiences that they

have mastered, such as giving birth and raising children, which provide insight to important

social skills (Markowska, 2016).

2.5 Chapter Summary

This chapter began by presenting an introduction of the literature review for the topic which

covered highlighting socioeconomic factors, economic empowerment, and inclusive citizen

engagement. It continued to provide information to readers on the theoretical views of

public sector hearings and shared information such as the threats and benefits that come

with empowering citizens to participate in public hearings. Examples of policies made with

both high and low levels of public participation were provided and the ladder of public

participation according to Arnstein was explained. The next chapter provides research

methodology followed by results and findings in chapter four and finally, summary,

discussion, conclusion and recommendations in chapter five.

20

CHAPTER THREE

3.0 RESEARCH METHDOLOGY

3.1 Introduction

In the chapter, research methodology is provided, giving specific details about the methods

and procedures used to carry out the study. The first section explains the research design

followed by target population and sampling design. Thereafter, the sampling frame and

techniques as well as sample size are provided. The last sub-section contains the data

collection methods, research procedures and data analysis methods.

3.2 Research Design

Research design identifies efficient methods of evaluating solutions for unique societies,

especially in clinical research (McCusker & Gunaydin, 2015). It is the process of using real

world approaches to obtain information for qualitative and quantitative research, for non-

business disciplines at post-graduate level and knowledge creation for undergraduate

students (Quinlan, Babin, Carr, & Griffin, 2019). Kumar (2019) defines research design as

a two-pronged approach that involves conceptualization of a study and establishing an

organized means of obtaining answers for the research questions formulated in the research

process. These two functions ensure that researchers identify the correct population,

sampling method, contacting methods, and response mechanisms to participants’ questions.

Bhat (2019) defines exploratory research as research approach used to investigate problems

that are not well defined. In this case, the reasons for poor participation of women are not

simple to identify and originate from a range of causes unique to each ward visited. The

author of this project combined two approaches to research design, namely action research

which focuses on investigative and diagnostic data collection and exploratory design which

was used to gain information on the public sector topic to answer the research questions

presented in section 1.3. Both approaches aided in identification of institutional

weaknesses in the process of public participation at county government level (Siala, 2015).

It was also affordable for the author to carry out both action and exploratory research

because both methods provided the necessary tools required to establish the causes of

challenges in public participation events.

21

3.3. Population and Sampling Design

This section provides a breakdown of the population in the county under the study and

arrives at a justification for the research design that will be used. Data will be provided in

tables from county data from the county department of finance and economic planning.

3.3.1 Population

A population is defined as the cumulative number of elements under scrutiny or can be

observed and share common characteristics in a set is the description of a population

(Anderson, Shoesmith, Sweeney, Amderson, & Wiliams, 2014). According to the Ministry

of Devolution (2018), Tharaka Nithi had a population of 365,330. The following tables

summarize population projections for Tharaka Nithi County and break down demographic

factors for each ward and include the number of those living with special needs, education

level, and gender. The target population was women and men who are not part of the

economic planning process but residents of the county but aware of the development

agenda in Tharaka Nithi. One other criterion used for the population was chosen to select

direct beneficiaries of the county government services. Appendix VI under appendices

breaks down the population of each constituency or ward in Tharaka Nithi County.

Table 3.1: Population Distribution and Density by Constituency/Sub County

2009 Census 2018 Projections 2020 Projections 2022 Projections

Constituenc

y

Mal

e

Fem

ale

Tot

al

Mal

e

Fem

ale

Tot

al

Mal

e

Fem

ale

Tot

al

Mal

e

Fem

ale

Tot

al

Tharaka 628

87

6721

1

130

098

738

40

7891

7

765

22

765

22

8178

4

158

306

793

02

8475

4

164

056

C/Igamban

g’ombe

621

77

6593

0

128

107

730

06

7741

3

150

419

756

58

8022

5

155

883

784

06

8313

9

161

545

Maara 533

87

5373

8

107

125

626

85

6309

7

125

783

649

62

6538

9

130

352

673

22

6776

5

135

086

Total 178

451

1868

79

365

330

209

531

2194

27

428

959

217

142

2273

98

444

540

225

030

2356

58

460

688

Source: KNBS, Population and Housing Census, 2009

22

Table 3.2: Overall Employment by Education Levels in Tharaka Nithi County

Category Percentage of Total Population Total

Population

None 12.7 10.0 60.7 1.8 8.5 0.5 2.1 3.9 15,512

Primary 15.1 10.7 55.1 0.5 6.9 8.6 0.4 2.7 118,084

Secondary 25.0 10.9 34.6 0.8 5.8 19.3 0.2 3.4 66,839

Total 18.2 10.7 48.7 0.7 6.7 11.5 0.5 3.0 202,887

Source: KNBS, Population and Housing Census, 2009

3.3.2 Sampling Design

This is the process of obtaining observations by examining a portion of the population,

rather than the entire population. Targeting a random sample will aid in determining if the

intervention to increase the number of women in public participation is effective (Leppink,

2019). Purposive sampling was used to identify Karingani, Igambang’ombe and Magumoni

wards for the population from a list of all the county participants who attended public

participation forums during FY 2018-19. A total of 60 respondents was the preferred

number by the researcher, because this would allow for distribution along location and

availability parameters.

3.3.2.1 Sampling Frame

A sampling frame lets a researcher list all groups within a population and samples are

selected from the frame to ensure representativeness (Walliman, 2017). The sampling

frame also contains an identifying number for each respondent to assist researchers and

research assistants to further subdivide the sample for further analysis (Njogu, 2018). The

sampling frame for the study will be obtained from the list of participants who attended

2018/19 public participation hearings, approved by the department of finance from the three

wards. An excerpt of this list is available in Appendix C, with contact details of

respondents.

3.3.2.2 Sampling Technique

Neelankavil (2015) defines a sampling technique as the collective steps taken to select

components that represent a whole. Specifically, cluster sampling was used to

geographically categorize 400 participants who originate from 3 wards. For the researcher

to obtain responses from subpopulations with specific characteristics required for the study,

purposive sampling was carried out to enable the author to obtain unbiased and well

diversified information on the state of public participation in the county. For example,

23

members of special interest groups who attend public participation were requested to

respond through the questionnaires, as an important subpopulation.

3.3.2.3 Sampling Size

The sample was targeted from markets, town centers and was requested for permission

before the questionnaires were distributed. Once consent was obtained, research assistants

and volunteers shared the precise number of questionnaires to respondents allowed to seek

clarifications regarding the exercise. The project researcher was also available to answer

questions in many cases.

For the research to experiment if the individuals in each group are subject to the specific

conditions, stratified random sampling will be done to provide an unbiased estimate in

comparison to the standard error (Leppink, 2019). Sampling size is represented by ‘n’ and

will be obtained by n = N / ((1+N (e2)), according to Singh & Masuku (2014) where:

n = the sample size

N = the sample population

1 = constant

e2 = the estimated standard error where a 95% confidence level is used with a 5% standard

error.

n = 460,688 / ((1+460,688(0.052) = 400

This sample size ‘n’ was the minimum total number of respondents required for this

research, in comparison to the proposed 60 as shown in table 5. Table 3.3 illustrates the

sample size for this study.

Table 3.3: Sample Distribution

Ward Respondents

Karingani 134

Igambang’ombe 133

Magumoni 133

Total 400

24

3.4 Data Collection Methods

This study involved the collection of primary data. The study used structured questionnaire

to collect primary data. It is advisable to use structured questionnaire to prevent

misconception of the idea of study, while at the same time it is deemed appropriate for

descriptive research because it allows the researcher to investigate perception of

participants on the variable of study.

The questionnaire items were constructed from the research questions while it also

contained questions to capture respondents’ demographic data. The questions on the

research questions were constructed in a Likert Scale nature with a 5 point scale. The first

part contained the demographic questions, the second part captured effect of women

socioeconomic factors on decision – making, the third part captured effect of women

economic empowerment on decision – making, the fourth part captured how women

inclusion influence decision – making. The fifth part contains questions on women decision

making and the last part had general questions. These formed the data that was analyzed

and interpreted.

3.5 Research Procedures

This research was carried out in an orderly manner in order to attain its purpose and ensure

reliable data collection and analysis. First, an introductory letter was obtained from the

Institution Review Board in USIU-A. This letter enabled the researcher to apply for

NACOSTI permit for carrying out the research. The researcher then approached the

respondent with these letters and voluntarily recruited participants. Following their

approval and acceptance to participate in the study the researcher first involved 10

respondents in a pilot study. The pilot study raised a number of issues such as unclear

questions, ambiguous questions and unnecessary questions. The questionnaire was

readjusted to ensure they collect accurate information.

The actual study followed the pilot study after the review of the questionnaire. The

questionnaire during the actual study were dropped to respondents at their convenience.

They were given 1 day to fill the questionnaire and the researcher revisited them to collect

the completed questionnaires the next day. This enabled a high response rate because the

respondents had a whole day to respond to the questionnaire. The researcher further,

informed the respondents how the data would be used and the confidentiality of their info

and that participation would be voluntarily. This facilitated collaboration from the

25

participants and also ensured the researcher remained ethical by using the data only for the

intended academic purpose.

3.6 Data Analysis Methods

This study collected quantitative data from the participants. The data was analyzed

statistically through both descriptive and inferential statics. It was first cleaned and coded

in preparation for data entry into Statistical Package Social Sciences (SPSS), and then

entered in SPSS prior to analysis. Descriptive analysis was performed by calculating the

percentage and average scores and standard deviation values of the field data. This enabled

the researcher to describe, illustrate and summarize the large quantity of collected data in a

significant way. Inferential statistics involved correlation and regression analysis that was

done to assess the relationship of the study variables. The data was presented in figures and

tables.

The regression equation used is represented below:

Y=a+ b1x1 + e

Y= Dependent variable (decision making)

a = constant

x1 = Independent Variable (socioeconomic factors, economic empowerment, inclusive

citizen engagement).

3.7 Chapter Summary

This chapter has summarized the various research methods that the author proposes to

utilize for the project, which included targeting 60 respondents for questionnaire

distribution, telephone interviews, and focus group discussions. Research design, sampling

design, and data collection methods were discussed in the initial sections of the chapter

were linked to the use of primary and secondary data sources obtained from the Budgeting

and Economic Planning Unit. The pilot run to test effectiveness of the research tools and

analysis methods was discussed in this chapter and a preamble to the analysis methods used

are highlighted in the concluding sections of this chapter. The next chapter provides results

and findings followed by summary, discussion, conclusion and recommendations in

chapter five.

26

CHAPTER FOUR

4.0 RESULTS AND FINDINGS

4.1 Introduction

This chapter presents the results and findings of the study. Results are presented in line

with the research questions starting with response rate and background information. This

is followed by effect of socioeconomic factors on decision making, effect of women

economic empowerment on decision making at public hearing, and finally, women

inclusion influence decision making at public hearings.

4.2 Response Rate and Background

This sub-section provides response rate and background information. It starts with response

rate followed by background information. A total of 120 women and 116 men recorded

their respondents through submitted questionnaires and shared their feedback on the nature

of high capital projects that the county would benefit from and suggestions on how to

improve the participation of women in decision-making on project selection activities.

4.2.1 Response Rate

The researcher targeted 400 respondents overall, consisting of an equal number of male

and female respondents. However, a total of 236 questionnaires were received after

distribution representing a 59% response rate.

4.2.2 Background Information

The background information section showed that respondents were classified according to

gender, age, academic qualification, employment status, religion, and ward.

4.2.2.1 Respondents’ Gender

Information provided by respondents showed that there were 120 women and 116 men,

representing 50.6% and 49.4% of the respondents respectively. This is illustrated in Figure

4.1.

27

Figure 4.1: Respondents’ Gender

4.2.2.2 Academic Qualification

The respondents shared information on their levels of education. Approximately 17% of

respondents attained only primary school education while 56% of all respondents attended

secondary school. According to results 26%of all respondents attended tertiary institutions

such as TVET, colleges, and universities. The results are shown Figure 4.2.

Figure 4.2: Academic Qualification

4.2.2.3 Employment Status

With regards to employment and empowerment opportunities, respondents shared the

following: 32.2% of men are employed while 37.4% are employed women. In total, 82

respondents classified themselves as employed while 154 did not. This includes

respondents who did not consider subsistence farming gainful employment and shows that

0.00%

10.00%

20.00%

30.00%

40.00%

50.00%

60.00%

Primary Secondary Tertiary

18.50%

54.60%

26.90%

Academic Qualification

49.40%

50.60%

Respondents' Gender

Male

Female

28

66.4% of all respondents were unemployed and only 33.6% are employed. This is shown

in Figure 4.3.

Figure 4.3: Employment Status

4.2.2.4 Public Participation Knowledge

With regards to public participation 77.5% of respondents claimed to have knowledge of

the exercise taking place annually, while 22.5% of male and female respondents had no

knowledge of public participation. This is as displayed in Figure 4.4.

Figure 4.4: Public Participation Knowledge

4.2.2.5. Healthcare Access

The participants responded as follows to the question “Do you have access to healthcare?”

Table 4.1 shows these responses.

77.5%

22.5%

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

80.0%

90.0%

Yes No

Public Participation Knowledge

29

Table 4.1: Healthcare Access

Gender

Yes, I have access to

healthcare

No, I do not have access to

healthcare

Male 94 27

Female 89 26

Total 182 53

4.2.2.6 Involvement in Public Participation

The respondents shared information on their interaction with public participation, based on

if they have attended the barazas. According to findings, 57% of the respondents were not

involved in public participation, only 43% were involved in public participation. This is

shown in Figure 4.5.

Figure 4.5: Involvement in Public Participation

4.2.2.7 Community/Political Group Membership

This study sought to find out the involvement of the respondents in community and/or

political group membership and leadership. According to findings shown in Figure 4.6,

55.3% of the respondents were members to a community and/or political group while

44.7% were not. Results also showed that those who were members to a community and/or

political group, 36.6% of them participated in leadership of the group while 63.4% were

not involved in the leadership of the group.

57.0%

43.0%

Involvement in Public Participation

Yes No

30

Figure 4.6: Community/Political Group Membership

4.3 Effect of Socioeconomic Factors on Decision-Making in Women at Public

Participation Hearings

This study examined several factors relating to socioeconomic and their effect on decision

making among women in public participation. Findings showed that 24.8% of the

respondents felt that health and community awareness projects was a very good contributor

to women decision making, 31.8% felt it was a good contributor and 13.9% were neutral

while 15.6% thought it was a poor contributor and 13.9% thought it was very poor

contributor. This had a mean of 3.8 and a standard deviation of 0.3. According to 31.1%

respondents said that education projects were a very good contributor to women decision

making, 34% also felt education projects were a very good contributor while 18.5% were

neutral and 12.6% thought it had a poor contribution and 3.8% felt it had a very poor

contribution. This had a mean of 4.2 and a standard deviation of 0.7.

Entrepreneurship opportunities, according to 20.8% of the respondents was a very good

contributor to women decision making and according to 20.8% it was a good contributor

while 34.2% were neutral and still according to 14.3% it was a poor contributor and 12.5%

felt it was a very poor contributor. This had a mean of 4.6 and a standard deviation of 0.8.

Women and youth employment creation was a very good contributor to women decision

making according to 15.4% respondents while according to 31.6% it was just a good

contributor, however 25.6% were neutral and still 14.1% thought it was a poor contributor

0.0%

10.0%

20.0%

30.0%

40.0%

50.0%

60.0%

70.0%

Community/Political GroupMembership Leadership

55.3%

36.6%

44.7%

63.4%

Community/Political Group Membership & Leadership

Yes No

31

while 13.3% thought it was a very poor contributor. This had a mean of 4.0 and a standard

deviation of 0.7.

According to 12.9% respondents ATI/veterinary lab/ milk processor plant construction and

farm input provision was a very good contributor to women decision making while 21.3%

felt it was just a good contributor but 17.1% were neutral and yet 21.3% felt it was a poor

contributor and 27.4% felt it was very poor contributor. This had a mean of 4.7 and a

standard deviation of 0.9. Water project was a very good contributor according to 25.5%

and according to 28.9% it was just a good contributor while 13.7% were neutral and still

20.1% felt it was a poor contributor and11.8% felt it was a very poor contributor. This had

a mean of 3.8 and a standard deviation of 0.5.

According to 19.7% of the respondents housing was a very good contributor to women

decision making and 27.5% felt it was good contributor while 21.5% were neutral and still

17.1% thought it was a poor contributor while 14.2% felt it was a very poor contributor.

This had a mean of 4.6 and a standard deviation of 0.4. Electrification and ICT connectivity

was a very good contributor according to 21.7% and 38.7% felt that it was a good

contributor while 17.4% were neutral and still 10.0% felt it was a poor contributor

and12.2% felt it was a very poor contributor. This had a mean of 4.1 and a standard

deviation of 0.6.

Roads, footbridges and bridges were a very good contributor of women decision making in

public participation according to 22.2% and just a good contributor according to 32.6%

while 15.7% were neutral but still 16.9% felt it was a poor contributor and according to

12.6% it was a very poor contributor. This had a mean of 3.9 and a standard deviation of

0.7. According to 14.9% of the respondent’s construction / completion of markets and trade

parks was a very good contributor and according to 28.2% it was just a good contributor

while 23.8% were neutral and still 16.7% felt it was a poor contributor and 16.4% felt it

was a very poor contributor. This had a mean of 3.9 and a standard deviation of 0.9. These

results are shown in Table 4.2.

32

Table 4.2: Socioeconomic Factors

Very Poor

contributo

r

Poor

contributo

r

Neutra

l

Good

Contributo

r

Very good

contributo

r Mean

Std

Dev.

Health and

community

awareness 13.9% 15.6% 13.9% 31.8% 24.8% 3.8 0.3

Education

projects 3.8% 12.6% 18.5% 34.0% 31.1% 4.2 0.7

Entrepreneurshi

p opportunities 12.5% 14.3% 18.2% 34.2% 20.8% 4.6 0.8

Women and

youth

employment

creation 13.3% 14.1% 25.6% 31.6% 15.4% 4.0 0.7

ATI/ veterinary

lab/ milk

processor plant

construction and

farm input

provision 27.4% 21.3% 17.1% 21.3% 12.9% 4.7 0.9

Water projects 11.8% 20.1% 13.7% 28.9% 25.5% 3.8 0.5

Housing 14.2% 17.1% 21.5% 27.5% 19.7% 4.6 0.4

Electrification

and ICT

connectivity 12.2% 10.0% 17.4% 38.7% 21.7% 4.1 0.6

Roads,

footbridges and

bridges 12.6% 16.9% 15.7% 32.6% 22.2% 3.9 0.7

Construction /

completion of

markets and

trade parks 16.4% 16.7% 23.8% 28.2% 14.9% 3.9 0.9

33

4.3.1 Correlation Between Socioeconomic Factors and Decision-Making

There was a significant positive correlation between decision making in women in public

participation and socioeconomic factors, r=0.213, p<.001. These results are shown in Table

4.3.

Table 4.3: Correlation Between Socioeconomic Factors and Decision-Making

Factor Decision Making

Socioeconomic Factors Pearson

Correlation .213**

Sig. (2-tailed) .001

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

4.3.2 Regression on Socioeconomic Factors and Decision-Making

This study sought to find out the effect of socioeconomic factors of women on decision-

making in public participation. A regression analysis was performed to examine this

influence, the dependent variable was decision making and the independent variable was

socioeconomic factors. As shown in Table 4.4, the model summary shows that R Square =

.045, this shows that socioeconomic factors, predicted 4.5% of decision making of women

in public participation.

Table 4.4: Regression on Socioeconomic Factors and Decision-Making

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .213a .045 .041 12.22749

a. Predictors: (Constant), Socioeconomic Factors

The ANOVA table illustrates how well the regression model predicts the dependent

variable. According to results shown in Table 4.5, socioeconomic factors, was significant

in predicting decision making in women, p<.001.

34

Table 4.5: ANOVA on Socioeconomic Factors and Decision-Making

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 1679.841 1 1679.841 11.236 .001b

Residual 35434.224 237 149.511

Total 37114.065 238

a. Dependent Variable: Decision Making

b. Predictors: (Constant), Socio-economic Factors

The regression coefficient for socioeconomic factors is .386, this shows that with 1 unit

increase in socioeconomic factors, decision making in women went up by .386 units. This

finding is shown in Table 4.6.

The regression equation derived from this analysis is:

y= a + b1x1 + e

y= women’s’ decision making;

a=constant;

b1 = socioeconomic factors;

e = error term

y= 3.064+ .386x1 + 0.115

Table 4.6: Coefficient on Socioeconomic Factors and Decision-Making

Model

Unstandardized

Coefficients

Standardized

Coefficients

T Sig. B Std. Error Beta

(Constant) 3.064 1.070 2.863 .005

Socioeconomic_F

actors .386 .115 .213 3.352 .001

a. Dependent Variable: Decision-Making

4.4 Effect of Women Economic Empowerment on Public Participation

This study examined several factors relating to women economic empowerment and their

effect on decision making among women in public participation. According to findings,

public administration/employment of civil servant was considered to have a very serious

effect among 17.4% of the respondents, 22.5% felt the effect was just serious, 16.1% were

neutral and 20.7% thought it had a not very serious effect while 23.3% felt the effect was

not serious at all. This had a mean of 4.1 and a standard deviation of 0.9. Distribution of

35

transformative projects in wards was considered to have very serious effect among 13.3%

and 31.6% felt it had a serious effect while 23.6% were neutral, 18.8% felt it the effect was

not very serious while 13.3% also felt the effect was not serious at all. This had a mean of

3.9 and a standard deviation of 0.8.

Further, delays in national funding to county governments had a very serious effect on

women decision making in public participation according to 19% of the respondents, while

32.3% felt it had a serious effect, still 23.3% were neutral and 16.4% said the effect was

not very serious and 9% though the effect was not serious at all. This had a mean of 3.8 and

a standard deviation of 0.1. Introduction of new projects had very serious effect according

to 8.7% of the respondents and 22.1% thought it had serious effect while 36.4% were

neutral, however 17.7% felt the effect was not very serious and 15.2% felt the effect was

not serious at all. This had a mean of 3.7 and a standard deviation of 0.3.

Many departments with similar or identical mandates duplicated each fiscal year had a

serious effect on women decision making in public participation, as per 13.0% of the

respondents and 21.1% felt this effect was serious while 31% were neutral and still 18.5%

thought that this effect was not very serious and 16.4% felt the effect was not serious at all.

This had a mean of 3.8 and a standard deviation of 0.3. Lastly, PFM calendar deadlines had

a very serious effect on women decision making in public participation, this is according

to 11.3% and 20.3% considered this effect to be just serious while 24.2% and yet 28.6%

said that this effect was not very serious and 15.6% held that this effect was not serious at

all. This had a mean of 4.1 and a standard deviation of 0.3. These findings are shown in

Table 4.7.

36

Table 4.7: Women Economic Empowerment

Factor

Not serious

at all

Not very

Serious

effects Neutral

Serious

effects

Very

Serious

effects Mean

Std Dev.

Public administration /

employment of civil servants 23.3% 20.7% 16.1% 22.5% 17.4% 4.1 0.9

Distribution of transformative

projects in wards 13.3% 18.8% 23.1% 31.6% 13.3% 3.9 0.8

DELAYS in national funding

to county governments 9.0% 16.4% 23.3% 32.3% 19.0% 3.8 0.1

Introduction of new projects 15.2% 17.7% 36.4% 22.1% 8.7% 3.7 0.3

Departments with

similar/identical mandates

duplicated each fiscal year 16.4% 18.5% 31.0% 21.1% 13.0% 3.8 0.3

PFM calendar deadlines 15.6% 28.6% 24.2% 20.3% 11.3% 4.1 0.4

4.4.1 Correlation between Women Economic Empowerment and Decision-Making

There was a significant positive correlation between decision making and women economic

empowerment, r=.146, p<0.024. These results are shown in Table 4.8.

Table 4.8: Correlation between Women Economic Empowerment and Decision-

Making

Decision-making

Economic_Empowerment Pearson

Correlation .146*

Sig. (2-tailed) .024

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

4.4.2 Regression on Women Economic Empowerment and Decision-Making

This study sought to find out the effect of women economic empowerment on decision-

making in public participation. A regression analysis was performed to examine this

influence, the dependent variable was decision making and the independent variable was

women economic empowerment. As shown in Table 4.9, the model summary shows that

37

R Square = .021, this shows that women economic empowerment, predicted 2.1% of

decision making of women in public participation.

Table 4.9: Regression on Women Economic Empowerment and Decision-Making

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .146a .021 .017 12.38023

Note. a. Predictors: (Constant), Economic_Empowerment

The ANOVA table illustrates how well the regression model predicts the dependent

variable. According to results shown in Table 4.10, socioeconomic factors, was significant

in predicting decision making in women, p<.024.

Table 4.10: ANOVA on Women Economic Empowerment and Decision-Making

Model Sum of Squares df Mean Square F Sig.

Regression 789.049 1 789.049 5.148 .024b

Residual 36325.016 237 153.270

Total 37114.065 238

a. Dependent Variable: Decision_Making

b. Predictors: (Constant), Economic_Empowerment

The regression coefficient for women economic empowerment is .167, this shows that with

1 unit increase in women economic empowerment, decision making in women went up by

.167 units. This finding is shown in Table 4.11.

The regression equation derived from this analysis is:

y= a + b1x1 + e

y= women’s’ decision making;

a=constant;

b1 = socioeconomic factors;

e = error term

y= 4.576 + .167x1 + 0.073

38

Table 4.11: Coefficient on Women Economic Empowerment and Decision-Making

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B

Std.

Error Beta

1 (Constant) 4.576 .895 5.114 .000

Economic_Empowerment .167 .073 .146 2.269 .024

a. Dependent Variable: Decision_Making

4.5 Effect of Inclusivity in Public Participation Hearings on Decision-Making

This study examined several factors relating to inclusivity in public participation hearing

and their effect on decision making among women in public participation. According to

findings, 36.6% respondents agreed and 24.3% strongly agreed that the executive does not

understand the needs of women in the county while 13.2% were neutral and still 17%

agreed and 8.9% strongly agreed. This had a mean of 3.7 and a standard deviation of 0.9.

Findings showed that 24.1% disagreed and 19.1% strongly disagreed that excluding

eligible female candidates negatively affects development while 20.4% were neutral and

still 24.1% agreed and 12.3% strongly agreed. This had a mean of 4.1 and a standard

deviation of 0.8.

Results showed that, 15.7% respondents strongly disagreed and 19.5% disagreed that

Barazas views were not considered during budgeting for their ward while 32.2% were

neutral and still 22.6% agreed and 10% strongly agreed. This had a mean of 4.5 and a

standard deviation of 0.4. Lastly, 34.6% respondents agreed and 15.8% strongly agreed that

there is poor coordination of Barazas in their ward but 17.6% disagreed and 13.6% strongly

disagreed while 18.4% were neutral. This had a mean of 4.2 and a standard deviation of

0.8. These results are shown in 4.12.

39

Table 4.12: Inclusivity in Public Participation Hearings

4.5.1 Correlation between Inclusivity in Public Participation Hearings and Decision

There was a significant positive correlation between decision making and women

inclusivity, r=.396, p<.000. These results are shown in Table 4.13.

Table 4.13: Correlation between Inclusivity in Public Participation Hearings and

Decision-making

Factor Decision_Making

Women_Inclusivity Pearson

Correlation .396**

Sig. (2-tailed) .000

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).

4.5.2 Regression between Inclusivity in Public Participation Hearings and Decision

This study sought to find out the effect of women inclusivity in public participation hearing

on decision making. As shown in Table 4.14, the model summary shows that R Square =

.157, this shows that women inclusivity in public participation hearing, predicted 15.7% of

decision making.

Factor

Strong

ly

disagr

ee

Disagre

e

Neutra

l Agree

Strongly

Agree Mean

Std

Dev.

The executive does not

understand the needs of women in

the county 24.3% 36.6% 13.2% 17.0% 8.9%

3.

7 0.9

Excluding eligible female candidates

negatively affects development 19.1% 24.1% 20.4% 24.1%

12.3

%

4.

1 0.8

Barazas views are not considered

during budgeting for our ward 15.7% 19.5% 32.2% 22.6%

10.0

%

4.

5 0.4

There is poor coordination of

Barazas in our ward 13.6% 17.6% 18.4% 34.6%

15.8

%

4.

2 0.8

40

Table 4.14: Model Summary on Inclusivity in Public Participation Hearings and

Decision

Model R R Square Adjusted R Square

Std. Error of the

Estimate

1 .396a .157 .153 11.49018

a. Predictors: (Constant), Women_Inclusivity

The ANOVA table illustrates how well the regression model predicts the dependent

variable. According to results shown in Table 4.15, inclusivity was significant in predicting

decision making in women, p<.000.

Table 4.15: ANOVA on Inclusivity in Public Participation Hearings and Decision

Model

Sum of

Squares df Mean Square F Sig.

1 Regression 5824.305 1 5824.305 44.115 .000b

Residual 31289.760 237 132.024

Total 37114.065 238

a. Dependent Variable: Decision_Making

b. Predictors: (Constant), Women_Inclusivity

The regression coefficient for Women inclusivity had a regression coefficient of .465, this

shows that with 1 unit increase in women inclusivity, decision making in women went up

by 0.465. These findings are shown in Table 4.16.

The regression equation derived from this analysis is:

y= a + b1x1 + b2x2 + b3x3 + e

y= women’s’ decision making;

a=constant;

b1 = socioeconomic factors;

b2 = economic empowerment;

b3 = women inclusivity

e = error term

y= .092+ .019x1 + 0.401x2 + .374x3 + 1.047

41

Table 4.16: Coefficients on Inclusivity in Public Participation Hearings and Decision

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) 3.209 .818 3.922 .000

Women_Inclusivity .465 .070 .396 6.642 .000

a. Dependent Variable: Decision_Making

4.7 Chapter Summary

This chapter summarized the data collected through questionnaires from respondents in

Tharaka Nithi county. The descriptive analysis section provided insight on the

representation of male and female respondents from each ward and covered background

information, socioeconomic and economic factors. Inclusivity, and decision – making

factors concluded this section, supported by data on the recommendation of residents who

were approached regarding the highlighted factors above. The inferential statistics section

provided regression analysis of the data. The final chapter provide summary, discussions,

conclusions and recommendations.

42

CHAPTER FIVE

5.0 DISCUSSION, CONCLUSION AND RECOMMENDATION

5.1 Introduction

This chapter presents a discussion of the findings presented in chapter four. It further

provides conclusions and recommendations for each objective as informed by the research

findings on specific objectives. The chapter first presents a summary of the study in the

following section.

5.2 Summary

The purpose of the study was to examine the effect of women representation in public

participation on decision-making. The study was constructed on three research questions

which include, what is the effect of women socioeconomic factors on decision – making at

public hearings? what is the effect of women economic empowerment on decision – making

at public hearings? How does women inclusion influence decision – making at public

hearings? This study used a mixed method research design including, action research and

exploratory design. The study population included women and men from Tharaka Nithi

County. This study used purposive sampling and random sampling technique to obtain

participants for the study. A total of 400 respondents were selected to participate in the

study. Questionnaire were used to collect data that was analyzed through descriptive and

inferential statistics.

The findings on the first research question showed that most of the respondents, 56.6% felt

that health and community awareness projects was a good contributor to women decision

making while 29.5% felt otherwise and only 13.9% were neutral. Again, most of the

respondents, 65.1% said that education projects were a good contributor to women decision

making but 16.4% were of the contrary opinion while 18.5% were neutral. Further, majority

of the respondents 41.6% thought that entrepreneurship opportunities, was a good

contributor to women decision making and 26.8% were negative while 34.2% remained

neutral. Additionally, 47% of the respondents held that women and youth employment

creation was a good contributor to women decision making, still 27.4% were opposed to

this notion and 25.6% were neutral. Results also showed that most of the respondents,

48.7% felt that ATI/veterinary, lab/milk processor plant construction and farm input

provision was a poor contributor to women decision making but 34.2% were of the contrary

opinion while 17.1% were neutral. According to 54.4% of the respondents, water project

43

was a good contributor to women decision making however 31.9% of the respondents felt

otherwise while 13.7% were neutral. In addition, 47.2% of the respondents felt that housing

was a good contributor to women decision making, however 31.3% were negative

while21.5% were neutral. Results also showed that majority of the respondents, 60.4% felt

that electrification and ICT connectivity was a good contributor to women decision making

but 22.2% were negative and 17.4% were neutral. Again, most of the respondents, 54.8%

thought that roads, footbridges and bridges were a good contributor of women decision

making even though 29.5% were negative and 15.7% were neutral. Most of the

respondents, 43.1% felt that respondent’s construction / completion of markets and trade

parks was a good contributor but 33.1% opposed this while 23.8% were neutral. According

to the correlation analysis, there was a significant positive correlation between decision

making in women in public participation and socioeconomic factors, r=0.213, p<.001. The

regression analysis showed that socioeconomic factors, predicted 4.5% of decision making

of women in public participation.

Findings on the second research question showed that most of the respondents, 44% felt

that public administration/employment of civil servant had a serious effect on women

decision making, still 39.9% felt it had no serious effect while 16.1% were neutral.

According to findings, 44.9% of the respondents thought distribution of transformative

projects in wards had a serious effect on women decision making while 32.1% felt

otherwise and 23.6% were neutral. Findings showed that majority of the respondents,

53.3% thought that delays in national funding to county governments had a serious effect

on women decision making in public participation, still 25.4% differed while 23.3% were

neutral. Again, results showed that 30.8% of the respondents felt introduction of new

projects had a serious effect on women decision making in public participation while 32.9%

were negative while 36.4% were neutral. In addition, results showed that 34.2% of the

respondents thought that identical mandates duplicated each fiscal year had a serious effect

on women decision making in public participation while 34.9% felt this effect was not

serious while 31% were neutral. Further, 44.2% of the respondents felt that PFM calendar

deadlines had a no serious effect on women decision making in public participation while

31.6% felt this had a serious effect while 24.2% were neutral. According to the correlation

analysis, there was a significant positive correlation between decision making and women

economic empowerment, r=.146, p<0.024. The regression analysis showed that women

44

economic empowerment, predicted 2.1% of decision making of women in public

participation.

Findings on the third research question showed that most of the respondents, 60.9%

disagreed that the executive does not understand the needs of women in the county, still

25.9% agreed and 13.2% were neutral. Results showed that 43.2% of the respondents

disagreed that excluding eligible female candidates negatively affects development but

36.4% disagreed while 20.4% were neutral. It was again showed that, 35.2% of the

respondents disagreed that Barazas views were not considered during budgeting for their

ward but 32.6% agreed to this while 32.2% were neutral. In addition, majority of the

respondents, 50.4% agreed that there is poor coordination of Barazas in their ward but

31.2% disagreed while18.4% were neutral. According to the correlation analysis there was

a significant positive correlation between decision making and women inclusivity, r=.396,

p<.000. Regression analysis showed that women inclusivity in public participation hearing,

predicted 15.7% of decision making.

5.3 Discussion

5.3.1 Effect of Socioeconomic Factors on Women Participation in Decision-Making in

Public.

Findings on the first research question showed that most of the respondents, 56.6% felt that

health and community awareness projects was a good contributor to women participation

in decision making. This is in line with the argument presented by WHO (2013) that healthy

women are in a better position to participate in society take joint action to promote their

own interests. Again, most of the respondents, 65.1% said that education projects were a

good contributor to women participation decision making. This in line with Bishaw (2014)

who established that as the level of education of women in rural areas increases, their

participation in political and economic events. Further, majority of the respondents 41.6%

thought that entrepreneurship opportunities, was a good contributor to women participation

in decision making. The findings are in agreement with Morshed and Haque (2015)

observation that women entrepreneurs have a more participation in politics and social

activities.

Additionally, 47% of the respondents held that women and youth employment creation was

a good contributor to women participation in decision making. Similarly, Raju (2015)

45

found out that women employment has a appositive influence on active participation in the

decision making process among women. This was an observation made by Pambè,

Gnoumou and Kaboré (2014) who noted that women that are paid for work are more likely

to participate in decision making as opposed to women who do not receive work pay.

Results also showed that most of the respondents, 48.7% felt that ATI/veterinary, lab/milk

processor plant construction and farm input provision was a poor contributor to women

participation in decision making. This contradict the findings of Diiro et al (2018) which

showed that rural development initiatives in Kenya that seek to improve agricultural

productivity and enhance food security and minimize poverty can attain greater effect

through incorporating women empowerment, which entails participation in decision

making. According to findings, majority of the respondents, 54.4% thought water project

was a good contributor to women’s decision-making, however. In line with the findings

here, Joshi and Fawcett (2001) argued that women have been represented in community

decision-making forums and grown more aware of health and hygiene aspects of water

management and participated in income generation activities as a result of investment of

time and resources on water projects.

In addition, majority of the respondents, 47.2% felt that housing was a good contributor to

women decision making. Results also showed that majority of the respondents, 60.4% felt

that electrification and ICT connectivity was a good contributor to women participation in

decision making. This observation corresponds to Nikulin (2017) findings that there is a

positive effect from ICT usage women workforce participation in developing countries. A

number of infrastructures were identified as a good contributor women participation in

decision making, 54.8% identified roads, footbridges and bridges while 43.1% identified

markets and trade parks as good contributors of women decision making. Mbogori (2014)

on the other hand identified a number of infrastructures that have an effect on women

participation, these include, mode of transport and road networks. Most of the respondents,

43.1% felt that construction / completion of markets and trade parks was a good contributor

to women participation in decision making. Moreover, findings showed that socioeconomic

factors had a significant relationship with women participation in decision making

(r=0.213, p<.001). The results demonstrated that socioeconomic factors, predicted 4.5% of

women participation in public decision making. This observation here is consistent with

Pambè, Gnoumou and Kaboré (2014) study results that found out a significant relationship

between socioeconomic and women decision making.

46

People often complain about the high amount of expenses related to improving their

educational levels and the amount of time consumed attending universities, secondary and

even primary schools. However, this is the singular simple approach to improving how

society operates. It aids in improving the decision-making capabilities of students,

including women. According to Banks and Banks, (2019), a divided society is a high risk

society with higher likelihood of inequality. The meritocracy rewards hard work and

initiatives of both male and female students succeed, based on more than their talents.

However, aspects beyond the control of women such as the quality of schools and education

influence their ability to contribute consistently for their households.

Higher investment directed to women to offer a larger number of options to study improves

the differences in social inequality. Time, money, and knowledge must be passed on to

ensure women spend more time learning better literacy skills and as professionals,

accordingly. Children whose parents attend tertiary institutions are more likely to devote

time to their own pursuit of higher education. Elements that increase the likelihood of

women in middle income and low-income levels is therefore considered a viable approach

to improving decision making in the long term in Tharaka Nithi county. Tracking women

and ensuring that they attend specific, economy-boosting courses is impacted positively by

the attitudes of students, who are at higher risk of spending less time in engaging in decision

making at government level.

Women are more likely to escalate issues to government officials if they attend more time

training on how to improve their capabilities. County Governments therefore require

national government funding for programs that focus on women in marginal rural areas to

attend learning institutions to mitigate the decision-making gap currently witnessed in the

counties such as Tharaka Nithi. Ultimately, societal biases are also reduced by ensuring

that patterns such as higher drop-out rates among vulnerable women are reduced and more

opportunities awarded to them. The average Kenyan citizen is more likely to spend time in

school with the hope that their effort will pay-off. However, with the high rate of

unemployment and dwindling economy, more must be done to ensure that societal skills

such as participating in governance are enhanced. Polices formulated in the future must

bear this consideration in order to enhance the future of the entire nation.

47

5.3.2 Effect of Women Economic Empowerment on Public Participation

Findings showed that most of the respondents, 44% felt that public

administration/employment of civil servant had a serious effect on women participation in

decision making. Consistent with findings here, Nasser (2018) argues that balanced total

employment between men and women is critical, still it is crucial to have women spread

across the various sectors of administrative governance and also fairly represented in every

levels of decision-making. According to findings, majority of the respondents, 44.9%

thought that distribution of transformative projects in wards had a serious effect on women

participation decision making. In line with this, Kongolo (2009) argues that women in rural

settlements will be able to participate in development like their counterpart in urban

settlements, if these women are introduced and guided in development.

Findings showed that majority of the respondents, 53.3% thought that delays in national

funding to county governments had a serious effect on women decision making in public

participation. In the same line Sow (2012) observed that decentralization bodies lack

financial resources to effectively implement gender equality policies in the back of under-

representation of women in key position of policy and program implementation. Again,

results showed that majority of the respondents, 36.4% were neutral on whether

introduction of new projects had a serious effect on women decision making in public

participation. These findings are in line with the observation made by Casey, Glennerster

and Miguel (2011) who could not establish a sustained effect of community development

projects on among other things decision making processes and participation of women in

local matters.

Further, majority of the respondents, 44.2% felt that PFM (public finance management)

calendar deadlines had a no serious effect on women decision making in public

participation. This seems to contradict the sentiment of Welham, Barnes-Robinson,

Mansour-Ille and Okhandiar (2018) who indicated that public finance management

processes influenced reducing gender inequalities. However, Welham, Barnes-Robinson,

Mansour-Ille and Okhandiar (2018) asserted that this is can be attained through making the

process of public finance management to be more aware of gender. According to Birchall

and Fontana (2015) gender insensitive budget could miss out on prospects of using public

finance to enhance the position women in the community. This could lead to the risk of

unconsciously reproducing and reinforcing systematic inequalities among women and men.

48

According to the correlation analysis, there was a significant positive correlation between

women economic empowerment and decision making of women in public participation,

r=.146, p<0.024. The regression analysis showed that women economic empowerment,

predicted 2.1% of decision making of women in public participation. Sow (2012) registered

mixed findings in a study to examine women political participation and economic

empowerment. Though he found evidence showing that poverty and economic insecurity

prevented women from political participation, the results in Uganda was contradicting what

was a common observation. In Uganda Sow (2012) noted that the progress made by women

in the economic domain did not provide them a more prominent position in political

decision making.

There are close ties between economic development and the level of education that

individuals attain. Widespread availability of the empowerment of all citizens and

particularly women is pegged on high quality public training in various aspects of economic

empowerment. A fairer distribution is pegged on individuals in public institutions attaining

training previously accessible to those in private institutions and psychological and political

empowerment thrives in an environment where women attain technical and other

certifications that enable them to attend public universities, access borrowing facilities in

banks and other financial institutions.

Finally, to combat gender discrimination, society must push women to benefit from the

manifest functions beyond their counties of origin and explore other locations in the country

that will enable them to learn about more opportunities for them to succeed. Furthermore,

national governments should encourage social integration which drives acknowledgement

and appreciation of cultures beyond those living within a region or country. Modernization

through technical and social training occurs once women are granted the opportunity to

explore, transforming their lives. According to Calhoun (2019), large scale social

integration contributes to stronger social foundations in communities. Kenya, with its

diverse cultures, stands to benefit from the economic empowerment of women through

encouraging their access to different parts of the world to improve their understanding and

mold the future workforce. According to Vos (2019), Credentialing individuals who attend

foreign institutions can also help the government identify proper remuneration for all and

contribute to social cohesion and prevent alienation.

49

5.3.3 Effect of Inclusivity in Public Participation Hearings on Women Decision-

Making in Public Participation

Most of the respondents, 60.9% disagreed that the executive does not understand the needs

of women in the county. According to the Beijing Declaration (1995) equality in decision-

making is fundamental to the development of women’s rights and that women’s equal

participation in decision-making is more than just a question of simple justice or

democracy, but also a need for women’s interests to be considered. Results showed that

43.2% of the respondents disagreed that excluding eligible female candidates negatively

affects development. According to other researcher findings by Hejase et al (2013) despite

the great intake of women in the workplace and enhancing number of women occupying

mid-level managerial positions, executive position at the top were elusive to women.

It was again showed that majority of the respondents, 35.2% disagreed that Barazas views

were not considered during budgeting for their ward but 32.6% agreed to this while 32.2%

were neutral. Contrary to findings here a Wacera (2016) in a study of the influence of

citizen participation in Nyandarua County found out that residents indicated that their views

were barely ever considered in the County. In addition, majority of the respondents, 50.4%

agreed that there is poor coordination of Barazas in their ward. This was the same scenario

observed by Wacera (2016) in Nyandarua County, residents of Nyandarua County were

dissatisfied with the way the public participation through such group as County Barazas

were carried out.

According to the correlation analysis there was a significant positive correlation between

women participation in decision making and women inclusivity, r=.396, p<.000.

Regression analysis showed that women inclusivity in public participation hearing,

predicted 15.7% of decision making. This result is in line with the argument of O’Neil and

Domingo (2015) who argued that critical drivers of women’s political influence include

among other more and inclusive politics. According to O’Neil and Domingo (2015) across

the globe women have become more influential over the decision that impact their lives

which is a result of the more equitable policies advocated by feminists and gender

advocates.

Class matters in the lives of Kenyans and at the very beginning of life, each individual

experiences class socialization, which impacts the lives of women experience political

contexts and pass on knowledge on aspects such as obedience and better social cleavage,

50

to their children, according to Grasso, Farrall, Gray, Hay and Jennings (2019) who study

the trickle-down effect of political socialization. For individuals who learn this lesson early,

the chances that they select locations with better funding opportunities for education,

health, entrepreneurship, and public amenities is higher. Inclusivity implies that women

can attend institutions and places of work with advanced technology, which influences

employment and education of future generations.

The movement to enforce inclusion counters the establishment of gaps in healthcare,

income, money education, and occupational disparities. Different groups of people share

various advantages and disadvantages in their counties of origin. The socioeconomic status

of someone with better access to these amenities is obviously better than that of an

individual who has not enjoyed social mobility, as shown by the results of this study. Social

influence theories assert that the stereotyping associated with the roles of women in the

society can lead to discrimination of those who step away from conventional roles while

prejudiced views propagate the attitude of the masses, discrimination affects behavior of

people in society. Inclusivity impacts the association placed with individuals, led by the

implicit attitudes that communities bear.

Why is inclusivity important? According to Weller (2017), inclusivity ensures that society

remains cohesive, especially through religion and governance. County governments and

national governments overall influence the narrative followed by the population and can

change the generalizations made regarding development. For example, they can influence

the just world phenomenon stating that people get what they deserve. If governments in

multicultural settings focus on changing the behavior and attitudes of the society, positive

changes are more likely to occur. Visibly less conflict, increased cooperation, and better

management of public resources are witnessed in inclusive societies. Equity is one of the

major considerations that women seek when searching for job opportunities in the public

sector. Furthermore, Edge and Harvey (2017) state that inclusivity is an aspect of social

justice that protects women from individualistic behavior. In many developing nations, law

and religion go hand in hand, molding society. County governments can utilize these two

aspects of contemporary society to address issues arising specific to the needs of women.

Encouraging women to participate in unconventional roles plays a significant role in global

efforts to make governance participatory.

51

5.4 Conclusion

5.4.1 Effect of Socioeconomic Factors on Women Decision Making in Public

Participation

This study concludes that socioeconomic factors, influence women participation in public

decision making. The socioeconomic factors that affect women decision making, health

and education community awareness projects, entrepreneurship opportunities, women

employment, water project, housing, electrification and ICT connectivity. Infrastructure

including roads, footbridges and bridges as well as markets and trade parks also contribute

to women participation in decision making in the public sphere.

5.4.2 Effect of Women Economic Empowerment on Women Decision Making in

Public Participation

This study concludes that women economic empowerment significantly contributes to

women decision making in public participation. Women public participation in decision

making is contributed by such economic factors as, employment of women in the public

services and distribution of transformative projects in wards. The delays caused by the

county government funding from the national government negatively affects women

decision making in public participation.

5.4.3 Effect of Inclusivity in Public Participation Hearings on Women Decision-

Making in Public Participation

This study concludes that women inclusivity significantly affected thier decision making

in public participation. Inclusivity provides women with an opportunity to be invloded

public matters that affect them such as, politics, recruitment to the public services and

economic opportunities that will empoer them.

5.5 Recommendation

5.5.1 Recommendation for Improvement

5.5.1.1 Effect of Socioeconomic Factors on Women Decision Making in Public

Participation

This study proposes that the socioeconomic factors that affect women such as housing,

education, health and employment be given priority in local government. This will enable

52

women to come out into the public and be involved in public issues some of which affect

them directly. Women are encouraged to come out strong and help in the improvement of

socioeconomic status with an aim of empowering their own in taking up position public

participation.

5.5.1.2 Effect of Women Economic Empowerment on Women Decision Making in

Public Participation

This study recommends that the new county government should uplift the economic

conditions of women at the grassroot. They should support women in their economic

ventures that would empower them and drive them into public participation. Women should

venture out in business opportunities and seek public office that would make them stronger

to engage in public matters.

5.5.1.3 Effect of Inclusivity in Public Participation Hearings on Women Decision-

Making in Public Participation

This study proposes for stronger policies in the government to include more women in

public activities. Women should be supported with policies that guarantees thier

participation in the public. This should be especially on matter that affect them directly.

There should reseved posts in the public sector for women while the private sectro should

also be compelled to ensure a gender balance in thier workforce.

5.5.2 Recommendation for Further Studies

This study was carried out to examine factros that affect women decision making in public

participation. The study proposes further research to be carried out on factros that

encourage women decision making in public participation. this study was carried out in

Tharaka Nithi County, a similar study can carried out in otehr counties to relate with the

findings here.

53

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the-public-finance-management-act-2012

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61

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62

APPENDICES

Appendix I: Introductory letter

63

Appendix II: Questionnaire

I Rachel Wanjiru Kimani, (Student ID NO 622552) an MBA student at United States

International University-Africa, am conducting a study on the effect of women

representation in public participation on decision-making in Kenya. You have been selected

as a stakeholder in this area to respond to a few questions to enable me gather necessary

data to inform the findings and conclusions of my research proposal. The information you

give will be aggregated and solely used for the intended purpose and the interview will take

not more than 15 minutes. All feedback will be treated with the highest level of

confidentiality.

SECTION A: BACKGROUND INFORMATION

1. Gender: Male _______Female _______

2. Age: ___________

3. Highest level of academic qualification: Primary _____Secondary _____Tertiary

_____

4. Employed: Yes: _____________ No: ___________________

5. Occupation __________________________________

6. Religion __________________________________________

7. Ward _____________________________________________

8. Do you know what public participation is? Yes _______ No _____

9. Do you have access to healthcare? Yes _______ No _____

10. Have you ever engaged in any form of public participation? Yes _______ No _____

11. Are you a member of any community group or political group? Yes _______ No

_____

12. If yes, are you an official? Yes _______ No _____

64

SECTION B: SOCIOECONOMIC FACTORS

13. On a Likert scale provided below, projects that are socioeconomic in nature are

highlighted. Please rate your opinion on how the projects contribute to use of

development funds:

Item Very Poor

contributor

Poor

contributor

Neutral Good

Contributor

Very good

contributor

Health and

community

awareness

Education

projects

Entrepreneurship

opportunities

Women and youth

employment

creation

ATI/ veterinary

lab/ milk

processor plant

construction and

farm input

provision

Water projects

Housing

Electrification

and ICT

connectivity

Roads,

footbridges and

bridges

65

SECTION C: ECONOMIC EMPOWERMENT

14. How do the following economic empowerment issues affect the public sector

spending on development expenditure? Please rate your opinion:

Item Not serious

at all

Not very

Serious

effects

Neutral Serious

effects

Very

Serious

effects

Public administration /

employment of civil servants

Distribution of

transformative projects in

wards

Delays in national funding to

county governments

Introduction of new projects

Many departments with

similar or identical mandates

duplicated each fiscal year

PFM calendar deadlines

Others (specify)

SECTION D: INCLUSIVITY

15. Please rate your opinion on how the following inclusivity issues impact county

development:

Construction /

completion of

markets and trade

parks

66

Item Strongly

disagree

Disagree Neutral Agree Strongly

agree

The executive does not

understand the needs of

women in the county

Excluding eligible female

candidates negatively affects

development

Barazas views are not

considered during budgeting

for our ward

There is poor coordination of

barazas in our ward

Others (specify)

SECTION E: DECISION MAKING

16. Do you agree/disagree that the following decisions improve the local county

economy?

Item Strongly

disagree

Disagree Neutral Agree Strongly

agree

Timely payment to

contractors who have

completed project work

Awarding more projects to

younger female contractors

Women always attending

public participation as

formality

Trusting planners to make the

right project decisions

67

Sharing project suggestions to

economic planners

Others (specify)

SECTION F: GENERAL RECOMMENDATIONS

17. Is the county government doing enough to increase development expenditure in

sectors directly affecting the lives of women?

Yes ______ Why?

____________________________________________________________

__________________________________________________________________

________

No _______ Why?

__________________________________________________________

__________________________________________________________________

________

18. In your view what should be done to increase women’s participation in decision-

making on spending on development expenditures?

__________________________________________________________________

__________________________________________________________________

19. What challenges & solutions are experienced by women who participate in public

hearings?

Challenges Solutions

Thank you for your time.

68

Appendix III: Research Permit

69

Appendix IV: Attendees

CFSP PUBLIC PARTICIPATION FY 2018-19 AT KARINGANI,

IGAMBANG’OMBE & MAGUMONI WARDS

NAME GEN

DER WARD

PHONE

NUMBER LOCATION

1 David Gitonga M Karingani 718220930 Kiang'ondu

2 Mercy Muthoni Kathia F Karingani 715021402 Karingani

3 Akida Rajab F Karingani 726501605 Karingani

4 Cyrus Kinyua M Karingani 726496129 Karingani

5 Daniel Kimwea M Karingani 792539332 Kiang'ondu

6 Dorothy Wanja F Karingani 721572729 Mugwe

7 Susan Murugi F Karingani 728257382 Karingani

8 Pierra Wanja F Karingani 720634071 Karingani

9 Ephantus Muriithi M Karingani 726707257 Karingani

10 Rosalid Wanja F Karingani 717638041 Karingani

11 Caroline Gakii F Karingani 718825694 Kibumbu

12 Kellen Gatugi F Karingani 724550110 Mugwe

13 Caroline Kanjiru F Karingani 710438099 Kiang'ondu

14 Godfrey Mawira M Karingani 706809660 Mucwa

15 Amram Muthee M Karingani 707322580 Township

16 Patrick Micheni M Karingani 726393970 Township

17 Francis Muchangi M Karingani 708597375 Kiang'ondu

18 Linus Kirimi M Karingani 721446612 Township

19 Mercy Murugi F Karingani 708597375 Township

20 Modester Kambura F Karingani 712806252 Township

21 Mary Kaari F Karingani 723727928 Township

22 Purity Muthoni F Karingani 727095954 Township

23 Joy Kaari F Karingani 713825100 Township

24 James Kamau M Karingani 798564730 Township

25 Peter Mwenda M Karingani 716966596 Township

26 Stella Kaguthi F Karingani 724436422 Township

27 Caroline Wanja F Karingani 721929600 Township

28 Jedidah Murage F Karingani 721639154 Township

29 Gitonga Ththi M Mugwe 712594611 Muiru

30 James Njabuba M Mugwe 733644142 Gitareni

31 Japhet Kimoni M Mugwe 721813295 Nkuthika

32 David Kimathi M Mugwe 727037033 Gitareni

33 Harriet Kaburu F Mugwe 722172926 Gitareni

34 Kariuki Muthoni F Mugwe 703785943 Mugwe

35 Roda Muthoni F Mugwe 729245063 Muiru

36 Edita Muthoni F Mugwe 714753324 Muiru

37 Neitus Gaceri F Mugwe 716847259 Gitareni

38 Agnes Karimi F Mugwe 795804776 Gitareni

39 Edward Mutwiri M Mugwe 713567033 Muiru

70

40 Leonard Micheni M Mugwe 720629698 Muiru

41 Mary Muthoni F Mugwe 713821281 Muiru

42 Morris Mwiti M Mugwe 727849123 Muiru

43 Annjoy Muthoni M Mugwe 718223510 Muiru

44 Ruth Gacheri F Mugwe 720390981 Muiru

45 Esther Karegi F Mugwe 710148008 Muiru

46 Stanley Gitonga M Mugwe 700644885 Mugwe

47 Bedford Nyaga M Mugwe 723404151 Muiru

48 Alpha Njeru M Mugwe 711111390 Muiru

49 Aileen Kainyu F Mugwe 728700136 Mugwe

50 Wallace Gitari M Mugwe 727629745 Mugwe

51 Dorcas Cirindi F Mugwe 723897826 Gitareni

52 Desderie Mbaka F Mugwe 721860321 Muiru

53 Pascawale Gitonga M Mugwe 710180650 Muiru

54 James Nyaga M Mugwe 728707450 Muiru

55 Dianah Kainyu F Mugwe 710449751 Mugwe

56 Dority Aliphan F Mugwe 708526777 Muiru

57 Alex Kinyua M Mugwe 713836496 Mugwe

58 Robert Mugambi M Mugwe 723562790 Muiru

59 Elosy Kageni F Mugwe 707598863 Muiru

60 Idah Karimi F Mugwe 716207356 Gitareni

61 Edith Kagendo F Mugwe 722103870 Gitareni

62 Judith Kirimi F Mugwe 724305350 Mugwe

63 Mutegi Titus M Mugwe 728493271 Muiru

64 Ellyjoy Kagendo F Mugwe 724009993 Gitareni

65 Faith Ciangai F Mugwe Gitareni

66 Mercy Kawira F Mugwe 714108084 Mugwe

67 Medlin Karegi M Mugwe 728142620 Muiru

68 Joyce Kathoni F Mugwe 716291480 Mugwe

69 Kamomi Kinyua M Mugwe 712750668 Muiru

70 Milea Kagendo F Mugwe 728336056 Mugwe

71 Mary Cianjira F Mugwe 726337121 Muiru

72 Eunice Kabubu F Mugwe 700321727 Mugwe

73 Lydicy Muthoni F Mugwe 729546376 Gitareni

74 Violet Rugendo F Mugwe 710321631 Gitareni

75 Dilsta Ciambaka F Mugwe 720266283 Mugwe

76 Charles Nderi M Magumoni 720266283 Kabuboni

77 Linus Kamau M Magumoni 710354646 Thuita

78 Anthony Njagi M Magumoni 711526873 Thuita

79 Edward Mutembei M Magumoni 725648719 Magumoni

80 Basilia Gitari M Magumoni 714146688 Thuita

81 Elisius Njoka M Magumoni 7282284198 Thuita

82 Patrick Mbuba M Magumoni 718315496 Thuita

83 Harrison Mwenda M Magumoni 723100751 Magumoni

84 Mary Njeri F Magumoni 726581110 Mukuuni

85 Denis Munene M Magumoni 759968735 Mukuuni

71

86 Morris Mwenda M Magumoni 759968735 Mukuuni

87 Martin Ireri M Magumoni 702825791 Mukuuni

88 Esther Njagi F Magumoni 727732432 Magumoni

89 Aileen Nyaga F Magumoni 726816714 Kathatwa

90 Patrick Mwiti M Magumoni 726586061 Thuita

91 Henry Kinyua M Magumoni 710267664 Thuita

92 James Mutwiri M Magumoni 723079239 Rubate

93 Mwenda MC M Magumoni 724041767 Thuita

94 Gregory Mputhia M Mariani 708579579 Karingani

95 Gitonga Mwiti M Mariani 725650470 Karingani

96 Stanley Kaburu M Mariani 712368440 Karingani

97 Christine Makena F Mariani 728825113 Mariani

98 Jack Kiboro M Mariani 711491702 Mariani

99 Frederick Gitonga M Mariani 746591922 Kithangani

100 George Mwenda M Mariani 796712312 Kithangani

101 Labat Muriuki M Mariani 729244481 Kithangani

102 Vindesio Ikingi M Mariani 714673060 Kithangani

103 ignatius Kariuki M Mariani 706192930 Kithangani

104 Coreen Kafuira F Mariani 705889814 Mariani

105 Janis Gatwiri F Mariani 716014557 Mariani

106 Dorycate Gatwiri F Mariani 700858858 Karingani

107 Rolena Kainyu F Mariani 717088291 Mariani

108 Rosemary Muthoni F Mariani 798072907 Mariani

109 Lukas mugendi M Mariani 728990120 Mariani

110 Frederick Mutegi M Mariani 719521731 Mariani

111 Taratisio Mabaka M Mariani N/A Mariani

112 David Magambo M Mariani 723835274 Ngumbo

113 Ephantus Mbaka M Mariani 729496030 Mariani

114 Patrick Bauri M Mariani 727117807 Mariani

115 Jerina Kaari F Mariani 707226883 Mariani

116 Simon Nthiga M kajuki 720884877 Igambang`ombe

117 David Gitonga M kajuki 726446001 Igambang`ombe

118 Benson Njeru M kajuki 748875610 Igambang`ombe

119 Florence Karithi F kajuki 726976271 Igambang`ombe

120 Charity Kananu F kajuki 703405908 Igambang`ombe

121 Doreen Kawira F Kamarandi 742702558 Igambang`ombe

122 Lucy Kariungi F Kajuki 740144941 Igambang`ombe

123 Janet kangagi F Kajuki 723781033 Igambang`ombe

124 Peter Mutwiri M Kajuki Igambang`ombe

125 Fredrick Kinyatta M Kajuki 708056360 Igambang`ombe

126 Christine M.Muthengi F Kajuki 790212514 Igambang`ombe

127 Hellen Kawira F Kajuki 791344139 Igambang`ombe

128 Vyeterina Kawira F Kajuki Igambang`ombe

129 Muthengi Mutani M Kajuki 715633343 Igambang`ombe

130 Peter Kirugutu M Kajuki Igambang`ombe

131 Jadiel Mikabete M Makanyanga 791194286 Igambang`ombe

72

132 Mukwanyaga M Kajuki Igambang`ombe

133 Caro Ciakuthii F Kajuki 792798282 Igambang`ombe

134 Francis Simba M Kajuki 727814851 Igambang`ombe

135 Michael Munyi M Kajuki 792700834 Igambang`ombe

136 Bonface Kavuitu M Kamwimbi 713041930 Igambang`ombe

137 Regina Njoki F Itugururu 724408370 Igambang`ombe

138 Newton Mwiti M Mutino 714894630 Igambang`ombe

139 Joseph Njeru M Kajuki 727893712 Igambang`ombe

140 Peter M Kajuki 2769078 Igambang`ombe

141 Peter Kienge M Kajuki 711690503 Igambang`ombe

142 Rutere Kanampiu M Kajuki Igambang`ombe

143 Hellen Karugi F Kajuki Igambang`ombe

144 Njoka Mutiria M Kajuki Igambang`ombe

145 Gilbert Kabunjia M kajuki 702687021 Igambang`ombe

146 Raphael Murithi M kajuki 710142094 Igambang`ombe

147 Luka Njeru M Kamutiria 701034875 Igambang`ombe

148 Josphat Kithome M Kamutiria 701698298 Igambang`ombe

149 Protas Kambuthu M kajuki 708348482 Igambang`ombe

150 Veronica Mwende F Kamutiria 751865155 Igambang`ombe

151 David Gitonga M KiKora 713668585 Igambang`ombe

152 Kennedy Mwiti Mbaka M Mutino 723880960 Igambang`ombe

153 Denis Mugambi M Kamaindi Igambang`ombe

154 Mitambo Muguika M kajuki Igambang`ombe

155 Babliel Kiania M Kajuki 5088205 Igambang`ombe

73

Appendix V: 2018-19 Budget Calendar

ACTIVITY RESPONS

IBILITY

DEADLINE

1. Prepare and issue budget circular with guidelines CEC

Member for

Finance

August 30th 2018

1.1 One day sensitization workshop September 2018

2. Sector Woking Groups County

Treasury

2.1 Launch and first meeting for SWGs and

sensitization on SDGs

October 2018

2.2 Second meeting for SWGs

Submission of projects and programmes to be

implemented for FY 2019/20

14th December

2018

2.3 Third meeting for SWGs March 2019

3. County Annual Progress Report County

Treasury

(Economic

Planning

Department

)

3.1 Draft CAPR 15th September

2018

3.2 Validation of the CAPR 15th – 20th Sept

2018

3.3 Submission to CEC for Approval 30th September

2018

3.4 Submission to CA for Approval 21st October 2018

4. Monitoring and Evaluation County

Treasury

(Economic

Planning

4.1 M&E field work September 2018

& August 2019

74

4.2 Annual M&E week Department

)

2nd week

November 2018

5. Statistical abstract County

Treasury

(Economic

Planning

Department

5.1 Draft Oct18

5.2 Launch Nov18

6. Development of ADPs for FY 2019/20 and

2020/21

County

Treasury

(Economic

Planning

Department

)

6.1. Draft ADP FY 2019/20 23rd August 2018

6.2 Submission of ADP FY 2019/20 to CEC 27th August 2018

6.3. Submission of ADP FY 2019/20 to County

Assembly

30th August 2018

6.4. Report of ADP from County Assembly

6.5. Consolidation of CA recommendations to

Final ADP

6.6. Approval of ADP by County Assembly

6.7. Meeting with TWGs for ADP FY 2020/21 30th May 2019

6.8. First draft ADP FY 2020/21 15th August 2019

6.9. Validation ADP FY 2020/21 15th – 20th August

2019

6.10. CEC Approval ADP FY 2020/21 20th August 2019

6.11. Submission ADP FY 2020/21 to County

Assembly

30th August 2019

75

7. Development of County Budget Review and

Outlook Paper (CBROP) 2018

County

Treasury

(Budget

Unit)

7.1. Estimation of Resource Envelope 10th Sep 2018

7.2. Determination of policy priorities “

7.3. Preliminary resource allocation to Sectors “

7.4. Draft County Budget Review and Outlook

Paper

16th Sep 2018

7.5. Validation 15th 20th

September 2018

7.6. Submission and approval of CBROP by

CEC

30th September

2018

7.7. Submission of approved CBROP to County

Assembly

21st October 2018

7.8. Drafting CBROP 2019 30th August 2019

8. Preparation of Budget proposals for the MTEF Department

s

8.1. First retreat to draft Sector Reports

(Programmes and projects submitted)

SWGs 20th Dec 2018

8.2. Public Sector Hearings County

Treasury

30th January 2019

8.3. Review and Incorporation of stakeholder

inputs in Sector proposals

SWGs 30th March 2019

8.4 Submission of Sector Reports to Treasury Sector

Chairperso

ns

5th April 2019

76

8.5. Consultative meeting with CECs/COs on

budget proposals

County

Treasury

15th April 2019

9. Draft County Fiscal Strategy Paper (CFSP) 2019

9.1. Draft CFSP County

Treasury

30th Jan 2019

9.2. Draft Debt Management Strategy (DMS) Budget

Unit

“

9.3. Validation Budget

Unit

15th - 20th

February 2019

9.4. Submission of CFSP and DMS to CEC for

approval

County

Treasury

20th February

2019

9.5. Submission of CFSP & DMS to County

Assembly for approval

County

Assembly

28th February

2019

10. Preparation and approval of Final Departmental Budgets

10.1. Develop and issue final guidelines on

preparation of 2019/20 MTEF Budget

County

Treasury

January, 2019

10.2. Submission of Draft Revenue Raising

Measures (Finance Bill) to County

Treasury

Line

department

s

30th March, 2019

10.3. Submission of Budget proposals to

County Treasury (First draft)

Revenue

Department

5th April, 2019

10.4. Consolidation of the Draft Budget

Estimates (final draft)

County

Treasury

15th April, 2019

10.5. Submission of Draft Budget Estimates to

CEC

County

Treasury

20th April, 2019

77

10.6. Submission of Draft Budget Estimates to

County Assembly

County

Treasury

30th April, 2019

10.7. Submission of Final Revenue Raising

Measures (Finance Bill) to County

Treasury

Revenue

Department

30th April,2019

10.8. Review of Draft Budget Estimates by

County Assembly

County

Assembly

15th June, 2019

10.9. Report on Draft Budget Estimates from

County Assembly

County

Assembly

15th June, 2019

10.10. Consolidation of the Final Budget

Estimates

County

Treasury

15th June, 2019

10.11. Approval of Appropriation Bill by

County Assembly

County

Assembly

30th April, 2019

10.12. Approval of Vote on Account by

County Assembly

County

Assembly

30th April, 2019

11. Public participation County

Treasury

(Economic

Planning

Department

)

31st January

2019

12. Development committees (ward level)

12.1. 1st meeting County

Treasury

30th October 2018

12.2. 2nd meeting 1st week February

2019

78

13. Budget Statement CECM

Finance

19th June, 2019

14. Appropriation Bill passed County

Assembly

30th June, 2019

79

Appendix VI: Map of Tharaka Nithi County

Figure 1: Map of Tharaka Nithi County: source, 2018-2022 CIDP

80

Appendix VII: Population Projections as per the wards

Constituency/Ward 2009 Census Projected population 2018-2022

Area

Population Density

(Km2) 2018 2019 2020 2021 2022

Tharaka 1,549.5 130098 83 152757 155506 158306 161155 164056

Gatunga 734 25703 40 30180 30723 31276 31839 32412

Chiakaringa 374.7 34679 114 40719 41452 42198 42958 43731

Mukothima 109.8 24273 125 28501 29014 29536 30067 30609

Nkondi 104 15574 150 18286 18616 18951 19292 19639

Marimanti 227 29867 100 35069 35700 36343 36997 37663

C/Igambang'ombe 624 128107 205 150419 153127 155883 158689 161545

Igambang'ombe 211 30160 143 35413 36050 36699 37360 38032

Karingani 29 23141 798 27171 27660 28158 28665 29181

81

Mugwe 44 24185 547 28397 28908 29429 29958 30498

Magumoni 64 36498 569 42855 43626 44411 45211 46025

Mariani 97 14123 146 16583 16881 17185 17494 17809

Mt. Kenya Forest 179 - - - - - - -

Maara 465.3 107125 230 125783 128047 130352 132698 135086

Mitheru 33 15309 464 17975 18299 18628 18964 19305

Mwimbi 104.3 22935 218 26930 27414 27908 28410 28921

Muthambi 50 19373 380 22747 23157 23573 23998 24430

Ganga 37 17514 473 20564 20935 21311 21695 22085

Chogoria 57 31967 561 37535 38210 38898 39598 40311

Mt.Kenya Forest 184 27 0 32 32 33 33 34

Total 2638.8 623533 137 428959 436680 444540 452542 460688

Source: KNBS, Population and Housing Census, 2009 (take to the appendices