Diversity Policies 2006

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Best Practices or Best Guesses? Assessing the Efficacy of Corporate Affirmative Action andDiversity PoliciesAuthor(s): Alexandra Kalev, Erin Kelly, Frank DobbinSource: American Sociological Review, Vol. 71, No. 4 (Aug., 2006), pp. 589-617Published by: American Sociological AssociationStable URL: http://www.jstor.org/stable/30039011

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Best Practices or Best Guesses?

Assessing the Efficacyof Corporate

Affirmative Action and Diversity Policies

Alexandra Kalev

University of California, Berkeley

Frank Dobbin

Harvard University

Erin Kelly

University of Minnesota

Employers have experimented with three broad approaches to promoting diversity. Some

programs are designed to establish organizational responsibilityfor diversity, others to

moderate managerial bias through training and feedback, and still others to reduce the

social isolation of women and minority workers. These approaches find support in

academic theories of how organizations achieve goals, how stereotyping shapes hiring

and promotion, and how networks influence careers. This is thefirst systematic analysis

of their efficacy. The analyses rely on federal data describing the workforces of 708

private sector establishments rom 1971 to 2002, coupled with survey data on their

employmentpractices. Efforts to moderate managerial bias through diversity training

and diversity evaluations are least effective at increasing the share of white women,

black women, and black men in management. Efforts to attack social isolation through

mentoring and networking show modest effects. Efforts to establish responsibilityfor

diversity lead to the broadest increases in managerial diversity. Moreover, organizations

that establish responsibility see better effectsfrom diversity training and evaluations,

networking, and mentoring. Employers subject to federal affirmative action edicts, who

typically assign responsibilityfor compliance to a manager, also see stronger effects

from some programs. This work lays thefoundation for an institutional theory of the

remediation of workplace inequality.

Lists of best practices in diversity man-

agement have proliferated recently.

Everyone seems to have a list, from the Equal

Employment Opportunity Commission (1998)

Direct correspondence o AlexandraKalev, RWJ

Scholars Program, University of California, 140

Warren Hall, MC7360, Berkeley, CA 94720

([email protected]).The authors thank Ronald

Edwards and Bliss Cartwright of the Equal

EmploymentOpportunityCommission for sharing

their data and expertise;Nicole Esparzaand Leslie

Hinkson or help with datacollection;KevinDobbin,

JohnDonohue, LaurenEdelman,JoshuaGuetzkow,

Heather Haveman, Jerry A. Jacobs, Seema

to the Presidential Glass Ceiling Commission

(1995), the women's business advocacy group

Catalyst (1998), and the Society for Human

Resources Management (2004). These lists are

Jayachandran, awrence Katz, JordanMatsudaira,

John Meyer, TrondPeterson, Daniel Schrage, Paul

Segal, Robin Stryker, Donald Tomaskovic-Devey,

Bruce Western,ChrisWinship,and four anonymous

reviewersfor suggestions; and Randi Ellingboe for

technical and editorial assistance. Supported by

National Science Foundation grant 0336642 and

Russell Sage Foundationgrant 87-02-03 and par-

tiallysupported y the RobertWoodJohnsonScholars

in Health Policy ResearchProgram.

AMERICANOCIOLOGICALEVIEW,006, VOL. 1 (August:589-617)


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590 AMERICANSOCIOLOGICALREVIEW

loosely based on academic heories hatpoint to

causes of workplace inequality ranging from

unwitting bias (Lemm and Banaji 1999) to

dependence on networks for hiring and pro-

motion (Reskin and McBrier 2000). Whereas

there has been a great deal of researchon the

sourcesof inequality, herehas been little on the

efficacy of differentprograms or countering t.

At best, best practices are best guesses. We

know a lot about the disease of workplace

inequality,but not much aboutthe cure.

We examine the effects of seven common

diversity programs-affirmative action plans,

diversity committees and taskforces, diversity

managers,diversity training,diversity evalua-

tions for managers,networkingprograms,and

mentoringprograms-on the representation f

white men, white women, black women, and

black men in the managementranksof private

sector firms. Each of these programsmay well

increase diversity.To date, therehas been little

evidence one way or the other.This is surpris-

ing given the popularity and cost of the pro-

grams. Ourcontribution s to bringto bearrich

new data, o theoretically istinguish hree ypes

of diversityprograms,and to show that organi-

zational structures llocatingresponsibility or

changemaybe moreeffective hanprograms ar-

geting either managerialbias or the social iso-

lation of disadvantaged roups.

Previous empirical studies of antidiscrimi-

nation and diversityprogramshave been limit-

ed by data constraints. Economists first

comparedemployers who are subject to affir-

mative action requirementswith those who are

not (Ashenfelterand Heckman1976; Heckman

and Wolpin 1976; Leonard 1984). They lacked

data on employer programs. Sociologists and

economistsstudyingemployerprograms xam-

ine data at one or two points in time (but see

Baron,Mittman, ndNewman 1991), analyzing

the effects of some programswithout account-

ing for others.These studies ndicate hat some

programsmay be effective,buttheir indingsare

inconsistent (Baron et al. 1991; Edelman and

Petterson 1999; Holzer and Neumark 2000;

Konrad and Linnehan 1995; Leonard 1990;

Naff and Kellough 2003). Gender and racial

segregationhas declined remarkably ince the

1970s, when employers first adopted antidis-

crimination programs (Jacobs 1989a; King

1992;Tomaskovic-Devey t al. 2006), but there

is no hardevidence thatthese programsplayed

a role.

We obtained he federal establishment-level

data that economists have used (i.e., the annu-

al EEO-1 reports hat privatesector establish-

ments submit to the Equal Employment

OpportunityCommission [EEOC]). We then

surveyed sampleof theseestablishments n the

history of their personnel and diversity pro-

gramsso thatwe could analyzeprogram ffects

on diversity.

A strengthof the EEO-1 reports s that they

detail annual employment by race, ethnicity,

and gender n all mediumand largeprivate ec-

tor workplaces.A limitation s that they cover

only nine broad ob categories, collapsing into

management ll jobs above that of first-line

supervisor Baronand Bielby 1985; Smith and

Welch 1984). We know frompreviousresearch

thatwomen andAfricanAmericansare crowd-

ed in the lowest ranksof management.Even as

women moved into management n the 1970s

and 1980s, womenmanagers ontinued o trail

their male counterparts n both earnings and

authority Jacobs 1992). Thus our analyses

indicatewhich diversityprogramshelp women

and African Americans move at least into the

bottom ranksof managementand, mportantly,

which do not. They cannot tell us whetherany

of these practiceshelp women andminorities o

move into the executive ranks.

We find a clearpattern n the data.Structures

establishing responsibility (affirmative action

plans, diversitycommittees,and diversitystaff

positions) are followed by significant increas-

es in managerialdiversity.Programs hattarget

managerial tereotyping hrougheducationand

feedback(diversity rainingand diversityeval-

uations) are not followed by increases n diver-

sity. Programs that address social isolation

among women andminorities networkingand

mentoringprograms)are followed by modest

changes. The effects of these initiatives vary

across groups, with white women benefiting

most, followed by black women. Black men

benefit least. We also find that responsibility

structuresmake training,performanceevalua-

tions, networking, and mentoring programs

more effective. Federal affirmative action

requirements,which typically lead to assign-

ment of responsibility or compliance,also cat-

alyze certainprograms.


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CORPORATEAFFIRMATIVEACTION AND DIVERSITYPOLICIES 591

These findings support an institutional the-

ory of inequality remediation that builds on key

precepts of organizational sociology. As Weber

(1978 [1968]) argues, executives must appoint

specialists and give them authority to achieve

specialized goals. Thus, remedies targeting indi-

vidual bias or network isolation may be less

effective than remedies that establish responsi-

ble parties. As neo-institutionalists (Meyer and

Rowan 1977) note, new programs decoupled

from everyday practice often have no impact.

Therefore, appointing a manager or committee

with responsibility for change is likely to be

more effective than annual diversity training,

periodic diversity evaluations, or decentralized

networking and mentoring programs. As struc-

tural theorists of organizational inequality claim

(Baron 1984), there is more to segregation than

rogue managers exercising bias. Thus, appoint-

ing special staff members and committees to

rethink hiring and promotion structures may be

more effective than training managers not to ask

their secretaries to make coffee, and not to

exclude minorities from football pools.

The argument that organizations should struc-

ture responsibility for reducing inequality may

seem commonsensical, but today's popular

diversity programs often focus on changing

individuals. In the academy generally and in

management studies particularly, methodolog-

ical individualism now holds sway. Theorists

prescribe solutions that change incentives for,

and beliefs of, individuals with the idea that

most problems of management are problems

of motivation rather than structure. Thus the

most popular program that is not federally man-

dated is diversity training, designed to attack

bias. Managerial bias is also the target of diver-

sity evaluations that offer feedback to man-

agers. Networking and mentoring programs

may appear to operate at the collective level, but

they are designed to fix a lack of specific

human and social capital in individual workers.

Next, we describe the three categories of

diversity practices, link them to theories of

inequality, and summarize the (scant) evidence

about the effects of workplace antidiscrimina-

tion programs. Then we review the research on

the effects of the Civil Rights Act and presi-

dential affirmative action edicts on employ-

ment-hitherto the main body of research on the

effectiveness of antidiscrimination measures.

After a discussion of data and methods, we

present the results from analyses of white men,

white women, black women, and black men in

management.

THREE APPROACHES TO INCREASING

MANAGERIAL DIVERSITY

Scholars often presume that practices designed

to attack known causes of inequality actually

will reduce it, as Reskin (2003) argues, making

a leap of faith between causes and remedies.

Thus, for example, although we know from

experimental psychology that unconscious bias

is endemic, and likely contributes to workplace

inequality, we can only hope that the prevailing

treatments-diversity training and diversity

evaluations-diminish inequality. Under-

standing the cause of malaria and understand-

ing its treatment are two different things.

Whether a prescription for inequality is effec-

tive is an inherently empirical question. Current

prescriptions are not based in evidence.

Our goal is to take a first step toward devel-

oping an empirically based theory of remedia-

tion for organizational inequality. We sketch

three mechanisms for remediating workplace

inequality rooted in different social science lit-

eratures and discuss the popular human

resources (HR) measures thought to put these

theories to work. One mechanism, based in

arguments from Max Weber and organization-

al institutionalists, is the creation of special-

ized positions as the way to achieve new goals.

Another mechanism, based in theories of stereo-

typing and bias, involves training and feedback

as the way to eliminate managerial bias and its

offspring, inequality. A third mechanism, based

in theories of social networks, involves pro-

grams that target the isolation of women and

minorities as a way to improve their career

prospects.

ORGANIZATIONALHANGE: TRUCTURESF

RESPONSIBILITY

We begin with a canonical insight from orga-

nizational theory. Organizational sociologists

and psychologists find that workers ignore

newly announced organizational goals and con-

tinue to pursue old goals with old routines. The

decoupling of formal goals and daily practice

may occur because individuals face information

overload, and thus stick to the familiar, or


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because the old ways of doing things have been

imbued with meaning and value over time

(Orton and Weick 1990; Selznick 1949).

Institutionalistsargue that decoupling is com-

mon in programs responsive to regulatory

demands, uch as civil rightsprograms Dobbin

et al. 1988; Edelmanand Petterson1999; Scott

2001; Sutton and Dobbin 1996). Thus, for

instance,academicdepartments aveabandoned

the old-boysystem of hiring n favorof open ob

advertisement,but department hairs still ask

their pals for leads. Some arguethat managers

may simply not perceive t as in their nterest o

promote gender and racial integrationof jobs

(Jacobs 1989b).Decoupling s particularlyike-

ly when there is no office or expertto monitor

progress, as Max Weber(1978 [1968]) hinted

when he argued hat executives should appoint

specialists to pursue specialized goals.

If Weberand the institutionalists re correct,

where diversity efforts are everyone'srespon-

sibilitybut no one'sprimary esponsibility,hey

aremore ikelyto be decoupled. n organizations

that do not assign responsibility for diversity

goals to a specific office, person, or group,

these goals may fall by the waysideas line man-

agers juggle competing demands o meet pro-

duction quotas, financial targets, and the like

(Edelman 1990; Meyer and Rowan 1977).

Scholars (Reskin 2003; Sturm2001) and con-

sultants (Winterle 1992) alike advise ongoing

coordination and monitoring of diversity

progress by dedicated staff members or task

forces. Three common approaches an be used

to establish responsibilityfor diversity,as dis-

cussed in the following sections.

RESPONSIBILITYAND AFFIRMATIVEACTION

PLANS. ssign responsibility or setting goals,

devising means, and evaluatingprogress;this

was Weber'sadvice to bureaucrats. he agency

LyndonJohnson et up in 1965 to monitoraffir-

mativeactionamong ederal ontractors ncour-

aged this approach. In 1971, the Office of

Federal Contract Compliance (OFCC, which

later gained a P for programs o become

OFCCP)orderedcontractors o write affirma-

tive action plans in which they annuallyevalu-

ate their own workforces,specify goals for the

fair representationof women and minorities

based on labor market analyses, and sketch

timetables for achievement of these goals

(Shaeffer 1973:66).

The order also specifies that firms should

assign responsibility o a staff member: He or

she must have the authority, esources,support

of and access to top management o ensurethe

effective implementation of the affirmative

action program (U.S. Department of Labor

2005). By collecting and reviewing ocal infor-

mation annually, he affirmativeaction officer

can track underutilization of women and

minorities and keep managers nformedabout

their departments' progress (Linnehan and

Konrad 1999:410; Reskin 2003:13) or initiate

constructivedialogue about making further

progress(Sturm2001).

The few studies hatexamineeffects of affir-

mative action plans are inconclusive. Baron et

al. (1991), studying annual data from 89

California state agencies between 1975 and

1981, found that, all else being equal, agencies

with affirmativeaction programsmade signif-

icantly slower progress in gender desegrega-

tion of jobs. Yet those agencies were more

integratedoriginally,so it may be that preex-

isting affirmativeaction programshad left lit-

tle roomfor improvementsee also Edelman nd

Petterson 1999:126; Leonard 1990:65). In a

study of 3,091 federal contractorswith affir-

mative action plans JonathanLeonard 1985b)

shows that the goals employers set for hiring

white women, blackwomen, andblackmen did

have positive effects, although the goals were

wildly optimistic. Goals apparentlydo not act

as quotas because virtually no employer ever

achieves its writtengoals.

Federal ontractors rerequired o writeaffir-

mative action plans, but contractor tatus does

not correspondperfectlywith the presence of a

plan. Many contractors ail to write plans or to

update hem (Bureauof NationalAffairs 1986;

Leonard 1990:55). Up to one fourth of firms

with affirmative ctionplansarenot contractors.

They createplans to bid for contractsor to set

diversity goals (Bureau of National Affairs

1986; Reskin 1998). In our sample,7 percentof

contractorsnever had a plan, and 20 percentof

firms thathad neverhad a contractwroteplans.

OVERSIGHTVIA STAFFPOSITIONS ND DEPART-

MENTS. ollowing the classic bureaucratic dic-

tum (Weber 1978 [1968]), some organizations

appoint ull-time taffmembersor createdepart-

mentsto monitordiversity nsteadof leaving he

task to line managersor assigning it to staffers


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with otherresponsibilities.As a newly appoint-

ed diversity manager in a high tech company

explained o us in 2001: As he organization as

started o grow, hey realized hey neededsome-

one in there to really pay attention o affirma-

tive action and compliance and ... efforts on

diversity.... So the position was createdat the

beginning of this year.

Big militarycontractorswere the first to cre-

ate special positions, in the wake of Kennedy's

initialaffirmative ctionorder n 1961. Edelman

and Petterson 1999) show that equal opportu-

nity departmentsdo not increase gender and

racial diversity on their own, but that they do

expand diversityrecruitmentprograms,which

in turn mprovediversity.We includea measure

for recruitmentprograms o isolate the effects

of diversitystaff positions.

OVERSIGHTAND ADVOCACYVIA COMMITTEES.

From the late 1980s, experts have advised

employers o appointdiversitycommitteesand

task forces comprising people from different

departments, professional backgrounds, and

managerial levels. Committees typically are

charged with overseeing diversity initiatives,

brainstorming o identify remedies, and moni-

toring progress.The diversitytask force at the

accounting and consulting giant Deloitte &

Touche, for instance, createda series of ongo-

ing groupsresponsible or analyzing he gender

gap, recommending emedialsteps, and estab-

lishingsystems ormonitoring esultsandensur-

ing accountability Sturm2001:492).

These three strategies share a focus on

responsibility.An organizationwith any one of

these has assignedresponsibility or progress o

a person or group-an affirmativeaction offi-

cer, a diversity manager or department,or a

committee or task force. That person or group

monitorsprogressregularly.Affirmativeaction

officers also write explicit annual goals for

progress,as do some staffers and committees.

BEHAVIORALHANGE: EDUCING IAS

THROUGH DUCATIONNDFEEDBACK

Social psychologists trace inequality to bias

amongmanagers.Stereotyping s a natural og-

nitive mechanism. It is inevitable given our

innocent endency o makeassociationsbetween

categories and concepts (Gorman 2005;

Heilman 1995; Lemm and Banaji 1999). The

implicit associations we make between race,

gender,ethnicity,and social roles can have the

effect of reproducing existing patterns of

inequality (Jost, Banaji, and Nosek 2004).

Managers may unwittingly select women for

jobs traditionally dominated by women and

men for obs dominatedby men, with the effect

of preserving between-group differences.

Moreover in-group preference is widespread

(TajfelandTurner1979) and may likewise con-

taminate managerial judgment (Baron and

Pfeffer 1994; Reskin 2000). Rosabeth Moss

Kanter 1977) sketches he earlyresearchon in-

group preference to support her theory of

homosocial reproduction-white men promot-

ing their clones. Kanterargues that managers

preferto hire their own for reasons of commu-

nication and trust.

Twocorporatenitiatives re hought o count-

er stereotyping and in-group preference.

Diversitytraining s thought o make managers

awareof how bias affectstheiractionsandthose

of subordinates. Diversity evaluations are

thought to provide managers with feedback

showing the effects of their decisions on diver-

sity.

EDUCATIONVIA DIVERSITYTRAINING.Social

psychological researchshows that giving peo-

ple informationabout out-groupmembersand

about tereotypingmay reducebias (Fiske 1998;

Nelson, Acker, and Melvin 1996). Diversity

trainingprovidesmanagerswith such informa-

tion. It can be traced to the equal opportunity

sensitivity rainingprograms hata handfulof

major corporations put together in the mid-

1970s in response to the first equal opportuni-

ty consent decrees and court orders (Shaeffer

1973). By the late 1980s, quite a few corporate

trainersandpsychologistshad developed rain-

ing modules designedto familiarizeemployees

with antidiscriminationaw, to suggest behav-

ioral changes that could address bias, and to

increase culturalawarenessand cross-cultural

communication Bendick, Egan, and Lofhjelm

1998).

Employersusually offer trainingeither o all

managersor to all employees. We look at the

effects of training offered at least to all man-

agers.Some studiesof diversity raining uggest

that it may activate rather than reduce bias

(Kidder et al. 2004; Rynes and Rosen 1995;

Sidanius,Devereux,andPratto2001). Research


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on diversity training programs has seldom

explored heireffectson workforce omposition,

but one study of federal agencies (Naff and

Kellough 2003) did show that a broaddiversi-

ty program had a negative effect on the pro-

motion of minorities (Krawiec2003:514).

FEEDBACKVIA PERFORMANCE VALUATIONS.

Feedback s thought o reducebias by directing

managerial attention and motivation (Reskin

2003:325). Laboratory xperimentsshow that

when subjects know that their decisions will

be reviewedby experimenters, hey show lower

levels of bias in assigning jobs (Salancik and

Pfeffer 1978; Tetlock 1985). Evaluatingman-

agers on their diversity performance creates

oversight and provides feedback. As early as

1973, the HarvardBusiness Review noted that

as one criterionof a line manager'sperform-

ance appraisal, ome companieshave included

his success in effectively implementingequal

opportunity programs (Fretz and Hayman

1973:137). By the mid-1980s, a study of nine

exemplary firms found that managers n each

firm received regular equal opportunityper-

formanceevaluations Vernon-Gerstenfeldnd

Burke 1985:59-60). To ourknowledge,no stud-

ies assess the effects of diversityevaluations.

TREATINGSOCIALISOLATION:NETWORKING

AND MENTORING

MarkGranovetter1974) brought nsightsabout

social networks,pioneeredby both sociologists

and psychologists, to the study of how people

find jobs. Students of inequality have since

speculated that differential network contacts

and differentialresources accruingfrom these

contacts may explain part of the continuing

inequality between whites and blacks, and

betweenmen andwomen (Blair-Loy 001; Burt

1998; Ibarra 1992, 1995; McGuire 2000;

Petersen, Saporta, and Seidelm 1998). White

men are more likely than others to find good

jobs through network ties because their net-

works are composed of other white men who

dominate the upper tiers of firms (Burt 1998;

Reskin and McBrier 2000, but see Fernandez

and Fernandez-Mateo 2006; Mouw 2003).

Social networksalso encourage rust, support,

and nformal oaching BaronandPfeffer 1994;

Castilla 2005; Kanter 1977). Networking and

mentoringprogramsdesigned specifically for

women and minorities are thought to provide

useful contactsand nformationThomas2001).

Both types of programswere pioneered in the

1970s and then revived in the 1990s as part of

diversitymanagement fforts Wernick 994:25;

Winterle 1992:21).

NETWORKING ROGRAMS.

Diversitynetwork-

ing programs or women andminoritiesvary in

structure. ome takethe form of regularbrown-

bag lunchmeetings,whereasothers nclude av-

ish national conferences (Crow 2003). These

programsmay be initiatedby employees or by

HR managers.They provide a place for mem-

bers to meet and share informationand career

advice. Some networks also advocate policy

changes,such as those involving amilypolicies

and domestic-partner benefits (Briscoe and

Safford2005). Althoughnetworkingmay occur

without any organizational mpetus, we exam-

ine formal networkingprograms hat employ-

ers support hrough elease ime forparticipants,

meeting space, funding,newsletters,and email

lists.

MENTORINGROGRAMS.n 1978, the Harvard

Business Review published an article titled

EveryoneWho Makes It Has a Mentor hat

made mentors a must-have for aspiring man-

agement trainees (Lunding, Clements, and

Perkins1979;see also Roche 1979). Proponents

of formal mentoringprogramsarguethat they

can level the playing field, giving women and

minorities he kinds of relationships hat white

men get through the old-boy network.

Mentoringprogramsmatch aspiringmanagers

with senior mentors,with the two meeting for

career counseling and informal advice.

Empirical tudies,such as BurkeandMcKeen's

(1997) survey of universitygraduates, uggest

a relationship between mentoring and career

success among women, but do not rule out the

possibility that ambitious women seek men-

tors. One study of randommentor assignment

within a single firm found that, in general,

mentees have improved social networks and

tacticalknowledge,whichmayhelp theircareers

(Moore2001). Othershavefound hatcross-race

mentoring relationships often fail (Thomas

2001), and that same-sex mentoring does not

have a positive effect on job placement n aca-


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demic departments of economics (Neumark

and Gardecki 1996).

ADVERSE FFECTS FDIVERSITYRACTICES

Some argue that affirmativeaction and diver-

sity programs can backfire (Bond and Pyle

1988; Linnehanand Konrad1999). First,exec-

utives may believe that women and minorities

benefit from reverse discriminationand thus

may not deserve their positions (Heilman,

Block, and Stathatos 997;but see Taylor1995).

Second,because of the elusive natureof cogni-

tive bias, conscious attemptsat thoughtregu-

lation -such as diversity rainingand diversity

evaluations- may even backfire, leading to

exaggerated stereotypingunder conditions of

diminished capacity, or when self-regulation

efforts are relaxed (Nelson et al. 1996:31).

Indeed,management onsultants ndresearchers

find mixed reactionsto diversitymanagement

among white males, who report that they are

tiredof being made to feel guilty in every dis-

cussion of diversity... of being cast as oppres-

sors (Hemphill and Haines 1997). Third,

coworkers and executives may have negative

reactions when they perceive minorities as

attempting o obtain power by individual and

collectivemeans Ragins 1995:106),andexec-

utives may fear that networking will lead to

union organizing(Bendick et al. 1998; Carter

2003; Friedman and Craig 2004; Miller

1994:443; Society for Human Resources

Management2004). Finally,some studies find

thatraciallydiversework groups communicate

less effectivelyandare ess coherent Baughand

Graen 1997; Townsendand Scott 2001; Vallas

2003; Williams and O'Reilly 1998). Taken

together, this research suggests that diversity

programs may inhibit management diversity,

particularly or blacks.

THE CIVILRIGHTS ACT, AFFIRMATIVE

ACTION EDICTS,AND DIVERSITY

PRACTICES

Although there is little researchon the effects

of corporate iversityprograms, he Civil Rights

Act and presidentialaffirmativeaction orders

havebeen shownto increasediversity.The Civil

RightsAct covers virtuallyall employers,mak-

ing research n its effectsdifficult Donohueand

Heckman 1991). The effects of presidential

affirmativeaction orders can be examined by

comparing ederal contractors ubjectto these

orders with noncontractors.Six studies using

EEOC data for periods of 4 to 6 years between

1966 and 1980 show that black employment

grew more quickly among contractors

(Ashenfelter ndHeckman1976;Goldsteinand

Smith 1976; Heckman and Payner 1989;

HeckmanandWolpin1976).Affirmativeaction

hadnegligibleeffects on whitewomen Leonard

1989:65). Contractor ffects on blacks, espe-

cially black women, declined from the early

1980s (Leonard 1990:58), coincident with the

Reaganadministration'solicy of deregulation.

These studies do not look at whether federal

contractors increased black employment by

adoptingantidiscrimination ractices.The two

exceptions are a study by Leonard (1985b)

showing that employers who set high recruit-

ment goals see more change and a study by

Holzer and Neumark (2000) showing that

employers subject to affirmative action law

expandrecruitment ffortsandhiremore appli-

cants from disadvantaged roups.We examine

the effect of affirmative action orders and

explore he possibility hatbeing subject o such

orders by being a federal ontractor)enders he

seven diversityprogramsmore effective.

In summary,we expect the differentsorts of

diversityprograms o vary n efficacy.If assign-

ing organizational esponsibility s more effec-

tive than targeting he behaviorof individuals,

then affirmative action plans, diversity com-

mittees, and full-timediversity taff will be fol-

lowed by broader increases in diversity than

will eitherdiversity rainingand diversityeval-

uations,or networking ndmentoring rograms.

By the same logic, the latter ourprogramsmay

be more effective when implemented n organ-

izations with responsibilitystructures.Finally,

we examinewhether ffirmative ctionoversight

rendersprogramsmore effective.

ALTERNATIVE OURCES OF CHANGE

IN THE MANAGERIALWORKFORCE

We include n the analysesother actors hought

to affect management diversity. We cannot

include factors hatdo not vary with time, such

as industry r location,becauseourfixed-effects

models account for such stable traits.


9/30


LEGALENVIRONMENT

Legal enforcement, through OFCCP compli-

ance reviews, lawsuits, and EEOC charges,

should increase employers'hiring and promo-

tion of women and minorities (Baron et al.

1991:1386; Donohue and Siegelman 1991;

Kalev and Dobbin forthcoming;Leonard1984;

Skaggs 2001).

ORGANIZATIONALTRUCTURES

Organizational ize andthe availability f man-

agerial obs createnew opportunities Baronet

al. 1991), but also more competition. Konrad

and Linnehan (1995) and Leonard (1990:52)

find that ncreaseddemand or managers avors

white women, but not African Americans.

Unionization tends to preserve segregationby

favoringold timers hrough eniorityprovisions

(Blau and Beller 1992; Milkman 1985; but see

Kelly 2003; Leonard 1985a). Formalization f

personnel systems can reduce favoritism

(Dobbinet al. 1993;ReskinandMcBrier2000),

although t also can create separatecareer ra-

jectories or different roups BaldiandMcBrier

1997; Baron and Bielby 1985; Elvira and

Zatzick 2002). Legal counsel may sensitize

employers o diversity n promotiondecisions,

and recruitment ystems targetingwomen and

minoritiescan increasediversity Edelmanand

Petterson 1999; Holzer and Neumark 2000).

Finally,work/family olicies mayremoveobsta-

cles to the promotion of women (Williams

2000).

TOPMANAGEMENTOMPOSITION

The diversityof the top management eam may

affect managerial hires through homosocial

reproductionor social closure (Kanter 1977;

Tomaskovic-Devey1993).

LABORMARKET NDECONOMICNVIRONMENT

Firms can more easily increase managerial

diversitywhen internaland external aborpools

are diverse (Cohen, Broschak, and Haveman

1998; Shenhavand Haberfeld 1992). Demand

for workers romunderrepresentedroupsmay

be higher in industrieswith more federal con-

tractors. n hardeconomic imes,blackmen, and

to a lesser extent women, are more vulnerable

than white men to being laid off (Elvira and

Zatzick 2002; Kletzer 1998). Finally,growing

industries can offer more attractive obs, and

both women and minorities have historically

been relegated o less attractive ectors (Reskin

and Roos 1990:298).

DATA AND METHODS

We conducted a fixed-effects analysis of lon-

gitudinaldataon the workforcecompositionof

708 establishments o assess changes in mana-

gerialcompositionafter he adoptionof each of

seven diversity practices. The data cover the

period1971-2002. Fixed-effectmodels account,

implicitly, or organizations'unobservedchar-

acteristics that do not vary over time and that

may affect diversity.

EEOCDATA

The Civil Rights Act of 1964, as amended,

requiresprivateemployerswith more than 100

employees and government contractors with

more than 50 employees and contracts worth

$50,000 to file annual EEO-1 reports. These

reportsdetail the race, ethnicity,and gender of

employees in nine broad occupational cate-

gories. There are no better data on workforce

composition for a methodological iscussionon

using EEO-1reports, ee Robinsonet al. 2005).

We obtainedthe data from the EEOC through

an IntergovernmentalersonnelAct (IPA)agree-

ment.

Some argue hatemployersreclassifiedjobs

in the 1970s, moving women and minorities

into managementcategories to improve their

federal reports (Smith and Welch 1984).

Leonard 1990:53) notes that purereclassifi-

cation would cause black losses in the lower

occupations[in the EEO data],which is gener-

ally not observed. Jacobs (1992:298) shows a

declining gender earningsgap consistent with

realprogress,noting hat thepredominantrend

has been toward eal, f slow progress nto man-

agementon the partof women. n our sample,

few firms show sudden ncreases or women or

blacks in management,but we checked results

for robustnessby eliminating hese cases, and

the results did not change. We also eliminated

establishment-year pells from before 1990, as

discussed later,and the findings held up.


10/30


ORGANIZATIONALURVEY ATA

We drew a random sample of establishments

fromthe EEO-1 database or our organization-

al survey. For that sample, we constructed a

dataset comprising all EEO-1 reports for the

years 1971-2002, interpolating or the missing

years of 1974, 1976, and 1977. Establishments

enter the datasetwhen they begin filing EEO-

1 reports.To ensure hatwe wouldbe ableto fol-

low establishmentsover time, we chose half of

the sample from establishments hat had been

in the dataset ince 1980 andhalf from hosethat

had been in the dataset since 1992. We also

stratifiedby size, selecting 35 percentof estab-

lishments with fewer than 500 employees in

1999, and by industryto represent he manu-

facturing, ervice,and rade ectors.We sampled

from food, chemicals, computer equipment,

transportationquipment,wholesale rade, etail

trade, nsurance,business services, and health

services. Corporatediversitycan be influenced

by acquisitions, pin-offs,andplantclosings, so

we sampledestablishments, electing no more

than one per parent irm.

We conducted a longitudinal survey of

employment practices at each establishment

covering he years 1971-2002, in collaboration

with the PrincetonSurveyResearchCenter.We

drewon the experiencesof otherswho had con-

ducted organizational urveys of employment

practices (particularlyKalleberg et al. 1996;

Kelly 2000; Osterman 1994, 2000). We com-

pleted 833 interviews,for a responserate of 67

percent, which compares favorably with the

rates of those other organizational urveys. In

preparation,we conducted41 in-person nter-

views with HR managers rom randomly am-

pled organizationsn fourdifferent egions,and

20 pilot phone interviews. Data from those

interviews are not included in the analyses

reported n this discussion.

We began by writing to the HR director at

each establishment.We asked for permission o

conduct an interview and for the name of the

person who could best answerquestions about

the establishment's istoryof HR practices.The

typical ntervieweewas an HR managerwith 11

yearsof tenure.We scheduledphone interviews

at the convenience of the interviewees, and

explained in advance the nature of the infor-

mation needed. We asked whether the estab-

lishmenthad everused each personnelprogram,

when it was adopted,and whetherand when it

hadbeen discontinued. rogram iscontinuation

was rare.When a respondentcould not answer

a question, we sent a copy of that question by

email or fax, askedthat she consult recordsand

colleagues, and called back to fill in the blanks.

During our in-personpilot interviews, respon-

dents routinelypulled out manualswith copies

of policies and lists of adoption and revision

dates. Nonetheless, because responses about

events long past may be inaccurate,we repli-

cated the analyses using only establishment-

year spells for 1990 to 2002, as discussed later.

We matched survey data for each establish-

ment with annual EEO-1 records, creating a

datasetwith annual establishment-year pells.

After excluding 10 cases that had EEO-1 data

available or fewer than 5 years, 13 cases with

excessive numbersof missing values for EEO-

1 or survey data,and 102 cases thatwere miss-

ing the adoption date for at least one key

program,our final dataset included 708 cases

and 16,265 establishment-year cells, with a

medianof 25 years of dataper establishment,

minimum of 5 years, and a maximum of 32

years. We collected dataon national,state, and

industry mployment rom he Bureauof Labor

Statistics.

Because of our stratified sampling design

and the response pattern,we were concerned

thatrespondentsmight not represent he popu-

lationof establishments hatfile EEO-1reports

in the sampled industries. We constructed

weights based on the inverseprobability hatan

establishment rom each stratum industryby

size and by time in the EEO-1 dataset)would

complete the survey.We replicatedall reported

analysesusing weights,andthe resultsremained

intact.We reportunweightedresults in the fol-

lowing discussion (Winshipand Radbill 1994).

We also were concerned that employers who

refusedto participatemight systematicallydif-

fer, on factors affecting diversity, from those

who participated.We included in the models

predictedvalues from a logistic regressionesti-

mating the probabilityof response (Heckman

1979). This did not change our results.

Covariates n that model were industry,estab-

lishment status (headquarters, ubunit, stand-

alone status),size, contractor tatus,managerial

diversity, nd contactperson'sposition.The last

variablewas obtained n the initial contact,the

others from the EEO-1 data.


11/30


DEPENDENTVARIABLES

The dependentvariablesare the log odds that

managersare white men, white women, black

women, and black men . For each group, odds

are calculated as the proportionof managers

from that group divided by the proportionnot

from that group (proportion/(l- proportion)).

Figure 1 presents he trends, n percents, n our

sample. Between 1971 and 2002, management

jobs held by white men decline from 81 to 61

percent in the average establishment.

Management obs held by white women rise

from 16 to 26 percent, whereas those held by

black women rise from 0.4 to 2 percent, and

those held by black men rise from 1 to 3.1 per-

cent. There also is a significant rise in the rep-

resentationof othergroups,notablyHispanics,

during his period,which s why the percentages

do not sum up to 100 percent.

Black women and men showed dramatic

changes in their proportions in management

relative o the baseline,quadrupling nd ripling,

respectively,but saw small changes in percent-

age points. Because the absolute changes for

blacks are relatively small we log the depend-

ent variables.We use log odds, rather han log

proportion,because the distribution s close to

normal (Fox 1997:78).1In a sensitivity analy-

sis, log proportionperformed very similarly.

The dependentvariable s measuredannually,

one year after the independent variables.

Changing he lag to 2, 3, or 4 yearsdoes not alter

the findings. Our sample is designed to inves-

tigatethe effects of diversityprograms n work-

force composition in private sector

establishments large enough to file EEO-1

reports.We do not claim to describe he nation's

managerialworkforce.Nationally epresentative

samples such as the CurrentPopulationSurvey

include the public and nonprofit sectors, in

which the gains of women and minoritieshave

1Because og-odds logit) s undefined t values

of 0 and 1, we substituted with 1/2Nj,and 1 with

1-1/2Nj,whereNj is the number f managersn

establishment (Hanushek ndJackson1977;Reskin

andMcBrier 000).Theresultswererobust o dif-

ferent ubstitutionsor0. Wechose heone hatkept

the distributionnimodal ndclosest o normal.To

ensure hat he substitutionoesnot drive he find-

ings,we include binary ariableorno groupmem-

bers n management.

been larger.Furthermore,ational iguresreflect

the change in women's representation n man-

agementassociatedwith service sector growth

(e.g. Jacobs 1992), whereas our data track a

relatively stable set of firms.

AFFIRMATIVECTION LANSANDDIVERSITY

PRACTICES

Figure2 showsthe prevalence f all sevendiver-

sity programsamong the 708 employers ana-

lyzed later. By 2002, affirmative action plans

were used in 63 percent of the workplaceswe

study, ollowedby training n 39 percent,diver-

sity committees n 19 percent,networkingpro-

grams forwomenandminorities) n 19 percent,

diversity valuations or managers n 19 percent,

diversity taff n 11 percent,andmentoringpro-

grams forwomenandminorities) n 11 percent.

The bivariate correlations and joint frequen-

cies of the seven programsare not shown here

(see Online Supplement,ASR Web site: http://

www2.asanet.org/joumals/asr/2006/toc052.html).

In the analysesreported n the following dis-

cussion,we use binaryvariables o represent he

presenceof the sevendiversity rograms. orsix

programs,we asked whether the organization

had ever had the program, when it was first

adopted, ndwhen (if ever) t was discontinued.

For the seventhpractice,diversitytraining,we

asked when it was first and last offered. If an

employerhad gone for 3 yearswithout raining,

we treated he programas defunct.We collect-

ed additional nformation boutdiversity rain-

ing because our n-person nterviewssuggested

that it varied across organizationsmore than

the other programs,but we found significant

similarities n trainingprograms. n 70 percent

of the establishmentswith training for man-

agers, trainingwas mandatory. ncluded n 80

percent of the trainingprogramswas a discus-

sion on the legal aspectsof diversity, nd98 per-

cent were conducted with live facilitators, as

opposed to being offered exclusively via the

Web or video. Although some organizations

offered trainingnot only to managers,but also

to all employees, we reporteffects of training

for managersbecause managersmade promo-

tion decisions. Training or all employees had

nearly identical effects in the models.

Because the measures are binary, coded 1

for all the years he program s in place,program

effects are estimated for the entire period of


12/30


percent

of

managers

90%

80%

70%

60%

50%

40%

1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Year

S---- White Men -0--- White Women -4- Black Men - - - - Black Women

Figure 1. Percent of Managers: White Men and Women and Black Men and Women, 1971-2002

Note: Based on EEO-1 reports 1971-2002 sampled for Princeton University Human Resources Survey 2002.

Varying N. Maximum N = 708; EEO = equal employment opportunity.

percent

of

Workplace

40%

30%

20%

1970 1972 1974 1976 1978 1980 1982

--- AA Plan

--A-- Diversity Committee

-0-- Diversity Training

- - -Mentoring for Women/Minorities

1984 1986 1988 1990 1992 1994 1996 1998 2000 2002

Year

-- FullTimeEO/AAStaff

-4- DiversityEfforts n Mgrs'Evaluations

-)-- Networking for Women/Minorities

Figure 2. Percent of Private-SectorWorkplaceswith Affirmative Action Plans and Diversity Programs, 1971-2002

Note: Based on Princeton University Human Resources Survey, 2002. Varying N. Maximum N = 708.


13/30


the program's xistence(not merelyfor the year

after initiation).

For six of the programs, between 2 and 4

percent of the respondents who reported the

program'sadoption could not tell us the exact

year.For he seventhpractice,affirmative ction

plan, the figure was 8 percent.We eliminated

cases with missing data on any of these vari-

ables. The resultswere virtually denticalwhen

we imputedmissing datafor variablesof inter-

est and retained these cases in the analysis.

Missing adoption dates for control variables

were imputed using ordinary least squares

(OLS) regression, with industry,age of estab-

lishment, and type of establishmentas covari-

ates. Omittingcases with imputeddata did not

substantiallyalter the findings.

CONTROL ARIABLES

All measures included in the analyses vary

annually.Table 1 presentsdefinitions and data

sources for key variablesas well as means and

standarddeviations (based on all organization-

al spells). Descriptive tatistics or the entire ist

of control variables are not shown here (see

Online Supplement,ASR Web site). Because

the fixed-effects method estimates variation

within the organization, t captures hangeover

time. For example, in the models, the variable

organizational size captures the effect of a

change in size on change in managerialdiver-

sity. These models effectively ignore measures

that do not change, such as industry,but cross-

case variation n those measures s capturedby

the fixed effects.

LEGALENVIRONMENT.e include a binary

variablebased on the EEO-1 reports ndicating

whether he establishment s a federalcontrac-

tor subject to affirmative action regulation.

Legal enforcement s measuredusing threesur-

vey variables that capturethe establishment's

experience with Title VII lawsuits, EEOC

charges, and affirmative action compliance

reviews. Each is coded 1 from the year of the

firm's first enforcementexperience.More than

one thirdof establishment-year pells had pre-

viously faced a lawsuit; more than one third

had faced an EEOC charge;and nearly 15 per-

cent had faced a compliancereview (only con-

tractorsare subject to compliancereviews).

ORGANIZATIONAL STRUCTURES. Organi-

zationalsize andavailability f managerialobs

are measured using EEO-1 data on the total

numberof employees in the establishmentand

the number of managerial employees.

Unionization is coded 1 when the establish-

ment has at least one contract. Substituting

with a measure of core job unionization does

not alter he results.FormalHR policies involve

a count of hiring, promotion, and discharge

guidelines; job descriptions; promotion lad-

ders; performanceevaluations;pay grade sys-

tem: and internal ob posting. Legal counsel is

measuredwith a binary variable for the pres-

ence of an in-house attorney.Targeted ecruit-

ment policy is a binary measure of special

diversity ecruitment fforts.Work-family up-

port counts paid maternity eave, paid paterni-

ty leave, flextimepolicies, andtop management

support or work-family programsas assessed

by our respondents.

TOP MANAGEMENTOMPOSITION.op man-

agement team diversity is measured with the

percentage of the top 10 positions held by

women and/or African Americans, based on

survey data.We asked about the percentageat

10-year intervals and interpolatedvalues for

the interveningyears.

LABORMARKET ND ECONOMIC NVIRONMENT.

The diversity of the establishment's internal

laborpool is measuredwith two variablesbased

on the EEO-1 reports: he percent of the focal

group n nonmanagerialobs and the percent n

the corejob. To determine he EEO-1 category

that held the core job, we asked respondents

about the single biggest job in the organiza-

tion. We include a variablecoded 1 when there

are no membersof the focal group in manage-

ment. Diversity of the establishment's xternal

labor pool is capturedby two sets of variables

on industry and state labor forces from the

CurrentPopulation Survey. Industryemploy-

mentvariablesare ogged.We use the industry's

percent of governmentcontractors based on

EEO-1 data)to measuredemand or underrep-

resentedworkers n affirmativeaction sectors.

Economic conditions are measured with the

yearly state unemploymentrate, and industry

size is measured as total annual industry


14/30

CORPORATEAFFIRMATIVEACTION AND

DIVERSITYPOLICIES 6ol

Table

1.

Selected

Variables

Used

in

Analysis

of

Managerial

Workforce

Composition

Mean

Standard

Deviation

Minimum

Maximum

Type

Data

Outcome

Variables

(percent)

Managers

who

are

white

men

70.0

23.6

0

100

Continuous

EEO-1

Managers

who

are

white

women

22.2

21.2

0

100

Continuous

EEO-1

Managers

who

are

black

women

1.4

4.2

0

66.7

Continuous

EEO-1

Managers

who

are

black

men

2.4

5.9

0

100

Continuous

EEO-1

Affirmative

Action

and

Diversity

Measures

Affirmative

action

plan

.422

.494

0

1

Binary

Survey

Full

time

EEO/diversity

staff

.045

.206

0

1

Binary

Survey

Diversity

committee

.052

.222

0

1

Binary

Survey

Diversity

training

.064

.244

0

1

Binary

Survey

Diversity

evaluations

of

managers

.102

.303

0

1

Binary

Survey

Networking

programs

.064

.244

0

1

Binary

Survey

Mentoring

programs

.033

.179

0

1

Binary

Survey

Legal

Environment

Affirmative

action

status

(government

contract)

.455

.498

0

1

Binary

EEO-1

Compliance

review

.149

.356

0

1

Binary

Survey

Discrimination

lawsuits

.341

.474

0

1

Binary

Survey

EEOC

charges

.314

.464

0

1

Binary

Survey

Organizational

Structures

Percent

managers

in

establishment

.124

.090

.002

.789

Continuous

EEO-1

Establishment

size

702

827

10

12,866

Continuous

EEO-1

Union

agreement

.254

.436

0

1

Binary

Survey

Formal

HR

policies

4.917

2.516

0

9

Count

Survey

In-house

attorney

.277

.448

0

1

Count

Survey

Special

recruitment

for

women

and

minorities

.156

.363

0

1

Binary

Survey

Work-family

accommodations

.912

.978

0

4

Count

Survey

Top

Management

Composition

(percent)

Top

managers

who

are

minorities

3.471

10.239

0

100

Continuous

Survey

Top

managers

who

are

women

16.445

23.575

0

100

Continuous

Survey

Note:

N

=

16,265.

Labor

market

and

economic

environment

variables

are

included

in

the

analyses

but

not

shown

here.

See

note

to

Table

2

or

a

etailed

list

of

variables

not

shown

here

(see

entire

list

of

control

variables

on

Online

Supplement,

ASR

Web

site:

http://www2.asan

EEO

=

equal

employment

opportunity;

HR

=

human

resources.


15/30


employment,both fromthe CurrentPopulation

Survey.

METHODS

We use pooled cross-sectional ime-seriesmod-

els, with fixed effects for bothestablishment nd

year (Hicks 1994; Hsiao 1986). We use fixed

effects for establishmentso account or unmea-

sured, ime-invariant haracteristics hat might

affect outcome variables (for recent empirical

examples of these methods appliedto individ-

uals, see Budig and England 2001; Western

2002). This specification, achieved by sub-

tracting the values of each observation from

the establishment mean (Hsiao 1986:31),

strengthens our causal inferences about the

effects of affirmativeaction plans and diversi-

ty practices by ruling out the possibility that

organizations hat adoptedthose practiceshad

stableunobservedpreferences or diversity.To

capture environmentalchanges, such as legal

and cultural hifts, we use a binaryvariable or

each year, omitting 1971. The large numberof

parametersnvolved n estimating ixed-effects

models rendersthem less efficient than other

estimators.However, we prefer these to alter-

native models because they provide the most

stringent tests of our hypotheses. The estab-

lishment and year fixed effects also offer an

efficient means of dealing with nonconstant

varianceof the errors heteroskedasticity)tem-

ming from the cross-sectional and temporal

aspects of the pooled data.

Because our dependentvariablesare meas-

ured as parts of the same whole (the whole

being management obs), we expect their error

terms to be correlated.Ordinary east squares

would husproduceunbiasedandconsistent,but

inefficient, estimators.We use seemingly unre-

lated regression, which takes into account

covariance between the errors and produces

unbiased, efficient estimators (Felmlee and

Hargens 1988; Greene 1997; Zellner 1962).

Simultaneous stimationalso allows us to com-

parethe effect of each diversitypracticeacross

groupswith formalchi-square ests (Kalleberg

and Mastekaasa2001; Zellner 1962).

FINDINGS

The analysis shows substantial ariation n the

effectiveness of diversity programs. Some

increasemanagerialdiversityacross the board,

whereas others have meager effects, or posi-

tive effects for some groupsandnegativeeffects

for others.The most effectivepracticesare hose

thatestablish rganizationalesponsibility: ffir-

mative action plans, diversity staff, and diver-

sity task forces. Attempts to reduce social

isolationamongwomen andAfricanAmericans

through networking and mentoring programs

are ess promising.Leasteffective areprograms

for taming managerialbias througheducation

and feedback.

DIVERSITYROGRAMST WORK

In Table 2, we report models of managerial

diversity. (Selected control variables are pre-

sented;the remainingcoefficients can be seen

on the OnlineSupplement,ASRWebsite). Each

dependentvariable s the (natural) og odds of

managersbeing from a certaingroup.To trans-

form he coefficient[p romrepresenting hange

in log odds to representingpercentagechange

in odds, it should be exponentiated: exp([3)-

1]*100. Once exponentiated in this way the

coefficient representsthe average percentage

change n the odds thatmanagers refroma cer-

taingroup,associatedwith a change n the inde-

pendentvariable. n the discussionbelow we use

'odds for [group]'as a shorthand.We also pro-

vide an illustrativesummary of the results in

proportion erms.

The R2 figures for these fixed-effects mod-

els represent the percentage of the variance

explained by the predictors when the unique

effectsof each establishment reexcluded.A log

likelihood ratio test shows that the variables

reported n Table 2 significantly improve the

model fit (chi(28) = 405.66; p < .001), as com-

pared with the baseline models that have no

variables epresenting iversityprograms avail-

able on request).

ORGANIZATIONALRESPONSIBILITY.Coeffi-

cients for the diversityprogramsrepresent he

change in the log odds that managersare from

a certain group that is attributable o the pres-

ence of a practice,averagedacross all years of

the program's xistence.After employers et up

affirmative ctionplans,the odds for white men

in managementdecline by 8 percent; he odds

for white womenrise by 9 percent;andthe odds

for blackmen rise by 4 percent.These numbers

represent the estimated average difference


16/30

CORPORATEFFIRMATIVECTIONAND

DIVERSITYOLICIES

603

Table2. FixedEffectsEstimates f

the

Log

Oddsof

White

Men andWomenandBlack

Women ndMen

in

Management,

971-2002

WhiteMen WhiteWomen BlackWomen

Black Men

Organizational esponsibility

Affirmative ctionplan -.078** .086** .005 .039*

(.017) (.017) (.014) (.015)

Diversity

ommittee

-.081** .175** .242** .114**

(.028)

(.029) (.024)

(.026)

Diversity

taff -.055

.104**

.123**

.128**

(.033) (.034) (.028) (.030)

Managerial

ias

Diversity raining

-.038

-.001 -.066** .031

(.021) (.022) (.018) (.019)

Diversity

valuations .028 .061*

-.027 -.081**

(.027)

(.028) (.023) (.025)

Social Isolation

Networking rograms -.083** .080** .012 -.096**

(.027) (.028) (.023) (.024)

Mentoring rograms

-.011 -.004 .213**

.037

(.033) (.035)

(.029) (.031)

Legal

Environment

Governmentontract .032

.006 -.039*

-.027

(.019)

(.019) (.016)

(.017)

Compliance

eview

-.083** .077** .020 .081**

(.020) (.020)

(.017) (.018)

TitleVII lawsuit

-.107**

.141** .044**

.029*

(.015)

(.016) (.013)

(.014)

EEOC

charge

-.007 .014

.019 .034*

(.016) (.017) (.014) (.015)

Organizational

tructures

Proportionmanagers

n

establishment

-.896**

.309**

-4.499**

-3.989**

(.108) (.112)

(.092)

(.099)

Establishment

ize

(log)

-.021

-.023*

-.661**

-.515**

(.012)

(.012)

(.010) (.011)

Union

agreement

-.053 -.068*

-.007

-.029

(.033)

(.034) (.028)

(.030)

Formal

ersonnel olicies

-.002

-.003 -.016**

-.015**

(.004) (.004)

(.003)

(.003)

In-house

ttorney

-.100**

.126** -.040*

.021

(.023)

(.024) (.020)

(.021)

Targetedecruitmentolicy -.071** .108** .131** .099**

(.021)

(.021)

(.018)

(.019)

Work-family

ccommodations

-.078**

.065**

.026**

.004

(.008)

(.009)

(.007)

(.008)

TopManagement

omposition

Proportion

minorities

n

top management

-.002

-.002

.007**

.012**

(.001)

(.001)

(.001)

(.001)

Proportion

omen

n

top management

-.002**

.004**

.002**

-.002*

(.001)

(.001)

(.001)

(.001)

R2

64 parameters)

.3335 .3146

.3636

.2799

Note:

Log

likelihood atio

est;

X2

28)

=

405.66;

p

<

.001. Datashownarecoefficients rom

seemingly

unrelated

regression

with standard rrors n

parentheses.

ariablesncluded

n the

analyses

butnot shownhereare 8

vari-

ablesfor

proportion

f each

group

n

non-managerial

obs

and

n

core

ob

in each

establishment;

binary

vari-

ables

for no workers roma

group

n

management;

variables

or

proportion

f each

group

n stateand

ndustry

labor

orces;

proportion

f contractorirms n

industry;

ndustry mployment;

ndstate

unemployment

ate

full

resultson Online

Supplement,

SRWebsite:

http://www2.asanet.org/journals/asr/2006/toc052.html).

nalyses

also includeestablishment

nd

year

fixed

effects.

All

independent

ariables re

aggedby

1

year,excluding

proportion

f

managerial

obs.

N

(organization-year)

16,265;

N

(organizations)

708.

EEOC

=

Equal

Employment Opportunity

Commission.

*

p

<

.05;

**

p

<

.01

(two

tailed

test).


17/30


between having a plan and the counterfactual

condition of not having a plan for the entire

period of the plan'sexistence.These resultsare

consistent with Leonard's 1990) finding that

affirmativeactionplan goals areeffective.Note

that the coefficient for black women is not sig-

nificant here. When we introduced industry

interactions,we discovered hat n manufactur-

ing (computers, electronics, transportation),

affirmative action plans had negative effects

on black women, whereas in service (retail,

insurance, usinessservices),affirmative ction

planshadpositiveeffects (resultsavailableupon

request).Creating diversity ommittee ncreas-

es the odds for white women, across the period

of the committee's existence, by 19 percent.

The odds for black women rise 27 percent,and

the odds for black men rise 12 percent.

Employerswho appoint ull-timediversity taff

also see significant increases in the odds for

white women (11 percent), black women (13

percent), and black men (14 percent) in man-

agement.

As noted, he coefficients n Table2 represent

the averagechanges in log odds that managers

are from a certain group. The effect of each

programon the percent of women and minori-

ties in management will vary depending on

where organizationsbegin (Fox 1997:78). For

example, an 8 percent decrease in the odds of

managersbeing white men resulting romadop-

tion of affirmativeaction plan would translate

to a decline of 2.6 percent in the percent of

white men in managementf they constituted 0

percent before adoption, but it would mean a

larger decline of 4.3 percent if they made up

only 50 percent at the baseline (Petersen

1985:311).

PROGRAMSFOR REDUCINGMANAGERIAL IAS.

Programsdesigned to reduce managerialbias

through ducation diversity raining)and feed-

back (diversity evaluations)show one modest

positive effect and two negative effects across

the threedisadvantaged roups.Diversity rain-

ing is followedby a 7 percentdecline n the odds

for black women. Diversityevaluationsare fol-

lowed by a 6 percentrise in the odds for white

women, but an 8 percentdecline in the odds for

black men. These mixed effects are anticipated

in the literature. s noted, aboratory tudiesand

surveys often show adverse reactionsto train-

ing (Bendick et al. 1998; Nelson et al. 1996).

Moreover, critics argue that trainers define

diversitybroadly o include groupsnot covered

by federal civil rights law (parents,smokers),

and therebydrawattentionaway from protect-

ed groups (Edelman, Fuller, and Mara-Drita

2001; Kochanet al. 2003; Konrad ndLinnehan

1995).

PROGRAMSFOR REDUCING OCIAL SOLATION.

Networkingandmentoringprograms,designed

to countersocial isolation, show modest effects

on managerial iversity.Networking s followed

by a rise in the odds for white women and a

decline in the odds for white men and black

men. The negative coefficient for black men is

anticipated y qualitative esearch Carter 003;

Friedman nd Craig2004) showing thatwhites

can develop negative attitudes owardAfrican-

American organizing. In contrast, mentoring

programsshow a strong positive effect on the

odds for black women. These findings suggest

that having personal guidance and support at

workcan facilitatecareerdevelopment Castilla

2005) for black women, whereasnetworking s

more effective for white women.

GENDER AND RACIAL PATTERNS.Overall, it

appears that diversity programs do most for

white women and more for black women than

for black men. Black men gain significantly

less from affirmative action than do white

women (chi-sq(1) = 4.15, p < .05), and signif-

icantly less from diversity committees than do

blackwomen (chi-sq(l) = 22.47, p.< .01). Three

programs show negative effects on African

Americans,whereasno programshows a neg-

ative effect on white women. We hesitate to

overinterprethis pattern,but note thatthere is

something of a trade-offamong groups.

Table3 evaluates he magnitude f the effects

of programson the proportion f each group n

managementbased on the coefficients in Table

2. Proportionn year of adoption s the mean

proportion of each group in management,

amongadopters,n theiractualyearsof program

adoption i.e.,just before reatment). Estimated

proportionwith practice shows the predicted

mean proportionafter the practice is in place.

Thus, for example, the proportion of white

women among managers n the averageestab-

lishment adopting an affirmative action pro-

gram was 0.132, and the net effect of the


18/30

CORPORATE

FFIRMATIVECTION

NDDIVERSITY

OLICIES

605

Table3.

Estimated

Average

Differences

n

Managerial omposition

Due

to

Adoption

of

Affirmative

Action

and

Diversity

Practices

WhiteMen

WhiteWomen

Black

Women

BlackMen

Affirmative

ActionPlan

Proportionnyearof adoption .783 .132 .017 .024

Estimated

roportion

ith

practice

.769

.142

.017

.025

Percent

ifferencedue to

adoption

-1.8%**

7.6%**

.0% 4.2%**

Diversity

Committee

Proportion

n

year

of

adoption

.630

.230 .014

.020

Estimated

roportion

ith

practice

.611

.262

.018 .022

Percent ifference

due

to

adoption

-3.0%**

13.9%**

29.8%** 10.0%**

Diversity

Staff

Proportion

n

year

of

adoption

.724

.157

.014

.021

Estimated

roportion

ith

practice

.713 .171

.016 .024

Percent

ifferencedue to

adoption

-1.5%

8.9%**

14.3%**

14.3%**

Diversity

Training

Proportion

n

year

of

adoption

.687 .194 .017 .022

Estimated

roportion

ith

practice

.679 .194

.016

.023

Percent

ifference ue to

adoption

-1.2% .0% -5.9%**

4.5%

Diversity

Evaluations

Proportion

n

year

of

adoption

.720

.160 .017

.024

Estimated

roportion

ith

practice

.726

.168 .017

.022

Percentdifference ue to

adoption

.8%

5.0%

.0%

-8.3%**

Networking rograms

Proportion

n

year

of

adoption

.702 .193 .014

.020

Estimated

roportion

ith

practice

.684 .206 .014

.018

Percent

difference ue

to

adoption

-2.6%** 6.7%**

.0%

-10.0%**

Mentoring rograms

Proportion

n

year

of

adoption

.690

.216 .017 .021

Estimated

roportion

ith

practice

.688

.215 .021 .022

Percent ifferencedue to

adoption

-.3%

-.5%

23.5%** 4.8%

Note:

Estimates asedon coefficients

presented

n

Table

2.

*

p

<

.05;

**

p

<

.01

(two

tailed

est).

program,

with control for

other

factors,

is

to

raise white women

proportion

to 0.142.

Similarly,

he

proportion

f blackwomen

among

managerswas 0.014 intheaverage irmadopt-

ing

a

diversity

committee,

and

adoptionbrings

black women to

0.018,

an increase of

almost

30%.

The

third

row,

based on the

first two

rows,

reports

he

percentage

hange

overthe baseline

resulting

from

program

adoption.

Tables

2

and 3

support

our

contention

that

programs stablishingorganizational

esponsi-

bility

are

more

broadly

effective than hose

that

address

managerial

bias

or

social isolation

among women and African Americans.

Organizations

hat

structure

esponsibility

see

consistent

positive

effects for

white

women,

black

women,

and black

men.

Coefficients

for

control variables

are con-

sistent

with

expectations,

with one

possible

exception.

The

negative

effect

of formal

per-

sonnel

policies

is not consistent with the idea

that

bureaucracy mpedes

cronyism

or

bias

in

promotion

decisions

(Reskin

and McBrier

2000), butis consistentwiththe argumenthat

formalization eads to

the

needless

inflationof

educational

prerequisites

Collins 1979),

and

with

findings

that

the

determinants f

promo-

tion

differ

systematically

or

whites andblacks

even

when formal

personnel

systems

exist

(Baldi

andMcBrier

1997).

Other oefficients

of

control variables show that

although growth

and

unionization

have

not

improveddiversity,

and

although egal

staffhad

only

limited

effects,

targeted recruitmentprograms,work/family

accommodations,

and

top

management

team

diversity

show

positive

effects

on

managerial

diversity.

Coefficients

for the

labor

marketand

economic

environment

measures,

not

shown

here,

are

in

the

expected

directionas well

(see

Online

Supplement,

ASR

Web

site).


19/30

606

AMERICANOCIOLOGICAL

EVIEW

DOEs ORGANIZATIONAL ESPONSIBILITY

IMPROVEPROGRAMEFFECTIVENESS?

It

is

possible

that

some

programs

work best in

combination with others

(MacDuffie

1995;

Perry-SmithandBlum2000). Ourfindingthat

organizational responsibility

structures

have

broadereffects

than

other

programs

suggests

that

perhaps

training,

evaluation,

mentoring,

and

networking

would be more successful in

combination

with

responsibility

tructures.

We

undertake everal

analyses

of

program

combi-

nations.

First,

we

explore

the

possibility

that

he

sim-

ple

number

of

programs

matters.

Perhaps

our

measures

apture

not the effects of discrete

pro-

grams

so

much as

an

orientation oward

hang-

ing workplacedemography.We introducehree

binary

variables

epresenting

he

presence

of

any

one,

two,

and three or more

programs.

Across

the

16,265

organization-year pells

of

data,

49

percent

had no

programs,

34

percent

had

one

program,

10

percent

had two

programs,

and 7

percent

had three or more

programs.

n the

top

panel

of Table

4,

we

report

the

effects of the

Table4. Fixed-EffectsEstimates f theLogOddsof WhiteMenandWomen ndBlackWomen nd Men n

Management

ith

Bundles

of

Programs,

971-2002

White White Black Black

Men

Women Women Men

Adoption

f

One or More

AA

Plans&

Diversity

Programs

Only

one

program

-.043** .056** -.009

.026

(.016) (.016) (.013) (.014)

Two

programs

-.091**

.121**

.020 .024

(.023) (.023) (.019) (.021)

Three

or

more

programs

-.158**

.232** .127**

.046

(.029) (.030) (.025) (.027)

R2

(60

parameters)

.3323 .3124 .3569

.2767

Interaction

ith

Responsibility

tructures

Responsibility

tructures

-.063** .081**

.007 .042**

(.017)

(.017) (.014)

(.015)

Diversity

raining

-.026 -.064

-.046 .026

(.036)

(.038) (.031) (.033)

x

Responsibility

tructure

-.026 .132** .044

.040

(.042)

(.043)

(.036)

(.038)

Diversity

valuations

.294**

-.042

-.065

-.077

(.057) (.059) (.049) (.052)

x

Responsibility

tructure

-.326** .136*

.057

.009

(.061) (.063) (.053)

(.057)

Networking

rograms

-.090

.163** -.026

-.172*

(.050)

(.052)

(.043) (.046)

x

Responsibility

tructure

-.003

-.088

.073

.118*

(.056)

(.058)

(.048)

(.051)

Mentoring

rograms

.140** -.101

-.042

.127*

(.066) (.068)

(.057)

(.061)

x Responsibility

tructure

-.183*

.133

.344**

-.108

(.074)

(.076)

(.063)

(.068)

R2

(66

parameters)

.3347

.3136 .3602

.2785

Note.:

Data

shownare

coefficients rom2

seemingly

unrelated

egression nalyses

with standard

rrors

n

paren-

theses.

Responsibility

tructuresncludeaffirmative

ction

plans,diversity

ommittees nd

diversity

taff.

The

analyses

ncludeestablishment

nd

year

ixed effects andall the

controlvariables

ncluded

n

the models

present-

ed

in

Table

2

(for

coefficientsof

control

variables,

ee

Online

Supplement,

SR

Web

site:

http://www2.

asanet.org/journals/asr/2006/toc052.html).

(organization-year)

16,265;

N

(organizations)=

08.

*

p

<

.05;

**

p

<

.01

(two

tailed

test).


20/30


numberof programs n models parallel o those

presented n Table2 (results or the controlvari-

ables are availableon the Online Supplement,

ASRWebsite).We compared oefficients orthe

binary count variablesusing t tests. For white

women, the sheernumberof programsmatters;

one is better hanzero, two better hanone, and

three or more are better than two. For white

men, we find the opposite pattern,suggesting

that each additionalprogramreduces the odds

for white men. Forblackwomen, havingone or

two programs s not significantlydifferent rom

having none. Having three is significantly dif-

ferent. For black men, none of the count vari-

ables show an effect significantlydifferent rom

having no programs.Hence, for white women,

the more programs he better. For blacks, the

numberof programsmatters ess thanthe con-

tentof the programs. his is not surprising iven

that some practices n Table2 show no effects,

or even negative effects, on blacks.

Althougheach additional rogram, egardless

of content,does not always ranslatento greater

diversity,particular undlesof programsmight

operatewell together.To test this idea, we ran

(in models otherwise dentical o those in Table

2) all two-way interactionsbetween affirma-

tive action plan, diversitycommittee, diversity

staff, raining, valuation, etworking, ndmen-

toring.(The bivariate orrelations nd oint fre-

quenciesof the sevenprograms represented n

the Online Supplement, ASR Web site.) The

two-way interactionsamong training, evalua-

tion, networking, ndmentoringdid not indicate

that any pairs operatedbetter than individual

programs. But two-way interactions with

responsibility structures did render training,

evaluation, networking, and mentoring more

effective. For ease of presentation,we collapse

the three responsibilitystructures nto a single

variable, nteracting t with the four other pro-

gram variables. The second panel in Table 4

includesestimates rommodelswith these inter-

actions(results or the controlvariablesarepre-

sented on the Online Supplement, ASR Web

site).

Diversity training, evaluation, networking,

and mentoringprogramsare more effective in

firms with responsibility tructures.Withdiver-

sity trainingand evaluations, he responsibility

structure interaction positively affects white

women. With networking, the responsibility

structure interaction positively affects black

men, and with mentoring, t positively affects

black women. Note that he noninteracted ari-

able,responsibility tructure, ontinues o show

the expected effects for white men, white

women, and black men. The overall pattern s

strikingand suggests that hese authority truc-

turesrender he otherprogramsmore effective.

Yeteven with responsibility tructuresn place,

none of these programsshow the sort of con-

sistent pattern across outcomes that we find

for, say, diversitycommittee.

Do AFFIRMATIVECTIONORDERSMEDIATE

PROGRAMFFICACY?

In Table 2, we also examine whetheraffirma-

tive action enforcement shows direct effects.

Employers who sign a government contract,

and hereby ecome subject o affirmative ction

regulation,do not see increases in managerial

diversityas a directresult.When we interacted

contractortatuswith the period1971-1980, the

results did not supportearly researchers' ind-

ings

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