 

$.57 V

. 4111...:

73.13
r.

 

.
”1...? r .2. .¥ Ah
a»??? E. g.
"and: ﬁaaﬁaﬁiﬁumﬁﬂi
J15, a... R
, g ”$53.; a.
i .90." cg.
‘ .

2 .3“
. .mamvafxalrd
1mm: .3

in...

, :5}. if-..
asl ‘ “Milk:
. . !.
$)ab!~.i§h a
73‘. .3. . it).

3.3.04.3. .. .. .Jutiim

t..- 31:! ) :1! I!
.9! .5‘132-159...

‘ ,3...xr...1:.

 

 

 

.3 wanking...“ ﬁuaga. .

TP‘CQIS

 

’2 ‘ LIBRARY
mo? Michigan State
University

 

 

This is to certify that the
dissertation entitled

STUDENT ATTITUDES TOWARD AFFIRMATIVE ACTION IN
COLLEGE ADMISSIONS AND RACIAL DIVERSITY BEFORE
AND AFTER PROPOSITION 209

presented by

WILLIAM A. EDWARDS

has been accepted towards fulﬁllment
of the requirements for the

Ph.D. degree in Higher, Adult, and Lifelong
Education

 

 

12¢me a. W

Major Professor’s Signature

 

IL] HID?

 

Date

MSU is an Afﬁrmative Action/Equal Opportunity Employer

-.-.---.-.-—-.-.-t-.—

-.-.-.-.--—.—.—.—.—.-.-.- —4—-—.—-——-»-u

 

PLACE IN RETURN Box to remove this checkout from your record.
TO AVOID FINES return on or before date due.
MAY BE RECALLED with earlier due date if requested.

 

DATE DUE DATE DUE DATE DUE

 

I,
t , i .
.— ‘u I u

151310

 

 

 

 

 

 

 

 

 

 

 

 

 

 

5108 KrlProjIAocsprelelRCIDateDue.indd

STUDENT ATTITUDES TOWARD AFFIRMATIVE ACTION IN COLLEGE
ADMISSIONS AND RACIAL DIVERSITY BEFORE AND AFTER
PROPOSITION 209
By

William A. Edwards

A DISSERTATION
Submitted to
Michigan State University

in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY
Higher, Adult, and Lifelong Education

2008

ABSTRACT
STUDENT ATTITUDES TOWARD AFFIRMATIVE ACTION IN COLLEGE
ADMISSIONS AND RACIAL DIVERSITY BEFORE AND AFTER
PROPOSITION 209
BY
William A. Edwards
Using a sample of California four-year college freshmen, this study
examines attitudes toward afﬁrmative action in college admissions and racial
diversity before and after the passage of Proposition 209 in California. The
results showed an increase in support for afﬁrmative action in college
admissions, but less concern for racial diversity from 1996 to 2000. Attitudes
toward afﬁrmative action and racial diversity were less polarized in 2000 than in
1996. Whites and Asian-American students were more opposed to afﬁrmative
action in college admissions than African-American or Hispanic/Latino students.
Women and those with more liberal political ideologies were more likely to
support afﬁrmative action in college admissions and were more concerned about
racial diversity. Regression analyses was included to Show how the factors used

to predict attitudes toward afﬁrmative action in college admissions and racial

diversity changed from 1996 to 2000.

Copyright by
William A. Edwards
2008

ACKNOWLEDGMENTS

I would like to thank my committee who provided a wealth of expertise on
this study. Your support and advice was appreciated every step of the way. I
would especially like to thank my Chair, Dr. Kristen A. Renn, for guiding me
through this long process. I would also like to thank my family, especially Le’Ann

Duran, for encouraging and challenging me to complete my Ph.D.

iv

TABLE OF CONTENTS

LIST OF TABLES ................................................................................................ vii
LIST OF FIGURES .............................................................................................. ix
CHAPTER 1
INTRODUCTION .................................................................................................. 1
The Diversity Rationale ..................................................................................... 3
Afﬁrmative Action in College Admissions and the ............................................. 5
Impact on the U. S. Workforce ........................................................................... 5
The Current Study ............................................................................................. 6
The Impact of Policy on Attitudes .................................................................... 1 1
Overview of the Study ..................................................................................... 13
CHAPTER 2
REVIEW OF THE LITERATURE ........................................................................ 15
Afﬁrmative Action Deﬁned ............................................................................... 15
Altemative Strategies to Promote Diversity on Campus .................................. 16
The Development of Afﬁnnative Action in the United States ........................... 17
The California Civil Rights Initiative ................................................................. 31
The Impacts of Banning Afﬁnnative Action on Enrollment ............................... 35
California ...................................................................................................... 36
University of Texas ...................................................................................... 48
University of Washington ............................................................................. 50
University of Georgia ................................................................................... 53
University of Florida ..................................................................................... 54
Summary ..................................................................................................... 56
Attitudes toward Afﬁnnative Action .................................................................. 57
Student Attitudes toward Diversity ................................................................... 63
Conceptual Framework ................................................................................... 67
Hypotheses ..................................................................................................... 67
CHAPTER 3
METHOD ............................................................................................................ 70
Research Questions ........................................................................................ 70
Instrumentation ................................................................................................ 71
Sample ............................................................................................................ 73
Variables ......................................................................................................... 73
Dependent Variables ................................................................................... 73
Survey Year ................................................................................................. 75
Student Background Characteristics ............................................................ 76
Self-Interest ................................................................................................. 76
Method of Analysis .......................................................................................... 80

CHAPTER 4

RESULTS ........................................................................................................... 83
Mean Differences ............................................................................................ 85
Percent Distributions ....................................................................................... 87
Correlation Matrices ........................................................................................ 89
Chow’s Test and Regression Analyses ........................................................... 92
Summary ....................................................................................................... 1 01

CHAPTER 5

DISCUSSION .................................................................................................... 103
Research Question 1 ..................................................................................... 103
Research Question 2 ..................................................................................... 106
Research Question 3 ..................................................................................... 108

Gender ....................................................................................................... 1 09
Political Ideology ........................................................................................ 1 1 1
SES ........................................................................................................... 1 12
Academic Preparation ............................................................................... 1 13
Choice of College ...................................................................................... 115
Research Question 4 ..................................................................................... 116
Key Findings .................................................................................................. 1 18
Limitations ..................................................................................................... 120
Suggestions for Future Research .................................................................. 122
Implications for Promoting Diversity within Higher Education ........................ 125
Conclusions ................................................................................................... 128
APPENDICES ................................................................................................... 130
BIBLIOGRAPHY ............................................................................................. 1323

vi

LIST OF TABLES

Table 1. African-American Undergraduate Enrollments at University of California
System Institutions .............................................................................................. 37

Table 2. African-American Undergraduate Enrollments at California State
University System Institutions ............................................................................. 39

Table 3. African-American Community College Enrollments in California from
1995 - 2005 ......................................................................................................... 42

Table 4. Hispanic/Latino Undergraduate Enrollments at University of California
System Institutions from 1995 -- 2005 ................................................................. 43

Table 5. Hispanic/Latino Undergraduate Enrollments at California State
University System Institutions ............................................................................. 44

Table 6. Hispanic/Latino Community College Enrollments in California from 1995
- 2005 .................................................................................................................. 47

Table 7. Yearly Undergraduate Enrollment at the University of Texas by
Race/Ethnicity ..................................................................................................... 48

Table 8. Yearly Undergraduate Enrollment at the University of Washington by
Race/Ethnicity ..................................................................................................... 51

Table 9. Yearly Undergraduate Enrollment at the University of Georgia by
Race/Ethnicity ..................................................................................................... 52

Table 10. Yearly Undergraduate Enrollment at the University of Florida by
Race/Ethnicity ..................................................................................................... 54

Table 11. Percent Distribution of California freshmen included in the sample by
political ideology and year ................................................................................... 83

Table 12. Percent Distribution of California freshmen included in the sample for
gender and race by year ..................................................................................... 84

Table 13. Percent Distribution of total enrollment in four-year postsecondary
institutions in California gender and race by year ............................................... 84

Table 14. Mean Responses of California Freshmen for each dependent variable
by year ................................................................................................................ 86

vii

Table 15. Percentage distribution for “Afﬁrmative action in college admissions
Should be abolished” by year .............................................................................. 87

Table 16. Percentage distribution for “Racial discrimination is no longer a major
problem in America” by year ............................................................................... 88

Table 17. Percentage distribution for “Importance of helping to promote racial

understanding” by year ....................................................................................... 89
Table 18. Correlation matrix for all dependent variables ..................................... 90
Table 19. Correlation matrix for all independent variables .................................. 91
Table 20. Correlation matrix for SES and Academic Preparation ....................... 92

Table 21. Chow Tests comparing separate regression equations for 1996 and
2000 for each dependent variable ....................................................................... 92

Table 22. Regression and t-test comparisons for “Abolish afﬁrmative action in
college admissions" in 1996 and 2000 ................................................................ 93

Table 23. Regression for “Abolish afﬁrmative action in college admissions” by
racial/ethnic group ............................................................................................... 95

Table 24. Regression for “Racial discrimination is no longer a major problem in
America” in 1996 and 2000 ................................................................................. 96

Table 25. Regression for “Racial discrimination is no longer a major problem in
America” by racial/ethnic group .......................................................................... 97

Table 26. Regression for “Importance of helping to promote racial understanding”
in 1996 and 2000 ................................................................................................ 98

Table 27. Regression for “Importance of helping to promote racial understanding”
by racial/ethnic group .......................................................................................... 99

Table A1. Mean responses for each dependent variable by race
and year ........................................................................................... 129

Table B1. Mean responses for each dependent variable by race, gender, and
year ................................................................................................. 130

viii

LIST OF FIGURES

Figure 1. Variable Coding Scheme ..................................................................... 74

ix

CHAPTER 1

INTRODUCTION

The debate over afﬁrmative action, preferences granted to groups based
on race/ethnicity, gender, sexual orientation, disability status, or national origin,
has intensiﬁed over the last decade as opponents of afﬁrmative action have
challenged the practices at the state and federal level. California, Texas,
Washington, and Florida eliminated the use of afﬁrmative action in college
admissions during the 19903. Two Supreme Court cases involving admissions
practices at the University of Michigan were decided in 2003. In 2006, voters in
Michigan passed a constitutional amendment banning the use of afﬁrmative
action (Schmidt, 2007a). In November 2008, voters in Colorado and Nebraska
voted on Similar measures (Wiedeman, 2008). Although the measure passed in
Nebraska, voters in Colorado narrowly rejected the ballot initiative marking the
ﬁrst time that a state ballot initiative has failed. Policies concerning afﬁrmative
action attract particular attention and “have brought this very controversial issue
to the forefront of national debate” (Sax & Arrendondo, 1999, p. 439). Opponents
of afﬁrmative action continue to challenge race-conscious admissions policies at
the state level leaving the future of afﬁrmative action in college admissions in
doubt

Proponents and opponents of afﬁrmative action in college admissions
seem to agree that more minorities successfully earning postsecondary degrees

is a desirable outcome, but they disagree on how to get there (Crosby, lyer, &

Clayton, 2003). Opponents argue that afﬁrmative action institutionally
discriminates against people of certain races and genders. They also point to
studies in which the authors concluded that systems built using racial and gender
preferences lead to negative attribution toward racial minorities and women, by
others and themselves (Carter, .1991; Crosby et al., 2003; Heilman & Blader,
2001). Loury (1998) argued that afﬁrmative action has created a greater chasm
between middle-Class and lower-class African-Americans.

Proponents argue that there are tangible beneﬁts to society because
afﬁrmative action promotes diversity in educational institutions and the workplace
(Crosby et al., 2003). Organizations that have tapped into the potential of a
diverse workforce have seen growth in market segments and productivity.
Beneﬁts also exist for postsecondary institutions. Gurin, Dey, Hurtado, and Gurin
(2002) included over 10,000 students at multiple colleges and universities to
study the educational beneﬁts of diversity. The authors found that diversity in
higher education increases academic skills and promotes intellectual motivation
and engagement. Bowen and Bok (1998) found that students admitted under
afﬁrmative action programs were more likely than white students to be active
civic leaders.

The battle over afﬁrmative action in college admissions garners particular
attention by proponents and opponents because postsecondary education
serves as a gateway to postgraduate learning opportunities and jobs (Wise,
2005). The 1978 Supreme Court decision in the case of University of Califomia

Regents v. Bakke, which has guided U.S. afﬁrmative action policy in college

admissions for the last 30 years, articulated the link between afﬁrmative action in
postsecondary education and the availability of qualiﬁed professionals from
diverse racial and ethnic backgrounds (Pusser, 2004). However, Bakke only
provides vague guidelines about what is and is not allowed within college
admissions, leading to persistent challenges to afﬁrmative action within the
courts (Wise, 2005). In the employment sector, federal law lays out clearly the
requirements of companies, but there are far fewer stipulations about what is
required with college admissions. The lack of clarity around afﬁrmative action
policies has contributed to the complex political landscape surrounding the issue.

Institutions of higher education have a vested interest in the outcome of
the political battle over afﬁrmative action. Bans on afﬁrmative action in California,
Washington, Georgia, Florida, and Texas have resulted in a decrease in the
number of underrepresented racial minorities, especially African-Americans at
the most selective public universities (Look what happens, 2001-2002). Across
the country, colleges and universities have made substantial ﬁnancial
commitments to assembling diverse student bodies and faculty (Carnevale & Fry,
2000). Eliminating affirmative action challenges postsecondary institutions to
explore alternative mechanisms to increase the representation of minority
students in postsecondary education.

The Diversity Rationale

Colleges and universities across the country are increasingly concerned

with promoting diversity on campus in order to foster a better learning

environment for all students (Gurin, 1999; Milem & Hakuta, 2000; Witt, Chang, &

Hakuta, 2003). A diverse student body and faculty help prepare students to
succeed in an increasingly complex and diverse society (Hurtado, 2001). Without
afﬁrmative action in college admissions the elite public universities have
struggled to provide a diverse learning experience for students, harming the
educational mission of colleges and universities within the US.

The diversity rationale has only recently become the primary argument by
colleges and universities in their efforts to continue afﬁrmative action practices
(Hurtado, 2005). Afﬁrmative action was initially established as a policy to redress
long-standing social injustice by an executive order signed by Franklin Roosevelt
in 1941. The 2003 Supreme Court cases in Grutter and Gratz marked a
signiﬁcant change in the approach to defend afﬁrmative action in college
admissions. Rather than redressing past discrimination, the University of
Michigan argued that diversity beneﬁted all students and served to promote a
better educational environment for all students.

As measures against afﬁrmative action continue to succeed at the state-
level, the socioeconomic gap between Caucasian and other racial groups is
increasing in the United States (Schmidt, 2007b). Whites are signiﬁcantly
outpacing other racial groups in income, net worth (Bucks, Kennickell, & Moore,
2006), housing (Bostic, 1996), and education (Schmidt, 2007b). Though overt
forms of discrimination are less common in American, covert discrimination
toward women (Glazer-Raymo, 1999; Hall & Sandler, 1984) and racial minority

groups (Virtanen & Huddy, 1998) is persistent within the United States.

Afﬁnnative Action in College Admissions and the
Impact on the U. S. Workforce

Though public sentiment has mounted against afﬁrmative action,
demographic proﬁles demonstrate that racial minority populations, especially
African-Americans, Hispanics/Latinos, and American-Indians, are
underrepresented on college and university campuses (Morﬁn, Perez, Parker,
Lynn, 8. Arrona, 2006) largely due to inequities in the K-12 educational system
(Bali & Alvarez, 2004; Farkas, 2003; Vernez, Krop, & Rydell, 1999), but this has
made little difference to the public or the courts. Education in the US. is largely
segregated at the K-12 and postsecondary levels, pushing minority students into
lower-tier schools. Attending a lower-tiered school affects a student’s opportunity
to pursue graduate and professional degrees (Trent et al., 2003).

One role of US. colleges and universities is to prepare students to meet
the needs of the workforce (US. Department of Education, 2006). Being able to
supply the country with an adequate number of qualiﬁed professionals from all
backgrounds is critical for the economic competitiveness of locales and the
country as a whole. As public sentiment against afﬁrmative action grows, the next
decade could significantly shape the future of race-conscious policies in the
United States. Existing segregation within US. schools and neighborhoods
threatens the supply of minority or female doctors, lawyers, engineers, nurses,
and teachers. Each of these professions rely on US. public universities for

training. If banning afﬁrmative action leads to fewer minority and female

graduates in these programs the result would likely be a shortage of qualiﬁed
professionals in places with high minority populations (Glaesor & Vigdor, 2001).
The CunentStudy

Previous research has been occupied with the effects of afﬁrmative action
on admissions and enrollment, but other outcomes of banning afﬁrmative action
are relevant to this controversial policy issue. Only since 1996 when California
and Texas implemented bans on afﬁrmative action could one study the impact of
eliminating afﬁrmative action on college and university campuses. As more states
continue to eliminate afﬁrmative action, researchers will be given the opportunity
to study the impacts that banning afﬁrmative action has on enrollment, but also
on other outcomes like student attitudes.

Scholars have given considerable attention to the way in which the bans
on afﬁrmative action and the systems used in their place have affected the
representation of racial minorities in colleges and universities (Bastedo, 2003;
Brown & Hirschman, 2006; Horn & Flores, 2003; Marin & Lee, 2003; Rendon,
Novack, & Dowell, 2005; Timar, Ogawa, & Orillion, 2004). Demographics are
important, but they do not tell the whole story. Bans on afﬁrmative action likely
have signiﬁcant ramiﬁcations on employee morale (America, 1986), employee
recruitment (Vernon-Gerstenfeld & Burke, 1985), student recruitment (Hurtado,
Milem, Clayton-Peterson, & Allen, 1998), scholarships (Crosby, lyer, &
Sincharoen, 2006), student retention (Moore, 1982), fund-raising (Schmidt,

2006), and many other areas of the university.

Through the current study I add a different layer to the growing debate
about afﬁrmative action by examining how Proposition 209, which banned
afﬁrmative action in California, has impacted student attitudes toward afﬁrmative
action in college admissions and racial diversity. Though researchers have
studied student attitudes toward afﬁrmative action (Meader, 1998; Sax &
Arrendondo, 1999; Zamani, 2000), an examination of the impact of banning
afﬁrmative action on student attitudes toward afﬁrmative action in college
admissions and racial diversity is lacking. I pose the following research
questions:

1) What differences exist between aggregate attitudes of California freshman
cohorts at four-year institutions toward afﬁrmative action in college
admissions and racial diversity before and after the passage of
Proposition 209?

2) Do gender, political ideology, race/ethnicity, parent's educational
attainment, parent's estimated income, average high school grade, college
entrance exam scores, and college choice predict California freshmen
attitudes toward affirmative action in college admissions and racial
diversity at four-year institutions?

3) What differences exist between factors used to predict aggregate attitudes
of California freshman cohorts at four-year institutions toward afﬁrmative
action in college admissions and racial diversity before and after the

passage of Proposition 209?

4) If differences are found between the variables used to predict attitudes
toward affirmative action in college admissions and racial diversity, how

did these vary by racial group?

I will answer these questions by examining data from the 1996, 1998, and
2000 CIRP Freshmen Surveys. Regression equations will be constructed
controlling for student background characteristics and self-interest variables.
Using Chow’s test, I will determine whether the equations for 1996 and 2000 are
signiﬁcantly different. I will also determine whether signiﬁcant differences exist
between the beta coefﬁcients for the two equations.

The current study examines the implications of the ban on afﬁrmative
action on student attitudes toward two distinct areas: affirmative action in college
admissions and racial diversity. Measuring the impact on student attitudes toward
afﬁrmative action in college admissions can help to understand how the newest
group of voters views this controversial policy issue (Sax & Arrendondo, 1999).
The current study offers a unique contribution in this area by examining how
attitudes have changed over time across different racial groups.

The policy process has often been viewed as a one-directional process
with various actors exerting influence. However, the framing of policy events
especially by the media inﬂuences the attitudes of the citizenry (Lewis, 2001). In
this case, college students are particularly important because they are directly
impacted by the outcome of the affirmative action debate and they represent the
new generation of voters and potential political leaders. Changes in the way that

students view afﬁrmative action in college admissions may offer an indication of

what the future holds for afﬁrmative action in college admissions. If the ban has
resulted in more support for afﬁrmative action in college admissions, it may point
toward a changing public sentiment in the future. If the ban results in less support
for afﬁrmative action in college admissions, it may suggest that afﬁrmative action
is not likely to return.

Understanding the impact of banning afﬁrmative action on student
attitudes toward afﬁrmative action in college admissions is a relevant issue for
policymakers. Not only should policymakers be concerned with the effect that
afﬁrmative action policies have on enrollment patterns, but they Should also be
responsive to student attitudes toward afﬁrmative action in college admissions.
Trends in student attitudes could yield some insight into the future direction of
public opinion about afﬁrmative action in college admissions as this generation
moves into leadership roles across the country. Furthermore, because afﬁrmative
action directly impacts college students, their attitudes toward the issue should
be a primary concern for policymakers.

Measuring the change in student attitudes toward racial diversity provides
insight into how banning afﬁrmative action in college admissions impacts campus
climate. College and universities invest signiﬁcant resources into improving
campus climate through formal and informal education and efforts to recruit a
diverse student body and faculty (Chang, 2002; Gurin, 1999; Hurtado, 2001).
However, Whitt, Edison, Pascarella Terenzini, 8 Nora (2001) found that students’
openness to diversity and challenge was the most signiﬁcant predictor of

openness to diversity and challenge after three years of college. If banning

afﬁrmative action in college admissions results in less concern for racial diversity,
this may be an indication that colleges and university will have a steeper learning
curve as they work to promote racial diversity and create a positive campus
climate for all students.

As students matriculate into the workforce they will be the future leaders
who are expected to interact in an increasingly diverse society. Students are
increasingly expected to enter the workforce promoting positive racial policies
and attitudes (Meader, 1998). The attitudes of entering freshmen toward racial
diversity can serve as a baseline for colleges and universities promoting diversity
as an intended education outcome. Examining student attitudes toward racial
diversity can also provide administrators with insight into the college racial
climate (lnkelas, 2003).

Measuring student attitudes toward afﬁrmative action in college
admissions and racial diversity would also be useful in understanding the impact
that banning afﬁrmative action has on the college aspirations of students,
especially racial minorities. Though the current study does not address this issue,
research in this area could help explain why applications from minority students
drop after afﬁrmative action is banned. Horn and Flores (2003) found that
minority applications at UC-Berkeley and UCLA declined with the passage of
Proposition 209 in 1996. As of 2001, the percentage of applications from minority
populations had still not recovered to 1995 levels. Research that measures

Changes in student attitudes could be used to provide more detailed analyses

10

into the contributing factors for the decrease in flagship applications among
minority students.

There is still much to learn about a world without afﬁrmative action. Race-
conscious policies have many opponents. However, Zamani and Brown (2003)
found that people may not fully understand what afﬁrmative action is and what it
is designed to achieve. The picture should become clearer as the body of
research about the lack of afﬁrmative action or policies used to replace
afﬁrmative action grows. It could be that afﬁrmative action in college admissions
is the most effective way to ensure proportional access to postsecondary
education for racial minority groups, despite its downsides. Scholars should
explore the afﬁrmative action debate from multiple levels. This study provides
insight into one area of this very important policy issue.

The Impact of Policy on Attitudes

In the current study I hypothesize that policies banning the use of
afﬁrmative action will decrease support for afﬁrmative action in college
admissions and decrease support for racial diversity among college students in
California. Political scientists have long studied public opinion to determine how
best to Shape policy to gain the support of the public, but the policy process is
iterative (Lewis, 2001). Policies and the media attention devoted to them heavily
inﬂuence how the public views policy issues. This is especially the case with
afﬁrmative action because of the controversy that surrounds the issue (Sax &

Arrendondo, 1999).

11

Politicians are increasingly using polarizing issues like afﬁrmative action to
build successful campaigns to garner support from particular segments of the
electorate (Cain & MacDonald, 1997). AS politicians continue to use issues as a
means to increase their political clout, studies that address attitudes toward
political issues become increasingly important in explaining the policy process.
Additionally, studies like the current one can be used to explain how the policy
process impacts students, an increasingly important group of voters.

The media play a vital role in the formation of attitudes about policies in
the amount of coverage they provide to an issue and the way in which the
policies are framed. The media are capable Of casting the spotlight on political
issues and bringing them to the forefront of public attention. They are also able to
focus less attention on certain policy issues, ensuring low levels of public
awareness about those policy issues (Lewis, 2001). Kellstedt (2000) found that
media framing for racial policies has a signiﬁcant impact on policy attitudes.
When policies such as affirmative action are cast in individualistic terms, the
public tends to oppose them and when policies are framed in terms of egalitarian
values the public is more supportive. The language used for state ballot initiatives
to eliminate afﬁrmative action has been highly contested. For instance, the
wording over a measure in Missouri in 2008, which failed to garner enough
signatures to be placed on the ballot, initially referred to afﬁrmative action. A
county Circuit judge changed the wording to preferential treatment (Lieb, 2008;

Weidman, 2008).

12

The heightened attention given to Proposition 209 is important to establish
given the current goal of examining the relationship between the voter
referendum and student attitudes. The debate over race-conscious policies in
California before voters passed proposition 209 produced signiﬁcant media
attention around the issue of afﬁrmative action. Nicholson (2003) analyzed
California ballot propositions from 1956 through 2000 to determine how the
political environment impacted public awareness of the propositions. Nicholson
found that propositions concerning civil liberties like afﬁrmative action generate
Signiﬁcantly greater awareness among the public than propositions that do not
concern civil liberties. Specific to the ban on afﬁrmative action in California,
Nicholson found that 84% of voters were aware of Proposition 209 compared to a
mean of 63.97% awareness of all of the propositions included in the study.
Furthermore, organized protests on college and university campuses numbered
in the thousands (Bacon, 1996; Bowman, 1996). Given the heightened level of
awareness about Proposition 209, I will examine in the current study how student
attitudes toward afﬁrmative action in college admissions and diversity were
impacted by this controversial ballot measure.

Overview of the Study

This dissertation is divided into ﬁve chapters. Chapter Two presents the
literature relevant to the present study including a brief summary of the history of
affirmative action, the unfolding of the California Civil Rights Initiative, previous
research on the impacts of banning affirmative action in college admissions, prior

research on student attitudes toward afﬁrmative action in college admissions,

13

and previous research about the beneﬁts of diversity. Chapter Three details the
theoretical framework and methodology employed for the study. Chapter Four
presents the ﬁndings of the study. Chapter Five includes a discussion of the

results, limitations of the current study, and directions for future research.

14

CHAPTER 2

REVIEW OF THE LITERATURE

This chapter examines previous work about afﬁrmative action that has laid
the groundwork for the current study. Initially, I provide a brief examination of the
meaning of afﬁrmative action. Second, I summarize alternative strategies used
by postsecondary institutions to increase diversity. Third, I offer an overview of
some of the more important historical events related to afﬁrmative action in the
United States is presented. The account is not comprehensive, but is offered to
provide a basic overview of how this controversial issue has unfolded over the
years. Then I provide a speciﬁc examination of the California Civil Rights
Initiative. Fifth, I examine previous literature on the role of student attitudes in
shaping campus climate. Sixth, I will address previous research on the impacts of
banning afﬁrmative action in college admissions. Seventh, I provide a summary
of previous research about student attitudes toward afﬁrmative action in college
admissions. Finally, I examine previous research about the beneﬁts of diversity in
postsecondary education.

Afﬁrmative Action Deﬁned

Afﬁrmative Action was implemented in the United States during the 19605
and has been the source of ongoing debate ever since (Aberson, 2003).
Although the issue has proven divisive, the term is often confusing and
misunderstood (Zamani & Brown, 2003). Afﬁrmative action refers to both

voluntary and mandatory efforts undertaken by federal, state, and local

15

governments; private employers; and schools to combat discrimination and to
promote equal Opportunity in education and employment for all (American
Psychological Association, 1996). In the United States, afﬁrmative action policies
have primarily beneﬁted women and racial/ethnic minority groups, but disability
status, religion, and sexual preference have been the focus of afﬁrmative action
in other countries (Afﬁrmative Action, 2004).

Whether afﬁrmative action programs violate the equal protection clause of
the Civil Rights Act of 1964, which makes it unlawful to discriminate in
employment or education against any person because of one’s race, color,
religion, sex, or national origin, has been the point of contention over afﬁrmative
action (Pusser, 2004). Opponents of affirmative action would restrict such
policies to enforcing non-discrimination, but would prohibit policies that
systematically use racial preferences. Proponents argue that racial preferences
are necessary to redress past discrimination and to promote diversity within
schools and the workplace. Though afﬁrmative action encompasses a wide
range of policies related to employment and education, in the current study I
focus on race-conscious admissions in postsecondary education, which lies at
the heart of the debate over the use of afﬁrmative action in postsecondary
education (Wise, 2005).

Alternative Strategies to Promote Diversity on Campus

Postsecondary institutions employ numerous strategies to promote
diversity on campus that are not considered afﬁrmative action according to state

law. Targeted outreach efforts have been one tactic employed by universities,

16

especially those in states that have banned the use of afﬁrmative action in
college admissions. Using race as a basis for recruitment could be considered a
form of afﬁrmative action (American Psychological Association, 1997), regardless
of whether applicants are given any preferential treatment. However, targeting a
geographic area with large concentrations of minority students has been allowed
in states that have banned afﬁrmative action in college admissions. If a university
fails to meet admissions goals for a certain racial/ethnic group, it might step up
recruiting efforts by sending more recruiters to high schools with large
concentrations of that particular racial/ethnic group.

Besides the racial composition on campus, universities promote formal
and informal cross-group interactions among students on campus and diversity-
related initiatives such as diversity courses, workshops, and intergroup dialogues
(Milem & Hakuta, 2000). Living-learning communities, study-abroad, and
community service activities have all Shown positive impacts on student's
openness to diversity (Astin & Sax, 1998; Laubscher, 1994; Pike, 2002). Many
colleges and universities have special support programs for minorities as well
(e.g., Federal TRIO programs, academic support, residence life programs).

The Development of Afﬁrmative Action in the United States

Afﬁrmative action was implemented in the United States as a means to
redress the historic institutionalized discrimination against racial minority groups
and women. Federal and state laws, including the original Constitution, condoned
and perpetuated the institution of slavery and discrimination against women.

After the Civil War, slaves were granted many rights that had previously been

17

denied, but support for such policies was Sparse, particularly in the South (Witt &
Shin, 2003). Government intervention was necessary to combat discrimination
against racial minorities and women.

The ﬁrst federal afﬁrmative action program was implemented in 1934
when Harold lckes, the Secretary of the Interior under President Franklin
Roosevelt, ordered no discrimination to be exercised against a person because
of color or religion on Public Works Administration (PWA) projects. Enforcement
was lacking for the nondiscrimination policy (Anderson, 2005). So, lckes ordered
all PWA housing contractors that accepted federal contracts in cities with a large
African-American population to employ a certain percentage of African-American
workers.

The 1930s and the New Deal brought only Short-term, minor changes. For
African-Americans, policies that promoted nondiscrimination were rarely enforced
(Anderson, 2005). State governments often ignored federal guidelines with little
recourse. Women were unlikely to ﬁnd skilled or professional work, instead
usually working in food service, sewing, or housekeeping. The disproportionate
effect on African-Americans helped spur their political activity (Weiss, 1997)

In the 19403 the United States implemented the ﬁrst peacetime draft in
preparation for a possible war in Europe and Asia (Anderson, 2005). In 1941,
African-Americans comprised over 16% of enlistments that year compared to
only 10% of the US. population (US. Bureau of the Census, 1975).

Unfortunately, they were relegated to duty as messmen and ofﬁcers’ stewards.

18

President Roosevelt was pressured to end segregation in the armed forces, but
did not comply.

Instead, on June 25, 1941 President Roosevelt issued Executive Order
8802, which ordered nondiscrimination for all training and vocational programs
for jobs with government defense contractors with regard to race, creed, color, or
national origin (Witt & Shin, 2003). The executive order also created the Fair
Employment Practices Committee (FEPC) to investigate complaints of
discrimination, but the commission had little means of enforcement. Although the
order did not end segregation in the military, it provided further support from the
President to change employment practices in the United States (Anderson,
2005)

In 1945, the State of New York passed the Ives-Quinn Act, which barred
discrimination by employers and labor unions. The state FEPC was more
powerful than Roosevelt’s FEPC because it provided an enforcement
mechanism. In instances where employers were found to have discriminated
against persons based on race, creed, color, or national origin the commission
had the authority to require the employer to “take such afﬁrmative action,
including (but not limited to) hiring, reinstatement or upgrading of employees,
with or without back pay, restoration to membership in any respondent labor
organization” (Weiss, 1997, pp. 40-41).

The 19505 produced a number of court cases that prevented educational
institutions from segregating or discriminating against persons based on race. In

Sweatt v. Painter, the Supreme Court in 1950 struck down segregation in state-

19

run law schools. In 1954 the Supreme Court decided in Brown v. Board of
Education that state policies on public education supporting “separate but equal”
treatment for persons of color were unconstitutional (Moore, 2005). Though the
case concerned K-12 education, the decision applied to higher education as well
(Brown, 2001). In subsequent decisions, the Supreme Court struck down
“separate but equal” policies and laws for other publicly funded facilities (Witt &
Shin, 2003). However, southern states paid little attention to ending segregation
within postsecondary education for another ten years (Brown, 2001).

The 19605 brought increasing activism on the part of African-Americans,
particularly in the South (Anderson, 2005). Colleges and universities began
recruiting and admitting greater numbers of African-American students (Witt &
Shin, 2003). The Civil Rights Movement was gaining momentum and led to a
number of policy changes to offer opportunities to minorities in the United States.
In March 1961, President John F. Kennedy issued executive order 10925, which
required employers to take afﬁrmative action to employ without discrimination
and to treat employees fairly without regard to race, creed, color, or national
origin (Anderson, 2005). The executive order was the ﬁrst to provide penalties for
non-compliance (Witt & Shin, 2003).

Between May 13, 1963 and June 20, 1963, 127 civil rights bills were
introduced in the United States Legislature (Weiss, 1997). The Civil Rights Act of
1964 compiled many of the previous executive orders into a single bill. The bill
prevented discrimination in the workplace for private companies as well, but did

not explicitly require employers to give preferential treatment to any individual

20

based on race, color, religion, sex, or national origin (Anderson, 2005). The bill
also created the Equal Employment Opportunity Commission (EEOC), which was
charged with investigating and eliminating discrimination in private employment.
Title VI of the act restricted the awarding of federal funds to segregated K-12
schools and postsecondary institutions (Brown, 2001).

A year later, President Lyndon Johnson issued Executive Order 11246,
which superseded previous executive orders and became the standing rule on
afﬁrmative action for the next several decades (Anderson, 2005). The order
reinforced non-discrimination, but added new requirements on contractors and
subcontractors with more than ﬁfty employees and contracts worth $50,000 or
more requiring them to periodically submit a written report about minority
participation on their projects and their afﬁrmative action plans (Weiss, 1997). In
1967, President Johnson extended afﬁrmative action provisions to include sex
discrimination.

Also in 1967, the EEOC issued a report which claimed that current
measures to diversify the workforce and end discrimination were having little
effect on most businesses. So, the federal government began to focus on the
construction industry and devised plans for speciﬁc urban areas. In 1969, speciﬁc
targets were laid out by the Department of Labor to increase African-American
participation on construction projects from 5% in 1969 to between 19% and 26%
by 1973 for Philadelphia (Witt & Shin, 2003). Similar plans’ were implemented in

Washington, DC, Seattle, St. Louis, Atlanta, and San Francisco.

21

During the 19705, numerical formulas were increasingly used by the
courts in instances where companies had been found guilty of discriminating in
the workplace. The judgments were viewed as temporary preferences for
minority applicants rather than quotas, which were prohibited under Title VII of
the Civil Rights Act Of 1964 (Weiss, 1997). The use of speciﬁc quantiﬁable
remedies was a necessary response to the failure of non-discrimination policies
that lacked successful enforcement mechanisms.

In 1971, the Department of Labor issued Order #4 and later Revised
Order #4, which expanded the Philadelphia Plan to all federal contractors
(Anderson, 2005). The orders removed all references to proportional hiring that
previous directives had included and required all contractors with 50 or more
employees and contracts of $50,000 or more to submit a written afﬁrmative
action plan for hiring minorities and women within 120 days of the start of a
contract (Weiss, 1997; Witt & Shin, 2003). The plans were to account for the size
of the minority population in the local region and demanded that contractors
establish specific goals and timetables within the plan. At the time, the policy
affected a quarter million contractors and 20 million workers or about a third of
the entire US. labor force.

During the same year, the US. Supreme Court ruled in Griggs v. Duke
Power Company that using a paper-and-pencil test as part of the criteria for
hiring was a violation of the Civil Rights Act of 1964 if the test was not deemed a
business necessity (Weiss, 1997). Because African-Americans had been denied

access to education and were more likely than whites to live in impoverished

22

conditions, the use of such tests had an adverse impact on minority applicants. In
1977, Eleanor Holmes Norton was appointed to the Chair of the EEOC by
President Jimmy Carter. The commission had a backlog of 130,000
discrimination complaints to investigate. In an effort to reduce the backlog,
Norton ordered the agency to Shift from investigating individual complaints to
investigating broader patterns and practices.

The US. Supreme Court directly addressed the issue of afﬁrmative action
in college admissions for the ﬁrst time in 1978 with the University of Califomia
Regents v. Bakke decision (Newman, 1989). Allan Bakke, the plaintiff, had been
denied admission to the University of California, Davis medical school, which
reserved 16 spots in each entering class out of 100 total incoming students for
African-American, Latino, and Asian-American students who had experienced
racial discrimination (Witt and Shin, 2003). Bakke, a white applicant, sued the
university Claiming that the admissions plan violated the equal protection clause
of the Fourteenth Amendment and Title VI of the Civil Rights Act of 1964 (Moore,
2005). Bakke sought an injunction against the special admissions program that
gave preferences to minority applicants and demanded admission to the medical
school

The court was sharply divided with four justices siding with the plaintiff,
four siding with the university, and Justice Powell siding with the plaintiff, but
refusing to end afﬁrmative action at the university. Six separate opinions were
issued in the case, but Justice Powell’s decision became the opinion of the court

(Pusser, 2004). Powell viewed the set-aside slots as quotas, which he viewed as

23

unconstitutional. Powell applied the strict scrutiny standard, which required the
plan to have a compelling objective and racial classification had to be necessary
to achieve the objective. Set-aside spots did not meet this standard for Powell,
but he claimed that race could be used as a “plus factor” that treated each
applicant as an individual (Newman, 1989). This became the standard for
afﬁrmative action programs in college admissions for the next two decades.

During the 1980s, the Reagan Administration took a number of steps to
curtail previous efforts for afﬁrmative action (Weiss, 1997). Justices Scalia and
Kennedy, open opponents of afﬁrmative action, were appointed to the Supreme
Court. Clarence Thomas was appointed to chair the EEOC in 1982 and reverted
to addressing individual complaints of discrimination rather than addressing
systemic patterns of discrimination. Numerical goals and timetables were
gradually eliminated as requirements for government contractors.

In 1986 the Supreme Court ruled in Wygant v. Jackson Board of
Education. The Jackson board of education developed an afﬁrmative action
program that had achieved gains in employing more African-American teachers,
but layoffs soon became necessary. Historically, the board would lay off the least
senior members of the faculty, but doing so would have resulted in the
termination of too many of the African-American teachers (Anderson, 2004). So,
the board modiﬁed the policy, splitting the teachers into white and African-
American groups and laying off the same percentage of teachers from each
group. The Supreme Court ruled that societal discrimination did not provide a

compelling objective and that the policy would be unconstitutional even if the

24

goals were permissible (Newman, 1989). The court held that the loss of an
existing job was more intrusive than denial of a future opportunity in college
admissions or in hiring.

In 1987 U. S. v. Paradise was decided by the Supreme Court. A federal
district court had previously found that Alabama had discriminated against
African-Americans in the hiring of state trooper positions. The district court
ordered that for every white promoted to corporal the Alabama Department of
Public Safety Should promote an African-American as long as qualiﬁed applicants
existed (Newman, 1989). In a 5-4 decision, the Supreme Court upheld the
previous ruling. The case is the closest the Supreme Court has come to
approving racial quotas (Witt & Shin, 2003).

In 1989 the court ruled in Wards Cove v. Antonio and in City of Richmond
v. Croson. In the former, the Supreme Court’s ruling moved the burden of proof
from the employer to the plaintiff in demonstrating discrimination has occurred
(Anderson, 2004).. In the latter, the Supreme Court ruled that the Minority
Business Utilization Plan used by the city, which “required prime contractors on
construction projects funded by the city to subcontract at least 30% of the dollar
amount of the contract to one or more Minority Business Enterprises (MBES). An
MBE was a business that was at least 51% owned by minority group members”
(Witt & Shin, 2003, p.196). The court found that the program was not narrowly
tailored and that the City failed to provide any evidence that past racial
discrimination had actually occurred. Systemic racism was clearly not recognized

by the Supreme Court as a justiﬁcation for afﬁrmative action.

25

In 1990, the Supreme Court ruled in the case of Metro Broadcasting, Inc.
v. Federal Communications Commissions (FCC). The FCC was sued for favoring
minority applicants for broadcast licenses (Witt & Shin, 2003). The FCC Claimed
that minority ownership was one factor among several that it used in awarding
licenses. At the time, white ownership in the industry was at 98%. The court ruled
in favor of the FCC declaring that diversity on the airwaves was an important
governmental objective and that proof of remediation was not necessary.

In United States v. Fordice (1992) the Supreme Court for the ﬁrst time
since Brown v. Board of Education in 1954 issued a ruling evaluating whether a
state had sufﬁciently “addressed its afﬁrmative duty to dismantle prior de jure
segregated systems of higher education” (Brown, 2001, p. 50). The ruling
mandated the adoption of desegregation compliance policies including
admissions policies to provide greater opportunities for African-American
applicants to attend the state’s historically White institutions (Olivas, 2005). To
the Court’s satisfaction, the State of Mississippi responded by broadening
admissions criteria to include high school grades and rank in class and also
implementing summer precollegiate programs that offer conditional admissions
and remedial instruction.

The court also concluded that the State of Mississippi Should permit
historically Black institutions to develop more high-demand specializations and
graduate programs. New programs in allied health professions, engineering,
social work, urban planning, and business administration were awarded to

historically black colleges, increasing the opportunities for African-Americans in

26

Mississippi to pursue these high—demand ﬁelds. In total, the state appropriated in
excess of $245 million over 17 years for the new programs at three historically
Black institutions.

In 1995, the Supreme Court handed down its ruling in Adarand
Constructors Inc. v. Pen'a. Adarand, a white-owned construction company, was
not awarded a subcontract for a project in which they submitted the lowest bid.
Instead, a minOrity-owned business was selected by the general contractor
(Pusser, 2004). A financial incentive existed for the general contractor to select
the minority-owned business. The Supreme Court overturned the Metro
Broadcasting ruling holding that governmental afﬁrmative actions should be
subject to strict scrutiny like other afﬁrmative action programs. However the court
did not rule on whether this case met strict scrutiny, choosing to remand the case
back to the lower court. Justice O’Connor wrote the opinion of the court,
declaring that race-conscious policies aimed at responding to societal
discrimination against minority groups could be allowed as long as the program is
narrowly tailored. The Supreme Court suggested that the lower court consider
whether the governmental interest was compelling, whether race-neutral
alternatives could achieve the desired ends, and whether the remedy would be
Short-lived.

The 19903 also brought increasing scrutiny to the use of afﬁrmative action
in college admissions. Because of a history of school segregation in the K-12
system and exclusion from many postsecondary institutions, colleges and

universities had employed afﬁrmative action in admissions to increase the

27

representation of minority and female students (Moore, 2005). The use of
afﬁrmative action in college admissions has become a prime target for opponents
of race-conscious policies. Voter referendums and Supreme Court cases have
cast a spotlight on the issue and have led to major policy changes for California,
Texas, Florida, Georgia, Washington, and Michigan.

In 1996, California voters passed proposition 209, which prohibited
discrimination against or preferential treatment based on sex, color, ethnicity, or
national origin in public employment, public education, or public contracting. In
the same year, the Fifth Circuit Court of Appeals issued its ruling in Hopwood v. '
Texas (Moore, 2005). The plaintiff claimed that the University of Texas Law
School had lower requirements for minority applicants than it had for white
applicants. The Court of Appeals decided that Bakke had no legal standing
because it did not have a majority decision. The court ruled that diversity was not
a compelling state interest and the university failed to prove the need for
afﬁrmative action. The ruling effectively forced institutions in Texas to eliminate
afﬁrmative action from their admissions policies.

In 1997, the University of Georgia was sued by eleven students, seven
whites and four African-Americans, who claimed that afﬁrmative action led to
racial segregation in the public university system (Moore, 2005). The court found
that the University of Georgia used an unconstitutional admission policy from
1990 to 1995 by giving preferences to African-Americans. By this time the
university had abandoned the use of afﬁrmative action. So, the ruling had no

impact, but the judge ruled anyway to prevent the policy from being reinstated.

28

In 1998, voters in Washington passed a referendum banning the use of
afﬁrmative action in hiring, contracting, and college admissions (Witt & Shin,
2003). Led by the Center for Individual Rights and Ward Connerly, the same man
responsible for leading the opposition against afﬁrmative action in California, the
referendum easily passed with 54% of voters supporting the ban. Although the
ban in Washington drew much less attention than in California, it reinforced
perceptions that more and more states would experience challenges to their
afﬁrmative action policies (Healy, 1998).

Building on the momentum against afﬁrmative action, Ward Connerly
threatened to push a Similar campaign in Florida. Florida’s Governor, Jeb Bush,
preempted such a measure by offering a plan to and afﬁrmative action in college
admissions and to admit the top 20% of each high school graduating class to at
least one of the public universities in the state (Moore, 2005). Similar plans had
been implemented in California and Texas in an attempt to maintain diversity
without the use of race-conscious admissions policies. The plan was adopted by
the Board of Regents and afﬁrmative action in college admissions was quickly
eliminated in Florida. 1

In 2003, the Supreme Court ruled in two cases involving the University of
Michigan (Moore, 2005). In Gratz v. Bollinger the court ruled that the
undergraduate admissions policy was not narrowly tailored and violated the
Fourteenth Amendment’s Equal Protection Clause. The policy employed a point
system that required the applicant to achieve a score of 100 points to be

admitted. Underrepresented racial and ethnic minorities were automatically

29

awarded 20 points, which the court found did not allow for individual
consideration.

In Grutter v. Bollinger the court ruled in favor of the University of Michigan
Law School holding that a racially and ethnically diverse student population is a
compelling societal interest (Green, 2004). Furthermore, the court determined
that the admissions policy was narrowly tailored such that race was used as one
factor, but was not the deﬁning feature of a student’s application. As long as the
policy avoided formulas and each applicant was viewed as an individual, the
court ruled that race could be used in college admissions.

The University of Michigan cases were major milestones in the history of
afﬁrmative action in college admissions. At a time when afﬁrmative action
programs were being dismantled in a number of states and public sentiment had
moved largely against such policies, the Michigan cases could have marked the
end of afﬁrmative action in college admissions. Instead, the Supreme Court
reaffirmed Bakke by ruling that afﬁrmative action in college admissions served a
compelling interest by increasing diversity on college campuses.

However, it is not clear how long the court will continue to uphold the use
of afﬁrmative action in college admissions. Justice O’Connor, writing for the court
in Grutter, indicated that in 25 years afﬁrmative action should not be needed. The
articulation of a speciﬁc time-frame that the court expects afﬁrmative action to be
unnecessary i3 profound (Moore, 2005). If the number of racial and ethnic
minorities fails to increase substantially over the next 25 years, the court may

reconsider the time-frame that was established. At the same time, the court may

30

hold institutions of higher education to this time-frame. Either way, the inclusion
of the time-frame certainly made it clear that the Supreme Court eXpectS that
affirmative action will be abandoned in the near future.

In November 2006, voters in Michigan passed Proposition 2, which
banned the use of racial and gender preferences by public colleges and other
state agencies (Selingo, 2006). In November 2008, voters in Nebraska passed a
similar measure (Wiedeman, 2008). During the same election cycle, voters in
Colorado narrowly defeated a measure eliminating afﬁrmative action in the state,
marking the ﬁrst time that a state measure banning afﬁrmative action did not
pass voters in the state. There are likely to be additional state measures in the
future challenging the use of afﬁrmative action in college admissions and
employment.

The California Civil Rights Initiative

California has held a prominent position in the afﬁrmative action debate
over the years. The University of California had pursued aggressive afﬁrmative
action policies since the early 19603 despite facing substantial legal challenges
(Timar, Ogawa, & Orillion, 2004). The landmark Bakke case pushed California
into the public spotlight and continues to be the litmus test for race-conscious
admissions policies since 1978. However, during the 19903 several forces led to
more public resentment of afﬁrmative action policies and California again was
pushed into the spotlight as voters passed a measure to ban afﬁrmative action

for public hiring, contracting, and college admissions.

31

In 1991, the California State Assembly considered legislation that would
have required the freshman classes in California’s public colleges and
universities to reﬂect the ethnic composition of the class that graduated from the
state’s public high schools (Chavez, 1998). The bill was vetoed by Governor Pete
Wilson, but it heightened debate around the use of racial preferences in college
admissions. Most importantly, the California Association of Scholars, a
conservative organization, became a vocal opponent of the bill and would later
draft Proposition 209 in response.

In 1993, Governor Pete Wilson, concerned about the increasing burden
that immigrants were placing on social services, set out to curb immigration in the
state and the cost of supporting such a high immigrant population (Chavez,
1998). The highlight of Wilson’s initiative was Proposition 187 in 1994, which
outlawed public beneﬁts for illegal aliens and their families in California, signaling
to some an increased level of resentment toward minority populations in the
state. Proposition 187 helped pave the way for the California Civil Rights Initiative
(CCRI), which eliminated the use of preferential treatment by the state to anyone
based on race, sex, color, ethnicity, or national origin (Mukherjee, 2000).

The eventual authors of the CCRI, Thomas Wood and Glynn Custred, had
tried for two years to place a measure on the ballot to eliminate state-sponsored
afﬁrmative action (Mukherjee, 2000). In 1994, they incorporated a political
committee, California Against Discrimination and Preferences, to organize in
support of the CCRI. The mid-term elections that year saw unexpected victories

for Republicans and the passage of Proposition 187 (Raza, Anderson, &

32

Custred, 1999). Although proposition 187 was overturned by the courts, it
heightened tensions over government policies targeting minority groups in the
state.

In 1995, Ward Connerly successfully convinced Governor Pete Wilson,
who had been a long-time proponent of afﬁrmative action, to reverse his position
on the matter (Timar et al., 2004). Wilson issued Executive Order W-124-95 on
June 1, 1995, which required the University of California to end preferential
treatment and promote merit instead. On July 20, 1995, the University of
California Board of Regents adopted SP-1, which eliminated the use of race and
gender in the admissions process (Mukherjee, 2000). Even though the Board of
Regents eliminated afﬁrmative action, SP-1 mandated that the university system
remain committed to maintaining a diverse student body through means other
than affirmative action (Timar et al., 2004).

In 1996, the political landscape had sufﬁciently Changed with the passage
of proposition 187 and SP-1. The public was now clearly leaning against
programs that provided assistance to immigrants and minority groups. Custred
and Wood wrote the referendum to mirror that of the 1964 Civil Rights and made
no mention of afﬁrmative action (Raza, Anderson, & Custred, 1999). Opponents
sued to have the term afﬁrmative action inserted into the measure. The trial judge
ordered the words inserted, but the ruling was overturned by the appellate judge.

Out of fear that SP-1 might be overturned, Ward Connerly agreed to chair
the initiative to get Proposition 209 on the ballot (Chavez, 1998). Connerly

offered the initiative a black man opposed to affirmative action, a direct

33

connection to Governor Wilson, and ties to wealthy potential supporters of the
initiative. With his support and that of the Governor, the initiative had ample
political and ﬁnancial support to succeed (Raza, Anderson, & Custred, 1999).

In November 1996, California voters passed proposition 209 with 54% of
the vote, making it illegal for the state to discriminate or give preferential
treatment to anyone based on race, sex, color, ethnicity, or national origin
(Mukherjee, 2000). Exit polls indicated that the measure was opposed by 76% of
Latinos, 74% of African-Americans, and 61% of Asian-Americans (Hajnal &
Louch, 2001). However, there were only 6 out of 58 counties where more voters
opposed the measure than supported it.

The proposition was immediately challenged in court by a group of CCRI
opponents. A temporary injunction was issued in December 1996 when the court
sided with the CCRI opponents that the measure violated the plaintiff’s
constitutional rights (Raza et al., 1999). However, a three-judge panel of the
Ninth Circuit US. District Court of Appeals ruled in April 2007 that the measure
did not violate the equal protection clause and the full Ninth Circuit Court
declined a request to delay implementation. The US. Supreme Court denied a
motion to block enforcement of the measure and in 1998 Proposition 209 took
effect (Timar et al., 2004). Passage of the proposition led to numerous other
lawsuits as particular practices came under increased scrutiny. Proposition 209
was a major blow to California’s selective universities, which now faced an uphill
battle in recruiting and enrolling minority applicants. California universities

continue to seek ways to increase minority enrollment without the use of

34

afﬁrmative action through increased outreach and geographically tiered
admissions (Rendon, Novack, & Dowell, 2005).
The Impacts of Banning Afﬁnnative Action on Enrollment

Signiﬁcant attention has been focused on the impact that banning
afﬁrmative action has had on minority enrollment in California, Washington,
Georgia, Texas, and Florida. Each state has distinct differences in the way that
afﬁrmative action was banned and in the way the state has responded in trying to
ensure adequate minority representation within higher education institutions after
eliminating afﬁrmative action in college admissions. However, in the absence of
afﬁrmative action public universities with selective admissions have struggled to
increase minority enrollments, especially African-American enrollments, as a
whole (Look what happens, 2001-2002).

For instance, African-American undergraduate enrollment dropped at the
University of California at Berkley (UC-Berkeley) from 1,200 in 1995 to 829 in
2005. At the University of California at Los Angeles (UCLA) African-American
undergraduate enrollment dropped 1,433 in 1995 to 799 in 2005 (University of
California, n.d.). Over the same time period UC-Berkley dropped from 2,696 to
2,484 Hispanic/Latino undergraduates while UCLA dropped from 4,009 to 3,788
(University of California, n.d.). At the University of Texas, African-American
enrollments dropped from 1,469 in 1995 to a low of 1,277 in 1999 (University of
Texas, 2005). Only in 2005 did African-American enrollments reach 1995 levels
with a total of 1,482 African-American undergraduates. Hispanic/Latino

enrollment declined slightly from 5,143 in 1995 to a low of 5,106 in 1999 before

35

steadily increasing to 5,919 in 2005. Though I seek to move beyond enrollment
data to examine the impact that the ban on afﬁrmative action in California has
had on student attitudes toward afﬁrmative action in college admissions and
racial diversity, it is important to consider the impact of the bans on minority
enrollment because it signiﬁcantly contributes to the ongoing debate across the
country about afﬁrmative action.
Califomia

Though minority enrollments have increased in some institutions within
California, the ﬂagship universities have faced an uphill battle in attempting to
enroll minority students (see Table 1). For instance, while UC-Berkeley and
UCLA have seen decreases in the number of African-American enrollments, UC-
lrvine has increased from 353 in 1995 to 453 in 2005. UC-Riverside has
increased from 382 to 957 over the same time period. As minorities have been
pushed down to less prestigious universities and colleges, higher education
scholars, elite institutions, and policymakers have become increasingly
concerned about the unequal stratification of minority enrollments (Bowen & Bok,
1998; Bastedo, 2003). Trow (1999) questioned the distinctions that have been
made between the value of a ﬂagship education and an education from other
publicly-funded institutions. However, having fewer minority students within
ﬂagship institutions limits the structural diversity and the educational beneﬁts of a
diverse undergraduate student body at those institutions (Hurtado, Dey, &

Trevino, 1994).

36

SEQmBchEOEOzaooéauodoc:.3353? Eot meow .w .62 mEEo 3559
{$33.21 2:0 850 .mLEoEmO .6 3902:: utmum new .338“. .ﬂcmoaw 0: co Ema ocm meEam .8539? E9“. .302

 

 

3.0.8 33$ 33$ 33: 339 33$ 33% 33$ 338

55. «mm mt. Em Em $3 5... SR mum 88
332 §3$ 33$ 33: 339 33$ 33$ 33$ 33$

5: mg iv mew mg 3% 8m 38 mm» .38.
33$ 33$ 33$ 33: 339 33$ 33$ 33$ 33:

mew... mum we. :3 «8 N9. 8... 8m «mm 88.
33$ 33$ 33$ 3...: 33m: 3.~.$ 33$ 33$ 3.5.:

2.3. new mow 9N mum 3. 38 Ra 2m 88
§Q$ §3$ 3.m..$ 33: 333 3.~.$ 33$ 3.5m: 33$

«9}. RN 3... «mm m: 5m So 23 Km 58
3.3: 33$ 33$ 3.3: 3.39 3.o.$ 33$ 33: 3.3:

at}. :8 one :N 80 v8 «3 moo; 08 88
A338 33$ 33$ 33: 33.9 33 : 33$ 3.5: 3.5:

38... RN 3N3 SN «3 EN 93 $3 moo; 82
33a 33$ 33$ 3k. : 33m: 35$ 33$ 3.3m: 3&9

3:... SN «3. EN Ev SN 5m 83 8: 82
33$ 33$ 33$ 36$ 3.3m: 31$ 33$ 33m: 33m:

83 RN 5. mom 8.. mmm 8m 3.} EN; 32
338 33$ 333$ 333$ 33m: 33$ 33$ 3.0.9 33m:

NE... SN owe 8m 8.. Rm «8 E} 53 82
3.3: 33$ 33$ 333$ 33m: 33$ 33$ 3.0.8 339

.20.... E as. Rm mmm 8m 5m 85 com. 82
E993 ~20 EmEmm ommﬁ. wu_m._m>_m was: m_>mo (1.0: NEOxEm Emm>

OD macaw mucmm cmw
.28

 

«cow—5.3:. 533w «ED—.30 ho E2825. «a 3coE=oEm 83.32932: :ao_._oE<-cao_.a< .v 03a»

37

The elite public universities stand the most to lose in their efforts to
promote diversity as states consider banning afﬁrmative action. Even if the
difference in the education one would receive between two institutions is merely
perception, these perceptions are important. Such perceptions are likely to
permeate the workforce. If employers perceive a difference between educational
institutions, then the value of an education from a particular institution becomes
concrete in the form of employment, wages, and advancement opportunities
(Alexander, 2000).

The total percentage of African-Americans enrolled in California colleges
and universities has decreased across the University of California (UC) System,
the California State University (CSU) System, and the California Community
Colleges (CCC) System. The UC System dropped from 4% African-American
undergraduate enrollment in 1995 to 3% in 2005. The CSU System dropped from
6.3% in 1995 to 5.9% in 2005. The CCC System dropped from 7.8% to a low of
7.3% from 2000-2001 before climbing to 7.6% in 2005. Across the two public
university systems and the community college system, the percentage of African-
Americans enrollments have dropped from 1995 levels.

UC-Berkeley and the UCLA have severely struggled to enroll a critical
mass of African-American and Hispanic/Latino students. Both in raw numbers
and in percentages of total undergraduate enrollment, the representation of
African-Americans (see Table 1) on the UC and the UCLA campuses have
declined since afﬁrmative action was banned. UC-Berkeley dropped from 5.9%

African-American enrollment in 1995 to 3.5% in 2005. UCLA dropped from 6% in

38

00050005..:OEQOEéOBom00.008.33.530?
So: meow .9 22. u0>0::0: 6900:5260 5:03P”: 5026000009: $28300 .0083”: 0000 520:0. ES“. .082

 

 

39

33F: §30$ 3.0.: 33$ 3.0.3 3.0.0: 3.3: 33$
003 0000 000 00 30 003 000 F0 080
330: 330$ 33: 3.0.: 3.0.0: 3.0.0: 3.0.: 3.0.0:
0FOF 0000 000 00 000 0: 0t 00 300
3.0.0: 330$ 33: 3.0.: 3.0.0: 3.0.0: 3.0.: 3.00:
F F0F 0000 EN 00 000 00... RF 00 080
3.0.0: 330$ 33: 33: 3.0.0: 3.0.0: 3.0.0: 33$
E2 0000 000 0 :0 F00 00F 0F 0000
3.0.0: 3.0.5 3.0.: 3.0.0: 3.0.0: 3.0.0: 3.0.0:
:00F 0000 30 - BF. 20 00F 00 F000
3.0.FF: 330$ 33: 3.0.0: 3.0.0: 3.0.: 33$
:3 03.0 000 - 000 000 00F t 08...
3.0. F F: 3.30: 3.0. F: 3.0.0: 3.0.0: 3.0. F: 3. F .0:
000F 0000 000 - 000 000 NFN 0F 000F
3.0. F F: 330$ 33$ 3.0.0: 3.0.0: 33 F: 3.0.:
NSF 00F0 000 - 000 000 000 00 002
3.0.0: 330$ 33$ 3. F .0: 3.00: 3.0. F: 3.0.0:
0F0F :00 0:0 - 000 $0 :00 0F :00F
33F: 3.0.0$ 33$ 3.0.0: 3. 0.0: 3.0.0.: 330:
F00F 0000 000 - 000 000 000 0F 82
3.0.FF: 3.0.5 3.0.$ 339 3.0.0: 3.0.0: 3.0.0:
F0: 008 000 - R0 F00 20 0F 002
50m 000.”: 051 32:0 00:02 20:39.0: 0:089: 8050 05.. >Emumo< 80>
56:02:: N03560: 56:02:: .0520 .5_0:02:: 56:02:: :8 55:02:: 08::02
0:0:0 50.02:: 90:0 50:02:: 20:0 0:60:20: 0:0:0 0:80.00
02.00.00 0:0.0 02.300 90:0 02.2000 000:0 0:50:20:
0_Eo:__0o 0_Eo:__0o 9500.00 0:60.00

 

0:023:05 £33m 3.0.02.5 35m 02:02.00 00 8:05:25 30:35:09.: 50:23.53; .N 030...

 

 

3.0.0: 330% 33F: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 30E 3.0.0: 3.0.0:

000 000 002 00: 0000 SF 000F 0F0F 00FF 000 0000
330: 3.0.0: 3.0.FF: 3.0.0: 3.0.: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.0:

000 000 008 000F 0000 00F 002 00F «00 000 0000
3.0.0: 3.0.0: 3.F.FF: 3.0.0: 3.0.: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 33...:

000 000 000F 000F 0000 00F 000F 0000 000 000 0000
3.0.0: 3.0.0: 330: 3.0.0: 3.0.0: 3.0.: 33: 3.0.0: 3.0.0: 3.0.:

000 000 00: 000F 0000 00F 000F 0000 000 :0 0000
3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.: 3.30: 3.0.0: 3.0.0:

000 00F 000F 002 0000 0FF 0F0F 0FF0 0.0 00 F000
3.F.0: 3.0.0: 3.0.0: 3.0.0: 3.0.: 3.0.0: 3.0.: 3.0.0: 3.0.0: 3.0.0:

000 00F 03F 000F 00F0 00F 0F0F 0000 0K 000 0000
3.0.0: 3.0.0: 3.0.0: 3.0.0: 33: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.F.0:

00F 00F «08 000F 0000 00 000F 0000 000 000 000F
3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.: 33: 3.0.0: 3.0.: 3.0.0: 3.0.0:

000 F0F 000F 000F 0000 00 000F 0000 000 000 002
3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.: 3.30: 3.0.0: 3.00: 3.30:

000 00F 00FF 000F 090 00 0F0F 3:0 000 000 000F
3.0.0: 3.0.0: 3.0.0: 3.0.0: 3.0.: 3.F.0: 3.0.0: 3.0.: 3.0.0: 3.0.0:

F00 F0F F00F 000F .030 F0 002 00 F0 000 000 002
3.0.0: 3.0.0: 3.00: 3.30: 3.0.: 3.30: 3.0.0: 3.0.: 3.0.0: 3.0.0:

000 0F F 0 F0F 03F 000F 00 002 0000 000 0 F0 000F
0:06:05 08:05. 052058 0::0E0:00w 090:5:02 ﬁmm 02%.0. :000m 5:93: 050:”: :00>
56:02:: :0m :0m 56:02:: 56:02:: >0:0::os_ 00.: 0:0: 56:02:: 56:02::

0:06 56:02:: 56:02:: 0:0:w 20:0. 56:02:: 56:02:: 56:02:: 0:0:w 0:0:w
02:00.00 0:06 0:06 0.50:..00 0.59.00 0:06 0:06 0:06 0.50....00 0.58.00
0.52.00 0.50:..00 0.0.0:..00 0.50:..00 0.50:..00

 

0:033:00. E303 36:02:: 0:05 0.58200 :0 0::0E=0::m 30:00:92.0: :00:0E<-:00_::< 40.2030 030...

40

 

 

3&9 3a.: $3.3 3.8.3 3.8.9 3.3 3.8.8 3%.:
828 9; P 5 58 88? 88 8 m 88
3.3V 3.8.: $03 3&9 3.3 3.8.3
888 m3 m8? 39 39 m8 - - 38
31.9 3.8. : 38$ 3.8.3 38.8 3.8.3
888 a? an: m E 88? N8 - - 88
3.3V 3.5.: 3:.s 3.. is 3.5.8 3.3V

88 83 m8 8m 8v «8 - - 88
3.8.3 3:.3 3.3; 3.98 35$ 3003
B88 SF 88? 39 82 2: - - S8
3&9 3:.3 §o$ 3.8.8 38.3 388v
088 mm: 82 82 82 m9 - - 88
300.9 33. 5 3.5.3 31.9 300$ §QNV
v8 8 9: £2 £9 83 82 - - 82
3.8.9 3.6.3 3.8.3 3.8.8 3%.: 30m. 5
888 82 8: 8t 83 :3 - - 82
3.8.9 3.3.3 300$ 3.8.3 3.8.3 3.8.:
888 we 8.2 22 am: 8; - - 32
3°09 3.8.8 §o$ 3.8.9 3.3.3 3%. c
888 8 mm: 8m: 89 8F - - 82
3.8.9 3°03 300i Agog 3.8.9 3.8. 3
«B8 38 8: on: 82 8F - - 82
Eek 3652c: 56.02:: 3652:: 3352.5 3652:: Io<m.r mEgoi .mm>

99m 29m 99m 99m 93m 3998 58853:.
mEocow .30.. cmw 820:9”. 0920 cam 6.88:: 939.8
:8

 

23:322.. Eougm £2265 33m £502.50 an 858:2:m Evacuate: :aotoE<-:aoE< .APEoou N 2:3.

41

Table 3. African-American Community College Enrollments in California from 1995 -
2005

 

 

Year Enrollments Percent of Total Enrollments
1995 166145 7.8
1996 173742 7.8
1997 181499 7.7
1998 186517 7.7
1999 191393 7.5
2000 193273 7.3
2001 205862 7.3
2002 21 1342 7.5
2003 190844 7.5
2004 191677 7.6
2005 194522 7.6

 

Note: From “Custom Data Reports," California Postsecondary Education Commission,
retrieved July 18, 2008 from http://www.cpec.ca.gov/OnLineData/0nLineData.asp

1995 to 3.2% in 2005. With black residents accounting for 7.4% of California’s
population, it is clear that the ﬂagship institutions do not sufﬁciently represent the
racial demographics of the state (US. Census Bureau, 2002). However, across
California the drop in percentages of African-American enrollments is
pronounced. Even with California’s top 4% plan that automatically admits
students graduating in the top 4% of their high school class, African-American
enrollments have not sufﬁciently recovered to their levels before afﬁrmative
action was banned in the state.

Hispanics/Latinos saw signiﬁcant gains in California undergraduate
enrollments in the 19905 sparked largely by the increase of Hispanics/Latinos
within the general population of the state. As a percentage of total population,
Hispanics/Latinos increased from 20.5% to 32.4% (U.S. Census Bureau, 1990;

US. Census Bureau, 2002). Within the UC System the percentage of

42

.bmuﬁwgmciaoncaooE:00.000:.3333? Eat meow .m >05. 05.5 09050. 300.603 05
:0 SEQ 6.80.300 .8 3802:: ntﬂm 0:0 5.300“. .mucmuam o: :0 £00 0:0 meEam .028sz9 E9”. .802

 

 

 

38...: 3.3: 3.8.5 3.8: 3.2.8: 3.3: 3.8.8: 3.8.8: 3.8.8:
8.8 83 88.8 88.8 88.8 28.8 8.8 88 83.8 88
32.8: 38...: 3.5: 3.8: 3.8.8: 3.3: 3.8.8: 3.3: 3.8.8:
88.8 88.2 82.8 88 88.8 88.8 8.8 88..., 28 88
88.8: 38...: 38.0: 3.88: 3.8.8: 33: 3.8: 3.3.8: 3.8.8:
838 83 88.8 88.8 «8.8 28.8 8.8 88.8 88 88
3.8.8: 3.8.8: 3.8.8: 3.8.8: 3.8.8: 3.3: 88.8: 38...: 3.8.8:
888 2.3 28.8 83 88.8 :8 .88 88.8 88 88
3.8.8: 8.8.8: 3.3: 3.8.8: 3.8.8: 83: 3.0.8: 3.3: 3.8.8:
88.2 83 28.8 883 88 88.8 83.8 88.8 88 88
3.8.8: 3.8: 3.8.8: 3.0.8: 3.2.8: 3.3: 3.8: 3.3.: 3.8.2
88.: 83 E8 83 83.8 83 83 8.8 88. 88
3.8: 3.8.8: 3.8: 32.8: 3.88: 3.88: 3.8.8: 3.3: 3.8.8:
88.: 82 88 83 02.8 83 83 88.8 28.8 82
3.8.8: 3.8: 3.8.8: 3.8.8: 3.8.8: 3.3: 3.8.8: 3.3: 3.3:
88.2 28.2 «8.8 83 83 83 83 88 88.8 82
3.8.8: 38...: 3.8.8: 3.8: 3.8.2: 3.8.2: 3.8.0: 3.8.8: 3.8:
8:: 83 28.8 83 88.2 83 :3 28.8 :8 B2
3.8: 3.8.8: 3.8.8: 3.3: 3.8.2: 3.8.8: 3.8.8: 3.8.8: 3.8.8:
8.: 83 8.8.8 23 83 :3 83 33. 28.8 82
3.8: 3.8.8: 3.5: 3.3: 3.8.8: 3.8.8: 3.3: 3.88: 3.8.8:
80.: 88.2 83 88.2 83 83 80.8 88. 88.8 82
829m N20 EmEmm 3105 09202”: 05>... m_>mn_ So: 3.03:3 50>
03 Scam 8me cam

38

88:82

E0... 0:033:00. E803 02:05.80 .0 3.0.03.5 an £=0E=0Em 3030290003 00333230.: .v 0.03

43

00006005....080005:c0.>0m.0o.0000.3§auc
E9. meow .2. 22. 00>0...0. 60.00.3000 00....0000m b0000000.00n. 0.0.0.500 .9500: 0.00 E2030. E9... 0.02

 

 

44

38.2: 3.8.8.: 3.8.2. 3.3: 3.3: 3.8.8. 38.: 38.:
82 28 22 80 88 88 22 8 88
3.3: 3.3.8. 3.8.2. 38¢: 38.8. 38...: 38.: 3.0.:
82 2.3 22 8.. 88 8:. 82 8 88
3.3: 3.3.8. 3.3.2. 33.8: 3.18. 33: 3...: 3.8.0.
82 82. 82 08 28 88 Rt 8 88
3.8.: 38.8. 3...: 3.3: 3.8: 3.8: 38.: 3.3.0.
82 8:. 22 8. 88 S8 :2. 3. 88
3...: 3...... 3.: 3.8.: 3.3.8. 3.0.8: 3.82. 38.0.
82 89. $2 - 22 88 82 3 88
83: 38.8. 3.0.: 3.3: 38.8: 3.8: 38.5
32 .28 82 - 82 82. 82 8 88
38.2. 3.3: 3.8.: 3.3: 3.3: 3.3: 38.:
82 88 22 - 22 88 82 8 82
3.0.2. 38.0: 3.8.: 38.: 3.3: 3.8.8: 3...:
82 88 82 - 22 88 88 8 82
38.2. 38.8: 3...: 38¢: 3.3: 3.0.2. 38.:
82 2.8 2.2 - 22 88 88 8 82
3.82. 38.0: 3...: 3.3: 3. 8.8. 38.02. 3...:
82 88 82 - 82 88 88 8 82
3.3: 3.3: 38.: 3.3: 3.0.2. 3.3: 38.0.
22 :8 B2 - 82 88 88 8 82
40m .08. 0:... 00:5 02.0.0. _0cc0..0 20:28.3 25an 8.0.00 0:... :00 #E0000< .00>
5.0.025 ~0amc_E0n_ 5.0.025 5.0.025 5.202;: 5.0.025 5.0.025 0.2m 05:85.
0.90 3:985: 0.08 20.0 055:8 0.9m 25528.. 05:82.... 052:8
055:8 08.0 055:8 055:8 055:8 0.90 055:8 055:8

 

00033.00... E205 3.0.02.5 0.3m 0.0.0....00 .0 0.:0E..0.:m 0.050.903... 2.843.000»... .m 0.00...

 

 

45

3°28: 3&5: @052 $03: @0184 3°25 @0222 @033 3.23: 303%
SK 3: 8% 3% RE 82 SE 38 «N8 38 meow
$33 55.58: 55.32 55.3: 55.205 523$ @053: @038 3.3.3 @033
88 33 «mom $8 .88 :8: 8mm 28 38 $2: 38
A5555 55.3: A228: 303: £53: £3.82 3%.va €035 55.33 £555
:8: 8m: :53 25 mm 5 : 5: $3 $8 82 85 88
@028: 3&2: 55.33 55.3: @253 A553: 3%.va 555$ 303$ @0553
38 mm? 83 £8 8% 52: £8 8: as: $3 88
$5.02: 55.3: £33 55.3: 55.33 3°23 3053 55.35 @033 55.0.5
3: S: F 8% 2.3 82 E 83 SE 88 8mm 58
3&8: 55.3: 55.0.8: §§c 55.2mm: $5.8: $5.22 @028: @058: 555.8:
58: 8: $8 55 58 Km 8% RE 8% :5 88
55.35 303: 323$ 523: £558 308% £5.35 @058: :55. E @028:
33 8a 88 8mm 28 on: £3 £5 8?, 82‘ m8:
@033 300.5 £533 303: @553 300.3: @053: 555.2: 55.38 555.018:
:3 mom E8 83 2% 22. $5 $8 53, 3% 82
3%. E 3°20: $00.2: A23 : 50$. :5 3°28 3&va £65 5 303 3 3028:
52 mt $8 8% 5% 8m mum» ammo $8 .88 52
555.8: 300.5: 3%. a: 303 5 £5.03 3&8: £5. E 3.5.5 5 3° : .m 5 @023
25: B: 38 $8 $8 am at 38 82V 33. 82
Aged : A23: 3°53: 3°05 : 3&8: 30m. E 3°28: 3&2 5 30$ 3 @038
mm: : 8m 8% 33 38 mi 82 m E 8 S 2 5. 82
85.555 8255. 059553 958908 535552 >mm 8.5% commm cotw=:n_ 9.me 55>
5.25253 cmw :8 56.52:: $52525 5:99:05. 8.. 98.. 55:52:: 5652::
22m .5295: .5295: 22m 22m .5295: .5295: .5295: 22m 22m
552:8 22m 22m 552:8 552:8 22m 22m 22m 552:8 552:8
552:8 552:8 552:8 552:8 552:8

 

23:332.. 5336 3.33:5 38m $502.50 «a 8:08:25 533M925: oEﬁdaEaanE .5203 m «in...

 

 

858: 822: 3°53: $2.2: 32.8: 303: 822: 822:

3.8 m Fm 88 85 8% 85 2 F x: 88
32.8: :82: 58.2: 822: 58.8: $05.2:

228 2» 2.8 R8 88 8:: - - 38
@028: 88: 5.8.2: :222: £58: A082:

2.25 “Fm 88 88 28 So - - 88
828: 82a: 3°22: :5. v. F F: 58.2: 508.2:

8va 88 22¢ 88 BS 5:: - - 88
58.8: 303: :82: 83: £58: 85::

288 28 88 35 88 23 - - 58
58.2: 308: 3&2: @092: 32.8: 8::

282 So 2% 88 $8 8: - - 88
303 F: 52.2 303 F: 502. F F: @058: 30::

~38 80 25 88 38 8m - - 82
:82: 5028: 32.2: 3%. F F: @028: :28:

$20 85 88 m2: 8% 80 - - 82
303 F: :88: 5°88 F: 88. F F: @058: 58.2

280 28 m8: mmFm 8%: to - - 32
3°52: 5°85: @022: 83: 822: :23:

$20 85 88 2 Fm $8 :5 - - 82
3°22: 58¢: 58.2: 58.2: @052: 5.8.5:

28m 80 88 88 88 m8 - - 82

Eek 3252c: 9252:: 36:52:: 3652:: 29m E2525 Io<m._. mEmaoE 58>

22m 22m 22m 850 :8 22m 2258 6555525
NED—how wmoﬁ cmw oow_ocm:u_ 5.09:3... 939mm:
cmw

 

28:33»:— Eﬁmam b.2533: 33w 3:3an «a 3:55:95m 8868902: 0534:0282: .3230: m 29:...

46

Table 6. Hispanic/Latino Community College Enrollments in California from 1995 -
2005

 

 

Year Enrollments Percent of Total Enrollments
1995 166,145 22.5
1996 173,742 23.1
1997 181,499 23.4
1998 186,517 23.9
1999 191,393 24.4
2000 193,273 25.2
2001 205,862 26.3
2002 21 1,342 26.5
2003 190,844 27.2
2004 191,677 27.8
2005 194,522 28.5

 

Note: From “Custom Data Reports,” California Postsecondary Education Commission, retrieved
July 18, 2008 from http://www.cpec.ca.gov/OnLineData/OnLineData.asp

Hispanics/Latinos grew only .3% (z = 3.178, p<.01) from 13.7% in 1995 to 14% in
2000 (see Table 4). UC-Berkeley dropped from 2,696 Hispanic/Latino
undergraduates in 1995 to a low of 2,175 in 2001, reaching 2,484 in 2005. UCLA
dropped from 4,009 Hispanic/Latino undergraduates in 1995 to a low of 3,499 in
2000, reaching 3,788 in 2005. Neither institution has recovered to 1995 levels.
The largest gains in Hispanic/Latino enrollment have been within the CSU
System (see Table 5) and within the community colleges (see Table 6). The
percentage of Hispanic/Latino undergraduates within the CSU System
signiﬁcantly increased (z = 46.102, p<.001) from 17.5% to 21.8% from 1995 to
2005 (California Postsecondary Education Commission, n.d.). The percentage of
Hispanic/Latino students within the CCC System increased from 22.5% to 28.5%

(2 = 148.053, p<.001) from 1995 to 2005. However, the lower number of

47

Table 7. Yearly Undergraduate Enrollment at the University of Texas by Race/Ethnicity

 

 

Year African- Hispanic/La American Asian White Total
American ’ tino Indian Enrollment Enrollment
Enrollment Enrollment Enrollment (Percent) (Percent)
(Percent) (Percent) (Percent
1995 1,469 5,143 131 4,213 22,961 35,086
(4.2%) (14.7%) (4%) (12%) (65.4%)
1996 1,479 5,247 156 4,459 23,345 35,789
(4.1%) ( 14.7%) (4%) (12.5%) (65.2%)
1997 1,353 5,234 182 4,783 24,219 36,861
(3.7%) (14.2%) (5%) (13%) (65.7%)
1998 1,311 5,154 182 5,104 24,200 37,203
(3.5%) (13.9%) (5%) (13.7%) (65%)
1999 1,277 5,106 166 5,372 24,007 37,159
(3.4%) (13.7%) (4%) (14.5%) (64.6%)
2000 1,298 5,152 175 5,695 24,341 38,162
(3.4%) (13.5%) (5%) (14.9%) (63.8%)
2001 1,335 5,236 164 6,124 24,199 38,609
(3.5%) (13.6%) (4%) (15.9%) (62.7%)
2002 1,372 5,459 175 6,616 24,453 39,661
(3.5%) (13.8%) (4%) (16.7%) (61.7%)
2003 1,400 5,505 148 6,541 23,254 38,383
(3.6%) (14.3%) (4%) (17%) (60.6%)
2004 1,405 5,647 158 6,399 22,326 37,377
(3.8%) (15.1%) (4%) (17.1%) (59.7%)
2005 1,482 5,919 162 6,270 21,588 36,878
(4%) (16.1%) (4%) (17%) (58.5%)

 

Source: University of Texas, Ofﬁce of Institutional Research, Statistical Handbook 2004-2005
Hispanic/Latino students within the UC System further demonstrate how minority
students are being concentrated at the less prestigious institutions within
California.
University of Texas

In 1996, the Fifth Circuit Court of Appeals ruled against the University of
Texas (UT) Law School in the case of Hopwood effectively eliminating the use of
afﬁrmative action in admissions by public universities in Texas (Pusser, 2004;

Raza et al., 1999). In an effort to implement a race-neutral alternative Governor

48

George W. Bush signed legislation that automatically admitted the top 10% of
graduates from each high school in Texas to their top choice public university in
the state. The number of African-American undergraduates at the University of
Texas dropped from 1,469 in 1995 to a low of 1,277 in 1999 (see Table 7). Only
in 2005 did the number of African-American undergraduates reach 1995 levels.
The number of Hispanic/Latino undergraduates dropped from 5,143 in 1995 to a
low of 5,106 in 1999 before climbing to 5,919 in 2005.

Compared to the state population, which is comprised of 12% African-
Americans and 32% Hispanics/Latinos (US. Census Bureau, 2002), enrollment
at the University of Texas as of 2005 comprised of 4% African-Americans and
16.1% Hispanics/Latinos. In contrast, Asians, which account for only 3.1% of the
population of Texas, have seen enrollments steadily increase over the past
decade. Asians now comprise 17% of undergraduate enrollments.

In 2003, the Supreme Court ruled in Grutter and Gratz, which supersedes
the Hopwood decision. Whereas Hopwood effectively reversed Bakke within
Texas, Grutter reafﬁrming the Bakke ruling that race could be used as one factor
to evaluate an individual for college admissions. The Grutter ruling reestablished
afﬁrmative action as one tool that postsecondary institutions can use to promote
diversity on campus. As a result, the University of Texas began considering race
as a factor once again in admissions. A consequence of the 10% plan has been
the inundation of UT by those who ﬁnish in the top 10% of their class (Fischer,
2005). Nearly three-quarters of admissions offers to Texas applicants are made

on the basis of class rank alone. In 2003 and 2004 freshmen outside of the top

49

10% outscored those within the top 10% on the SAT. As the ﬂagship institution in
the state, the implications of a lower average SAT score could demonstrably
impact the national prestige of the University of Texas.

University of Washington

Voters in Washington approved Proposition 200 in 1998, which banned
the use of racial preferences by any agency of the state government (Moses,
2001). After the ban minority enrollments dropped at the research universities in
Washington (Brown & Hirschman, 2006). African-American undergraduate
enrollment at the University of Washington fell from 832 in 1,995 to a low of 678 in
2000 (University of Washington, n.d.). Only in 2000 did the number of African-
American undergraduates return to 1995 levels. The number of applications
received by the University of Washington (UW) has rebounded to the levels
before l-200 partly due to an increase in outreach programs to high schools and
community groups to increase the number of applications submitted from
minority students (Brown & Hirschman, 2006).

The drop in admissions at UW is particularly noteworthy because the
university is not academically selective at the undergraduate level. Approximately
80% of all students who apply to the UW-Seattle campus are admitted. Under
such circumstances one would expect that African-American enrollments would
only be marginally impacted, but the drop in enrollments and applications to the

University of Washington indicate that African-American undergraduates are

50

Table 8. Yearly Undergraduate Enrollment at the University of Washington by
Race/Ethnicity

 

 

Year African- Hispanic/La American Asian Other Total
American tino Indian Enrollment Enrollment
Enrollment Enrollment Enrollment (Percent) (Percent)
(Percent) (Percent) (Percent

1995 832 935 264 5,033 17,774 24,838
(3.3%) (3.8%) (1%) (20.2%) (71.6%)

1996 838 984 274 5,190 17,942 25,228
(3.3%) (3.9%) (1%) (20.6%) (71.1%)

1997 841 1,022 410 5,697 17,852 25,822
(3.3%) (4.0%) (1.6%) (13%) (69.1%)

1998 744 1,032 371 5,639 17,760 25,546
(2.9%) (4.0%) (1.5%) (22.1%) (69.5%)

1999 699 980 327 5,705 17,927 25,638
(2.7%) (3.8%) (1.3%) (22.3%) (69.9%)

2000 678 935 318 5,888 18,026 25,845
(2.6%) (3.6%) (1.2%) (22.8%) (69.7%)

2001 695 956 299 6,081 18,829 26,860
(2.6%) (3.6%) ( 1.1%) (22.6%) (70.1%)

2002 733 944 297 6,605 20,449 29,028
(2.5%) (3.3%) (1%) (22.8%) (70.4%)

2003 731 985 289 6,855 19,002 27,862
(2.6%) (3.3%) (1%) (24.6%) (68.2%)

2004 799 1,018 313 7,031 18,571 27,732
(2.9%) (3.7%) (1 .1%) (25.4%) (67%)

2005 840 1,161 331 7,054 18,102 27,488
(3.1%) (4.2%) (4%) (17%) (65.9%)

 

Source: University of Washington, Ofﬁce of Institutional Studies, Student Headcount by Ethnicity
and Student Level

turning to other institutions. Brown and Hirschman (2006) attributed the drop in
minority enrollments to a discouragement effect. They argued that students’
plans for college were likely affected by their expectations for success in the
admissions process and in completing their degrees. Students with any doubt
about their chances to be admitted or to succeed at UW likely opted for a less

prestigious institution where they perceived greater chances for success.

51

Table 9. Yearly Undergraduate Enrollment at the University of Georgia by Race/Ethnicity

 

 

Year African- H lspanic/La American Asian White Total
American tino Indian Enrollment Enrollment
Enrollment Enrollment Enrollment (Percent) (Percent)
(Percent) (Percent) (Percent
1995 1,604 214 33 636 20,551 23,572
(6.8%) (9%) (.1%) (2.7%) (87.2%)
1996 1,570 227 36 643 20,092 22,946
(6.8%) (1%) (2%) (2.8%) (87.6%)
1997 1,516 250 33 702 20,418 23,236
(6.5%) (1.1%) (.1 %) (3%) (87.9%)
1998 1,499 257 36 698 20,724 23,479
(6.4%) (1 .1%) (2%) (3%) (88.3%)
1999 N/A N/A N/A N/A N/A N/A
2000 1,425 350 40 796 21,344 24,213
(5.9%) (1.4%) (2%) (3.3%) (88.2%)
2001 1,337 370 35 857 21,965 24,829
(5.4%) (1.5%) (.1%) (3.5%) (88.5%)
2002 1,247 392 42 967 22,079 24,983
(5%) (1.6%) (.1 %) (3.9%) (88.4%)
2003 1,214 439 35 1,069 22,410 25,415
(4.8%) (1.7%) (.1 %) (4.2%) (88.2%)
2004 1,153 439 39 1,134 22,009 25,019
(4.6%) (1.8%) (2%) (4.5%) (88%)
2005 1,351 480 46 1,139 21,738 25,204
(5.4%) (1.9%) (2%) (4.5%) (86.2%)

 

Source: U. S. Department of Education, National Center for Education Statistics, Integrated
Postsecondary Education Data System (IPEDS), Peer Analysis System.

The situation is worse in graduate admissions at UW. African-American

graduate enrollment dropped from 184 in 1995 to a low of 156 in 2001 at the

University of Washington (see Table 8). Between 1998 and 2000 African-

American graduate enrollments dropped by 12%. African-American enrollments

at the law and medical schools were poor before the ban on afﬁrmative action

and have seen little effect since the ban (Look what happens, 2001-2002). In

1998 and in 2000, there was only one African-American in the ﬁrst-year law

52

school class. In 1998 and in 2001, there was only one African-American in the
ﬁrst-year medical school class. Though undergraduate numbers may suffer as a
result of banning afﬁrmative action, the net effect on graduate numbers and
eventually employment may have more severe consequences.
University of Georgia

The University of Georgia did not admit an African-American student until
1961 (Cooper, 2000). But in 1996, the state attorney general, Michael Bowers,
used the Hopwood ruling in TeXas as justiﬁcation against the use of afﬁrmative
action in college admissions even though the ruling had no bearing in Georgia
(Kahlenberg, 1996). He ordered the state university system to stop using
afﬁrmative action in college admissions. In 2000, a federal court struck down the
use of affirmative action at the University of Georgia in the case of Johnson v.
Board of Regents of the University of Georgia. African-American enrollment at
the University of Georgia dropped each year from 1,604 in 1995 to a low of 1,153
in 2004 before jumping to 1,351 in 2005 after the Grutter decision (see Table 9).
Hispanic/Latino enrollment has steadily increased from 214 in 1995 to 480 in
2005. Still, with African-American students comprising only 5.4% of
undergraduate enrollment compared to 29.9% of the state population and
Hispanic/Latino students comprising only 1.9% of undergraduate enrollments
compared to 7.5% of the state population, the University of Georgia does not

reﬂect the racial demographics of the state (US. Census Bureau, 2002).

53

Table 10. Yearly Undergraduate Enrollment at the University of Florida by Race/Ethnicity

 

 

Year African- Hispanic/La American Asian White Total
American tino Indian Enrollment Enrollment
Enrollment Enrollment Enrollment (Percent) (Percent)
(Percent) (Percent) (Percent
1999 2358 3401 133 2079 24108
(7.13%) (10.29%) (40%) (6.29%) (72.92%) 33060
2000 2725 3601 174 2248 24231
(7.98%) (10.54%) (.51 %) (6.58%) (70.95%) 34154
2001 2712 3632 182 2291 24388
(7.87%) (10.54%) (53%) (6.65%) (70.79%) 34450
2002 2905 3877 187 2390 24586
(8.23%) (10.99%) (53%) (6.77%) (69.68%) 35282
2003 2993 4159 177 2407 24389
(8.51%) (11.82%) (50%) (6.84%) (69.30%) 35191
2004 2983 4182 152 2382 24050
(8.55%) (11.99%) (44%) (6.83%) (68.94%) 34883
2005 3133 4485 125 2560 24366
(8.72%) (12.49%) (35%) (7.13%) (67.84%) 35918

 

Source: University of Florida Factbook

University of Florida

In November 1999, Florida Governor Jeb Bush announced his plan to

eliminate afﬁrmative action in Florida and replace it with the Talented 20 Program

(Marin & Lee, 2003). The initiative guarantees admission to one of the

institutions in the State University System (SUS) for those students graduating

within the top 20% of their class who complete the required high school credits

and submit their ACT or SAT scores. Due to mounting pressure from Ward

Connerly who had successfully led campaigns in California and Washington to

ban affirmative action, Governor Bush preempted court involvement or a ballot

referendum by implementing his One Florida Initiative (Lookwhat happens, 2001-
2002). He touted the measure as a way to increase minority
enrollment at Florida’s colleges and universities without resorting to racial

preferences (Marin & Lee, 2003).

54

The University of Florida (U F) serves as the state’s ﬂagship campus with
total enrollment in excess of 50,000 students. Unlike other ﬂagship institutions
UF has managed to steadily increase the representation of racial minority groups
on campus (see Table 10). However, the increases may be more a function of
the proactive outreach efforts of UF rather than the Talented 20 program. Marin
and Lee (2003) conducted an analysis of the Talented 20 program and found that
minority students were not being assisted as much as enrollment numbers might
appear. The percentage of white Talented 20 applicants increased from 70.4% in
2000 to 72.9% in 2001 indicating that the program actually decreased the
number of minority applicants automatically granted admission to a SUS
institution.

The reasons for the University of Florida’s success probably lies in its
heavy use of race-targeted recruitment of minorities rather than the Talented 20
program, which has largely been ignored by UF (Marin & Lee, 2003). However,
while Hispanic/Latino enrollment has increased at SUS institutions, likely due to
the surge in Hispanic/Latino students enrolled in the state’s primary and
secondary schools, African-American enrollment has not kept pace (Chandler,
2005). Though overall African-American enrollment at SUS institutions held fairly
steady in terms of real numbers, as a percentage of total freshman enrollment
the representation of African-Americans has decreased 11% since 2002. The
enrollment of American Indians at the University of Florida has been historically

low, but there has been a steady decline from 182 in 2000 to only 125 in 2005.

55

Summary

Except for the University of Florida, the other ﬂagship institutions have
struggled to increase the representation of African-American students on
campus. Raw numbers dropped as a result of bans on afﬁrmative action at the
flagship public universities in California, Texas, Washington, and Georgia. Even
more telling are the drops in percentage of the overall student population. As of
2005, California and Georgia still had not recovered to 1995 levels for African-
American undergraduate enrollment. As of 2005, Texas and Washington had just
returned to 1995 levels, but the percentage of African-American undergraduates
has still not recovered to 1995 levels.

Enrollment for Hispanic/Latino students at the ﬂagship public universities
where afﬁrmative action has been eliminated has fair better than enrollment for
African-American students largely because of the rising Hispanic/Latino
population. However, UC-Berkeley and UCLA are clear exceptions.
Hispanic/Latino enrollment has still not recovered to 1995 levels in raw numbers
and as a percentage of total enrollment Hispanics/Latinos fell from 13.2% in 1995
to 10.6% in 2005 at UC-Berkeley and from 16.9% in 1995 to 15.3% in 2005 at
UCLA. With such a large Hispanic/Latino population, the drop in Hispanic/Latino
enrollments at UC-Berkeley and UCLA are striking. Texas and Florida with large
Hispanic/Latino populations as well have faired much better at enrolling

Hispanics/Latinos at the state flagship institutions.

56

Attitudes toward Afﬁnnative Action

A large body of research exists about public opinion and there is a
growing body of research on student attitudes toward afﬁrmative action.
However, current research has not adequately addressed how attitudes toward
afﬁrmative action have changed over time (Citrin, 1996). Additionally, no previous
studies were uncovered that examined the impact of afﬁrmative action policies on
student attitudes toward affirmative action. In order to understand the
signiﬁcance of the currently study, it is important to look back at the previous
work concerning public opinion and student attitudes toward afﬁrmative action.

Public opinion research has revealed a great deal about how Americans
view afﬁrmative action. Citrin (1996) points out that the public is opposed to both
racial discrimination and to racial preferences. The public often views afﬁrmative
action programs with suspicion believing that afﬁrmative action is the equivalent
of using quotas and perceiving that reverse discrimination should be of greater
concern than discrimination against minorities. This lack of trust among the public
of government and academic afﬁrmative action programs has contributed a great
deal to the recent dismantling of afﬁrmative action in several states across the
country.

A number of factors that relate to attitudes toward afﬁrmative action have
been explored. Citrin (1996) explains that:

Recent research concerning the underpinnings of attitudes toward

afﬁrmative action has centered on the relative importance of four main

motives: (1) self-interest, deﬁned broadly as the perceived impact of a

57

policy on both one’s own well-being and on the wealth, status, and power

of one’s ethnic or gender group; (2) individualist values, in the sense of

how strongly one is committed to a notion of equity that deﬁnes fair
treatment as rewarding people on the basis of individual merit rather than
social back-ground; (3) beliefs that attribute racial inequality to personal
causes such as lack of motivation or ability rather than to structural
discrimination; (4) sheer prejudice, that is hostility to a particular group
whose members are stereotyped as lacking requisite skills or character

traits. (pp. 45-46)

Suthammanont and Peterson (2004) argue that prejudice and political
belief primarily drive attitudes toward afﬁrmative action and often at the expense
of one another. Feldman and Huddy (2005) found that white liberals had higher
levels of resentment toward scholarship policies targeted at other races. For
white conservatives, political ideology was a more signiﬁcant factor in predicting
attitudes toward the scholarship policy.

Kinder and Winter (2001), using data from the 1992 National Election
Study, found a substantial difference in the way whites and African-Americans
view a number of different political issues. Many of the different views could be a
result of self-interest or socioeconomic status, but the researchers found that
African-Americans also hold more favorable views toward social welfare
programs that do not directly benefit them than do whites. Kinder and Winter

argued that the gaps between African-Americans and whites are based in

58

fundamental philosophical differences on the role of government in this country.
Afﬁrmative action policies are certainly at the forefront of this divide.

Aberson (2003) conducted a path analysis and found that self-interest and
the structure of affirmative action policies are signiﬁcant predictors of support for
afﬁrmative action. Aberson included only 114 college students and the model
was not robust enough to account for many other factors than inﬂuence attitudes
toward afﬁrmative action, but the model showed some promise in predicting
student attitudes toward afﬁrmative action.

For the current study I draw on the work of Sax and Arrendondo (1999),
who used data from the 1996 Cooperative Institutional Research Program (CIRP)
Freshman Survey to examine how attitudes toward afﬁrmative action in college
admissions varied by race and gender. The sample for the study consisted of
277,850 ﬁrst-time freshmen across the United States. The researchers grouped
variables around three constructs: self-interest, political ideology, and racial
affect. They found that men were more likely than women to oppose the use of
affirmative action in college admissions. For socioeconomic status and academic
preparation, the researchers found that for whites, Asian-Americans, and
Mexican-Americans those with higher socioeconomic status or higher levels of
academic preparation are more strongly opposed to afﬁrmative action in college
admissions. For African-Americans those with higher socioeconomic status and
those with more academic preparation were less likely to oppose afﬁrmative

action in college admissions. Sax and Arrendondo (1999) also found that across

59

all racial groups those with more conservative political views were more likely to
oppose afﬁrmative action in college admissions.

Zamani (2000) followed up on the work of Sax and Arrendondo using the
1996 CIRP Freshman Study data to analyze community college students’
attitudes toward affirmative action in college admissions. Zamani found that
gender, age, parents education, political view, likelihood to go on to obtain a
bachelors degree, and GPA were all related to support for afﬁrmative action in
college admissions. Zamani did not address the extent to which community
college students differ from other postsecondary students in their attitudes
toward affirmative action in college admissions.

Meader (1998) included over 2000 responses to the Midwest College
Study to examine factors that contribute to white and African-American students’
attitudes toward afﬁrmative action. Meader found that white students whose
parents had lower educational levels were more likely to oppose race—based
policies. Using Astin’s lnput—Environment-Output model, Meader found that
environmental variables had a more signiﬁcant impact on student attitudes
toward affirmative action than input variables. Taking a black studies course,
being involved on campus, and living on campus were all shown to have a
signiﬁcant relationship with attitudes toward afﬁrmative action for at least one of
the racial groups.

Kane and Kyyro (2001) conducted a study to determine the relationship
between education and beliefs about racial and gender inequality. They found

that greater levels of education for white men, white women, and African-

60

American men were more likely to reinforce views that promote racial inequality.
African-American women with higher levels of education were more likely to
possess views more critical of racial and gender inequality. Speciﬁc to afﬁrmative
action, white men were more likely to oppose afﬁrmative action while African-
American women were more likely to support afﬁrmative action.

lnkelas (2003) studied Asian Paciﬁc American (APA) students’ attitudes
toward afﬁrmative action and found that more than any other ethnic group APA
students were more likely to support afﬁrmative action in principle, but to
disapprove of the use of afﬁrmative action in practice. lnkelas also found that
APA women were more likely to support afﬁrmative action than were APA men.
lnkelas also found a positive relationship between those APA students majoring
in social science and humanities disciplines and their views of the potential
fallibility of the dominant ideology and the racial climate around them. Finally,
lnkelas found that APA students who engaged in more conversations about
diversity with their peers and students who had greater exposure to University-
sponsored diversity programs were more likely to support afﬁrmative action.

Andolina and Mayer (2003) studied the differences between members of
Generation X, those born between 1961 and 1981, and previous generations in
their attitudes toward race and racial equality. The researchers used data from
the General Social Survey and the American National Election Study and found
that members of Generation X were more likely to support school integration
efforts, but less likely to support afﬁrmative action. The shift in values

experienced by Generation X is further evidence that the political environment

61

around afﬁrmative action has become complex. Americans continue to
demonstrate their belief that increasing the representation of racial minorities in
higher education or in the workplace is not the way to increase diversity.

Rothman, Lipset, and Nevitt (2002) surveyed students, faculty, and
administrators across the nation to compare their views on diversity and
afﬁrmative action. The researchers found that about 66.7% of the students,
compared to 34% of the faculty and 26% of the administrators opposed
afﬁrmative action. The majority of the student participants would have grown up
with affirmative action programs used in college admissions and in hiring.
However, the researcher did not distinguish between those participants living in
states where afﬁrmative action was no longer employed. Students attending
school in Washington, California, Florida, or Texas may have different views
about afﬁrmative action than those in other states.

The previous research indicates that certain groups view afﬁrmative action
in signiﬁcantly different ways. Differences can be found with respect to race
(Meader, 1998; Sax & Arrendondo, 1999; Zamani, 2000), gender (lnkelas, 2003;
Kane & Kyyro, 2001; Sax & Arrendondo, 1999; Zamani, 2000), socioeconomic
status and parental education (Sax & Arrendondo, 1999), and generations
(Rothman, Lipset, & Nevitt, 2002). In the current study I will carry this further to
see how the introduction of the ban on afﬁrmative action in California impacted

student attitudes toward afﬁrmative action in college admissions.

62

Student Attitudes toward Diversity

Diversity has become a primary educational outcome for many campuses
because it helps maintain a positive campus climate and provides students with
opportunities to engage with people from other cultures (Hurtado et al., 1998).
Campus climate - the current patterns, perceptions, and attitudes about
organizational life, and culture, the deeply held meanings, beliefs, and values of
institutional members - deﬁne academic institutions (Peterson & Spencer, 1990).
Campus climate is particularly impacted by the perceptions and attitudes that
students, faculty, and staff have about diversity on campus. Additionally, diversity
has become a primary goal of many postsecondary institutions as they seek to
prepare students to succeed in an increasingly complex and diverse society
(Hurtado, 2001).

With increased resources being channeled into activities designed to
promote diversity on campus, more attention has been given to race, ethnicity,
and cultural diversity within higher education (Antonio, 2001). Supporters and
critics have formed polarized views about the likely outcomes of diversity efforts
in postsecondary education. Still, little empirical research exists to document the
relationship between diverse experiences on campus and the development of
college students (Antonio, 2001; Hurtado, 2001). Furthermore, the research that
has been conducted exists within insular intellectual communities divided by
methodologies and theoretical perspectives (Bobo & Fox, 2003).

Only recently have researchers established the beneﬁts of diversity

(Antonio et al., 2004; Bowen & Bok, 1998; Gurin, 1999; Gurin, 2002; Whitt,

63

Edison, Pascarella, Terenzini, & Nora, 2001). Researchers have demonstrated
positive relationships between diversity and a number of outcomes for college
students, including civic outcomes (Astin, 1993; Bowen 8 Bok, 1998; Hurtado,
2001), learning outcomes (Antonio et al., 2004; Gurin, 1999; Hurtado, 2001;
Milem & Hakuta, 2000), student retention (Chang, 1996; Smith & Associates,
1997), and satisfaction with college (Astin, 1993; Chang, 1996). Diversity efforts
also improve the campus climate (Springer, Palmer, Terenzini, Pascarella, &
Nora, 1996) and prepare students to enter an increasingly diverse workplace
(Bikson & Law, 1994).

Measuring the effects of diversity efforts is problematic because the
effects can not always be observed directly. Instead, the impacts of diversity
efforts lie in long-term outcomes like career choices, personal beliefs, and
friendship patterns (Hurtado, 2001). The short-tenn nature of most research
makes measuring these outcomes difﬁcult. Researchers have begun measuring
student attitudes toward diversity in speciﬁc contexts, building a body of literature
around the topic. Still, more longitudinal research is needed to examine how
student attitudes toward diversity change over time.

Loo and Rolison (1986) interviewed 163 undergraduate students at a
small public university within the University of California system. The researchers
found that minority students compared to white students experienced greater
levels of sociocultural alienation on campus marked by feelings of cultural
domination and ethnic isolation. “No matter how outstanding the academic

institution, ethnic minority students can feel alienated if their ethnic

64

representation on campus is small” (p. 72). L00 and Rolison also found that black
and Chicano students attributed their academic alienation to poorer academic
preparation in high school and being confronted with a new and different culture
in college.

Sedlacek, Helm, and Prieto (1997) surveyed students at the University of
Maryland - College Park to examine the relationship between perceptions of
diversity and student satisfaction. A positive relationship existed between comfort
in cross cultural situations and student satisfaction for all races. Diversity
awareness among Asian-American, Hispanic/Latino, and white students was
negatively correlated to overall student satisfaction. For African-American and
Hispanic/Latino students, comfort with their own culture was positively correlated
with student satisfaction in college. Predictor variables that had positive
relationships with overall satisfaction for all races included fair treatment by
students and teachers, comfort in cross-cultural situations, and respect for other
cultures. Negative correlations existed between satisfaction and perception of
racial tension and lack of support.

Springer, Palmer, Terenzini, Pascarella, and Nora (1996) surveyed a
national sample of white college students to examine the effects of diversity
awareness programs on attitudes toward diversity. The researchers found that
women and those in more liberal majors were signiﬁcantly more likely to hold
favorable attitudes toward diversity on campus. However, students who
participated in diversity awareness workshops had more favorable attitudes

toward diversity on campus regardless of gender or major. Students who did not

65

participate had less favorable attitudes toward diversity on campus. Henderson-
King and Kaleta (2000) found similar results with students at the University of
Michigan.

Hurtado (2001) examined a national sample of faculty and student
responses to surveys administered by UCLA’s Higher Educational Research
Institute to determine the impact that students’ exposure to diversity had on
student civic, job-related, and learning outcomes. Students who reported
studying with someone of another race/ethnicity reported gains in civic, job-
related, and learning outcomes. Hurtado found that interacting with diverse peers
was more important than curricular diversity on all three outcomes.

Gurin (1999) found that diversity in the classroom and diverse informal
interactions are related to a diverse student body. Gurin (2002) found that
students with more racially diverse classrooms and informal interactions
demonstrate the greatest growth in academic skills and in intellectual motivation
and engagement. Gurin argued that students exposed to diverse peers will be
better equipped for an increasingly diverse society.

In spite of the evidence to support the beneﬁts of diversity in education,
there is much to learn about the ways diversity is woven into the fabric of
postsecondary institutions and how speciﬁc events impact attitudes toward
diversity. In the current study I will examine the impact that banning afﬁrmative
action has had on student attitudes toward afﬁrmative action in college
admissions and racial diversity. The US. is at a critical juncture with afﬁrmative

action. With several states having banned afﬁrmative action and possibly more to

66

come, academic administrators, policymakers, and scholars should carefully
examine all outcomes associated with banning afﬁrmative action to examine the
impact that these important policy decisions have on diversity within
postsecondary education.
Conceptual Framework

I use the work of Sax and Arrendondo (1999) as the basis of the
conceptual framework for the current study. Their study provided a theoretical
basis for the relationship between student attitudes toward afﬁrmative action in
college admissions and a number of predictor variables. The current study
incorporates the same variables included in the work of Sax and Arrendondo
including race, gender, measures of self-interest, and measures of political
ideology. In the Sax and Arrendondo study, data from only 1996 were examined.
The current study offers a unique contribution by measuring change in attitudes
toward afﬁrmative action in college admissions and racial diversity from 1996,
when Proposition 209 was passed in California, to 2000.
Hypotheses

The ban on affirmative action is expected to have shifted student attitudes
more strongly against afﬁrmative action in college admissions and racial
diversity. Such a result would point toward the legitimizing power of the
referendum process. The Supreme Court has the ability to legitimize afﬁrmative
action policies among supporters and opponents (Mondak, 1994). I expect that
Proposition 209 will have a similar legitimizing affect on student attitudes with

more students opposing afﬁrmative action in college admissions and racial

67

diversity after the ban on afﬁrmative action in California. It is also expected that
women are more likely to favor affirmative action in college admissions than men,
that African-American and Hispanic/Latino students are more likely to favor
afﬁrmative action in college admissions, and that those with more conservative
political ideologies are more likely to oppose afﬁrmative action in college
admissions.

This study questions the extent to which the ban on afﬁrmative action has
impacted student attitudes toward racial diversity and afﬁrmative action in college
admissions. I examine freshmen cohorts at California four-year institutions
across a ﬁve year span from 1996 to 2000. The level of support for afﬁrmative
action in college admissions and racial diversity can provide insight for college
faculty and staff in designing diversity initiatives. A number of precollege factors
impact student attitudes toward diversity including gender, race, and political
orientation (Sax & Arrendondo, 1999; Springer, Palmer, Terenzini, Pascarella, &
Nora, 1996). Policy initiatives like Proposition 209 in California may affect student
attitudes toward racial diversity before they arrive on campus. If students are less
supportive of racial diversity, this makes the task of increasing openness to racial
diversity more challenging for faculty and staff.

Examining student attitudes toward afﬁrmative action in college
admissions and racial diversity can also provide administrators with a lens into
the college racial climate (lnkelas, 2003). More polarized views, especially
between racial groups, on affirmative action in college admissions and racial

diversity may be a sign that the campus racial climate has worsened. Though the

68

current study cannot make direct attributions to Proposition 209, less favorable
views toward afﬁrmative action in college admissions and racial diversity after the
ban on afﬁrmative action in college admissions may be an indication that the
policy has negatively impacted the college racial climate. Less polarized views
may signal that without afﬁrmative action the racial climate on campus improves.
Furthermore, student attitudes offer a glimpse into the likely voting
patterns of the college-educated in California. Student attitudes toward racial
diverserve as useful proxies to determine whether college students are more
likely to support policy measures that are race-neutral in the future. Under such a
scenario, banning afﬁrmative action would not only have signiﬁcant
consequences on the representation of racial minorities on university campuses,
but also on the diverse learning outcomes that most colleges and universities
strive to achieve. If California college graduates are less supportive of afﬁrmative
action in college admissions and racial diversity after the ban on afﬁrmative
action, then the policy may be reinforcing negative attitudes toward afﬁrmative

action in college admissions.

69

CHAPTER 3

METHOD

The purpose of the current study was to examine how the attitudes of
college students toward affirmative action in college admissions and racial
diversity changed after afﬁrmative action was banned in California. Additionally,
further analysis was conducted to explore the extent to which the factors that
contribute to students’ attitudes toward afﬁrmative action in college admissions
and racial diversity changed after the ban on afﬁrmative action in California. This
chapter is presented in the following six sections: research questions, conceptual
framework, instrumentation, variables, participants, and method of analysis.

Research Questions

In an attempt to study how eliminating afﬁrmative action in college
admissions impacts student attitudes toward afﬁrmative action in college
admissions and racial diversity, the following research questions are posed:

1) What differences exist between aggregate attitudes of California freshman
cohorts at four-year institutions toward afﬁrmative action in college
admissions and racial diversity before and after the passage of
Proposition 209?

2) Do gender, political ideology, race/ethnicity, parent's educational
attainment, parent's estimated income, average high school grade, college

entrance exam scores, and college choice predict California freshmen

7O

attitudes toward afﬁrmative action in college admissions and racial

diversity at four-year institutions?

3) What differences exist between factors used to predict aggregate attitudes
of California freshman cohorts at four-year institutions toward afﬁrmative
action in college admissions and racial diversity before and after the
passage of Proposition 209?

4) If differences are found between the variables used to predict attitudes
toward afﬁrmative action in college admissions and racial diversity, how
did these vary by racial group?

Instrumentation

The data for the study were drawn from the Cooperative Institutional
Research Program (CIRP) Freshman Surveys from 1996, 1998, and 2000. The
ban on afﬁrmative action was passed by California voters in 1996, but did not
take effect in undergraduate admissions until 1998 (Timar, Ogawa, & Orillion,
2004). 1996 was the ﬁrst year that the item on afﬁrmative action was included in
the CIRP Freshman Survey.

The CIRP Freshman Survey has been administered annually since 1966
by the Higher Education Research Institute (HERI) at the University of California,
Los Angeles. The survey is typically administered to incoming freshmen students
during orientation. The instrument collects data on a “range of student
characteristics: parental income and education, race/ethnicity, and other
demographic items; ﬁnancial aid; secondary school achievement and activities;

educational and career plans; and values, attitudes, beliefs, and self-concept”

71

(Sax & Arrendondo, 1999, p. 443). The survey is modiﬁed each year to include
questions pertaining to important issues of the day and items are removed from
the survey as well. Postsecondary institutions pay a fee to participate in the
survey. HERI estimates that the survey is administered to over 400,000 ﬁrst-time
freshmen at over 700 institutions each year (Higher Education Research
Institute, n.d.).

With over 40 years of data, the CIRP Freshmen Survey has exhibited “a
great deal of stability over time” for most items (University of California at Los
Angeles, n.d., p. 1). “Changes that are observed do not represent wild or random
ﬂuctuations, but can be linked to temporal trends or to real and meaningful
exogenous shocks (the events of September 11‘“, for example)” (University of
California at Los Angeles, n.d., p.1). Approximately 90 percent of the schools
included in the CIRP Freshman Survey sample are repeat participants, creating a
consistently reliable sample from year to year.

The CIRP Freshmen Survey is the most appropriate data source for the
study because it provides relatively broad coverage of student inputs and
includes items related to student attitudes toward afﬁrmative action in college
admissions and racial diversity. The CIRP Freshmen Survey data has been used
in numerous studies by higher education researchers to examine attitudes
toward afﬁrmative action in college admissions (e.g., Sax & Arrendondo, 1999;
Zamani, 2000) and diversity (Antonio, 2001; Astin, 1993; Hurtado, 2001).
Furthermore, because UCLA administers the survey, a large number of California

institutions regularly participate in the survey.

72

Sample

The sample was comprised of freshmen from California four-year colleges
and universities whose students completed the (CIRP) Freshman Survey each
year in 1996, 1998, and 2000. Because I am primarily interested in the attitudes
of United States citizens toward afﬁrmative action in college admissions,
international students were excluded from the analysis. The number of American
Indians in the sample was too low to include in the study. The CIRP Freshman
Survey did not include the item about afﬁrmative action, which serves as a
dependent variable for the study, in 1998. So, data from that year was excluded
from the regression analyses. The resulting sample represents a total of 73,642
students from 33 different institutions.

Variables

This section describes the variables to be used in the study. For details
about the coding schemes for all variables, see Figure 1.
Dependent Variables

Student attitudes toward racial diversity and afﬁrmative action in college
admissions served as the dependent variables for the study. Students rate on a
four-point scale the extent to which they agree that “afﬁrmative action in college
admissions should be abolished” from “disagree strongly” to “agree strongly.”
Higher scores indicate students’ agreement that afﬁrmative action in college
admissions should be abolished.

Measures of attitudes toward racial diversity included two items on the

survey: the student’s belief that “racial discrimination is no longer a major

73

Figure 1. Variable Coding Scheme

 

Variable

Coding Scheme

 

Afﬁrmative action in college admissions should
be abolished

Racial discrimination is no longer a major
problem in America

Importance of helping to promote racial
understanding a

Gender

Political Ideology

Race/Ethnicity

Parents’ Educational Attainment

Parents’ Estimated Income
Average High School Grade

College Entrance Exam Scores

College Choice

1 = disagree strongly, 2 = disagree somewhat,
3 = agree somewhat, and 4 = agree strongly

1 = disagree strongly, 2 = disagree somewhat,
3 = agree somewhat, and 4 = agree strongly

1 = essential, 2 = very important, 3 = somewhat
important, 4 = not important

0 = male and 1 = female

1 = far right, 2 = conservative, 3 = middle of
road, 4 = liberal, 5 = far left

A series of dummy variables representing ﬁve
racial/ethnic categories: White/Caucasian,
African-American/Black, American Indian,
Asian-American/Asian, Hispanic/Latino, and
Other. Puerto Rican and Other Latino, included
on the HERI survey, were recoded to
Hispanic/Latino. Multiple responses were
allowed. 0 = not marked, 1 = marked

The original instrument asks for mother's and
father’s highest level of formal education on an
8—point scale from grammar school or less to
graduate degree. A new variable was created
with scores equal to the highest value entered
for mother or father.

Measured on a 22-point scale from less than
$6,000 to $200,000 or more

1=D,2=C,3=C+,4=B-,5=B,6=B+,7=
A-,8=AorA+

Participants were asked to report their scores
on the SAT and ACT. ACT scores were

converted to their SAT equivalent.b In cases
where students provided ACT and SAT scores,
the higher of the two was chosen.

1 = less than second choice, 2 = second
choice, 3 = ﬁrst choice

 

Note. aCoding scheme was reversed from the original survey to align with the other dependent

variables

quuivalency scale taken from The Princeton Review at
httpzllwww.princetonreview.com/college/testprep/testprep.asp?TPRPAGE=8&TYPE=ACT.

74

problem in America” and commitment to “promoting racial understanding.” The
items were incorporated by Sax and Arrendondo (1999) as independent
variables in their analysis of student attitudes toward afﬁrmative action in college
admissions using the 1996 CIRP Freshman Survey data. The CIRP Freshman
Survey does not contain items that directly measure students’ attitudes toward
racial diversity, but these two variables can “shed light on students’ general affect
toward racial/ethnic groups” (p. 444).

Sax and Arrendondo (1999) and Zamani (2000) found that students who
believed that racial discrimination is no longer a problem in America were more
likely to support abolishing affirmative action in college admissions. In the Sax
and Arrendondo study, students who reported that they were not committed to
promoting racial understanding were more likely to oppose affirmative action in
college admissions. For two-year college students, Zamani found this to be the
case only for white students.

Survey Year

The primary variable of interest was the survey year. A dummy variable
was created to distinguish between the 1996 and 2000 cohorts and was used in
the regression analyses to measure differences between the two years.
Descriptive results include 1998 to give some indication of the pattern of change,
but data from 1998 were not included in the regression analyses. Chow’s Test
and the comparison of regressions coefﬁcients require a dichotomous dummy
variable. To avoid confusion, I included only the 1996 and 2000 cohorts in the

regression analyses to focus on the overall change for the ﬁve-year period. It is

75

expected that students will hold less favorable views toward afﬁrmative action in
college admissions and racial diversity in 2000 compared to 1996.
Student Background Characteristics

In addition to the survey year, I examined variables that have shown a
relationship to attitudes toward afﬁrmative action in college admissions to see if
the variables maintain a similar relationship in 2000. The previous work of Sax
and Arrendondo (1999) and Zamani (2000) included CIRP data only from 1996.
In the current study I examined how well the same variables perform in 2000.

Political ideology was also included in the analysis as a background
characteristic. Sax and Arrendondo (1999) found that for all racial groups,
students with more conservative political ideologies were more likely to support
abolishing afﬁrmative action in college admissions. Zamani (2000) found that
white two-year college students with conservative political ideologies were more
likely to support abolishing afﬁrmative action in college admissions than white
students with more liberal political views. However, no signiﬁcant relationship
existed between political views and support for abolishing affirmative action in
college admissions for African-Americans or Hispanics/Latinos. In line with the
previous research, it is expected that those with more conservative political
ideologies will be more likely to support abolishing afﬁrmative action in college
admissions
Self-Interest

Those who are more likely to beneﬁt from afﬁrmative action have a vested

stake in supporting afﬁrmative action policies. Measures of self-interest included

76

in the study are gender, race/ethnicity, parents’ educational attainment, estimate
of parents’ income, average high school grade, college entrance exam scores,
and whether students attend their ﬁrst-choice college or not.

In previous research, gender has had a signiﬁcant relationship to attitudes
toward afﬁrmative action with men more opposed to affirmative action in general
(Kravitz & Plantania, 1993; Meader, 1998; Sax & Arrendondo, 1999; Zamani,
2000). Using data from the 1990-91 Midwest College Study, Meader (1998)
found white males were more likely to oppose race-based policies than white
females. However, differences were not present for African-American students.
Zamani (2000) studied two-year college students who completed the 1996 CIRP
Freshman Survey to ﬁnd that across all racial categories males were more likely
to support abolishing afﬁrmative action in college admissions. Sax and
Arrendondo (1999) found using the 1996 CIRP Freshmen Survey that males
were more like than women to oppose afﬁrmative action in college admissions.
Kravitz and Platania (1993) also found that women were more likely to support
afﬁrmative action policies than were men. Because women have beneﬁted from
afﬁrmative action programs, it is expected that women will be more supportive of
afﬁrmative action in college admissions than men. It is also expected that women
will be more concerned about racial diversity than men.

Because afﬁrmative action as a social policy is designed to beneﬁt
minority applicants in college admissions, race/ethnicity contributes signiﬁcantly
to one’s perceived self-interest in maintaining or eliminating afﬁrmative action.

Previous research indicates that African—American and Hispanic/Latino students

77

are more likely to support afﬁrmative action than are whites. Kravitz and Platania
(1993) and Zamani (2000) found that African-Americans and Hispanics/Latinos
had more positive attitudes toward afﬁrmative action than whites. Meader (1998)
found that African-American students were more likely to support afﬁrmative
action that white students. Sax and Arrendondo (1999) included Asian-
Americans In their analysis and found that whites and Asian-Americans were
more likely to oppose afﬁrmative action in college admissions than were
Mexican-Americans and African-Americans. In the current study it is expected
that whites and Asian-Americans will be more likely to favor abolishing afﬁrmative
action in college admissions and less concerned about racial diversity than
African-Americans or Hispanics/Latinos.

Parents’ educational attainment and estimated income were included by
Sax and Arrendondo (1999) and Zamani (2000) in their studies. Sax and
Arrendondo found that for whites, Asian-American, and Mexican-American
students a positive correlation existed between both, higher levels of parental
education and annual family income, and support for abolishing afﬁrmative action
in college admissions. For African-Americans, higher levels of parental education
and annual family income were associated with support for afﬁrmative action in
college admissions. Zamani found a positive correlation between higher levels of
both, parental education and annual family income, and support for abolishing
affirmative action in college admissions for white two-year college freshmen only.

It is expected that students whose parents had higher levels of education and

78

higher incomes will be more likely to favor abolishing affirmative action in college
admissions and less concerned about racial diversity.

Average High school grade and college entrance exam scores were
included as measures of academic preparedness. Sax and Arrendondo (1999)
found that for whites, Asian-Americans, and Mexican-Americans a positive
relationship existed between academic preparation and support for abolishing
afﬁrmative action in college admissions. Freshman students with higher levels of
academic preparation were more likely to support abolishing afﬁrmative action in
college admissions. Zamani (2000) found the same pattern, but only for white
freshmen at two-year institutions. In line with previous research, it is expected
that those students with higher average high school grades and college entrance
exam scores will be more likely to favor abolishing afﬁrmative action in college
admissions and less concerned about racial diversity.

It is expected that students who indicated that they were not attending
their ﬁrst-choice college would be more likely to support abolishing afﬁrmative.
action in college admissions. Sax and Arrendondo (1999) found that for whites
and Asian-Americans opposition to afﬁrmative action in college admissions was
more likely to come from those freshman students who were not attending their
ﬁrst-choice institution. Among Mexican-Americans, those who were attending
their ﬁrst-choice institution were more likely to support abolishing afﬁrmative
action in college admissions. Zamani (2000) found that among white two-year
college students support for retaining afﬁrmative action in college admissions

decreased as students reported attending a lower-choice institution. No

79

signiﬁcant differences were present for African-American or Hispanic/Latino
students.
Method of Analysis

Data analyses were conducted in six stages: mean difference tests for
each dependent variable between 1996 and 2000, descriptive analysis, a
modiﬁed Chow’s test (Gujarati, 1970) of the equivalence of 1996 and 2000
regression equations for all dependent variables, examination of the separate
regression equations for 1996 and 2000, a comparison of regression coefﬁcients
for each of the predictors before and after the ban on afﬁrmative action in
California, and a comparison of regression coefﬁcients for each of the predictors
for each racial group before and after the ban on afﬁrmative action in California.
Initially, mean comparisons were computed to examine differences between
1996 and 2000 for each of the outcome variables. Descriptive analyses describe
student attitudes toward afﬁrmative action in college admissions and racial
diversity by each of the independent variables. Cross-tabulation tables with
percent distributions were created to show how attitudes toward afﬁrmative
action in college admissions and racial diversity break down for each
independent variable by survey year.

In the third stage, a modiﬁed version of Chow’s test was conducted using
a dummy variable where 0 = 1996 and 1 = 2000. The purpose of the Chow test is
to determine whether two regression lines are the same or, in other terms, if the
sets of coefﬁcients and the intercepts are equal (Gujarati, 1970). Chow’s test

measures the equality of error variances between two regression models

80

(Ghilagaber, 2004). The test is appropriate with large sample sizes, but small
samples can prove misleading. Additionally, the test is appropriate when the
sample sizes are equal and the form of heteroscedasticity is the same across the
two models. When samples sizes are unequal, considerable differences may
exist between the average variances of the error terms in the two models.

In the fourth stage, I examined the regression equations to determine
whether the independent variables predict attitudes toward afﬁrmative action in
college admissions and racial diversity in 1996 and 2000. The independent
variables have all been shown to predict attitudes toward afﬁrmative action in
college admissions, but previous research using the CIRP Freshman Survey only
included data from 1996. In the current study, I examined how well the
independent variables predict attitudes toward afﬁrmative action in college
admissions five years later. I also explored how well the same independent
variables predict attitudes toward racial diversity in 1996 and 2000.

The Chow Test determines whether two regression equations are
significantly different from one another, but does not pinpoint where these
differences lie within the equation (Gujarati, 1970). The ﬁfth stage involved
additional regression analyses to compare the regression coefficients from 1996
to 2000 for each of the dependent variables. A t-test was performed comparing
regression coefﬁcients for each of the dependent variables. Fairweather (1995)
explains that this procedure permits one to test the equivalence of regression
coefficients across groups. The test will reveal any changes in the factors that

predict attitudes toward afﬁrmative action in college admissions and racial

81

diversity. In the sixth stage I used the same procedure, but compared the
regression coefﬁcients for each racial group separately. As an example the
equation for the afﬁrmative action dependent variable in examining differences
across racial groups was:

ABOLISHAA = INTERCEPT + (INTERCEPT*YEAR) + b1GENDER +
b2(GENDER*YEAR) + b3POLlTICALVIEW + b4(POLITICALVlEW*YEAR) +
bssES + b5(SES*YEAR) + b7ACADEMlCPREPARATION +
b8(ACADEMICPREPARATION*YEAR) + bgCOLLEGECHOlCE +
bro(COLLEGECHOICE*YEAR) + e

In this case, the t-test indicates whether or not the coefﬁcient for GENDER
differed between 1996 and 2000. If there is a difference, the test can also
indicate in which direction. Positive signs for the t-test indicate that that the
absolute value of the coefﬁcient for 1996 is signiﬁcantly greater than the absolute
value of the coefficient for 2000 (FainNeather, 2005). Negative signs indicate that
the absolute value of the coefﬁcient for 2000 is signiﬁcantly greater than the
absolute value of the coefﬁcient for 1996. In the next chapter, I present the

results of the current study.

82

CHAPTER 4

RESULTS

The results are presented in this chapter beginning with an examination of
the sample demographic characteristics, which show the sample to have a higher
representation of whites and women compared to the total California 4-year
enrollment. Then mean differences and percent distributions are presented. The
mean trends provide an easy snapshot of the trends for each of the dependent
variables. Then, the results for Chow's test and the regression analyses are
presented. Though the independent variables served as good predictors for Sax
and Arrendondo (1999) using only 1996 data, I found the variables to be less
predictive in 2000. Signiﬁcant differences between 1996 and 2000 are explored
for each set of dependent and independent variables.

The percent distributions for political ideology are presented in Table 11
for 1996, 1998, and 2000. The percentage of California 4-year freshman who
reported being far left or conservative dropped from 27% in 1996 to 22.8% in
2000. At the same time the percentage who classiﬁed themselves as middle of

the road, liberal, and far left increased from 1996 to 2000. l computed means for

Table 11. Percent Distribution of California freshmen included in the sample by political
ideology and year

 

 

Item 1996 1998 2000
FAR RIGHT 1.5 1.3 1.4
CONSERVATIVE 25.5 22.7 21.4
MIDDLE OF ROAD 43.6 45.2 44.3
LIBERAL 27.3 28.5 29.9
FAR LEFT 2.1 2.3 3.0

 

83

Table 12. Percent Distribution of California freshmen included in the sample for gender
and race by year

 

 

Item 1996 1998 2000
Gender
Male 44.8 42.9 42.4
Female 55.2 57.1 57.6
Race/Ethnicity
White 63.8 62.0 61.9
African-American 3.7 4.1 4.1
American Indian .5 .5 .5
Asian-American 16.9 17.8 17.9
Hispanic/Latino 15.1 15.5 15.5

 

Note: Totals may not add to 100 due to rounding

each year (1996 = 3.03, 2000 = 3.12) and a two-tailed t-test (t = 10.10, df =
34792, p < .01), which showed that the students in 2000 were significantly more
left of the political spectrum than students in 1996.

Percent distributions for gender and race/ethnicity for the sample
population are provided in Table 12 for 1996, 1998, and 2000. Table 13 provides
the percent distribution by gender and race/ethnicity for overall enrollment in four-
year postsecondary institutions for the same years. Using contingency tables, I

computed X2 values to test whether there were significant differences in gender

Table 13. Percent Distribution of total enrollment in four-year postsecondary institutions in
California gender and race by year

 

 

Item 1996 1998 2000
Gender
Male 48.0 47.2 46.3
Female 52.0 52.8 53.7
Race/Ethnicity
White 51.0 48.6 47.6
African-American 7.7 7.5 7.3
American Indian 1.2 1.1 1.0
Asian-American 18.3 18.9 18.6
Hispanic/Latino 21.8 23.8 25.4

 

Note: Totals may not add to 100 due to rounding
Source: California Postsecondary Education Commission, Online Data — Customized Reports,
retrieved July 5, 2007 from http://www.cpeccagov/OnLineData/OnLineDataasp

84

or race between the sample and the population for each of the three years. No
statistical differences were found using this method meaning the sample is
statistically representative of the population along gender and racial categories.
Mean Differences

For each of the dependent variables, Table 14 displays the mean
responses for each of the three years included in the study. Mean responses
divided by racial groups can be found in Appendix A or by race and gender in
Appendix B. Overall, students supported abolishing affirmative action in college
admissions. Support for abolishing affirmative action in college admissions
diminished slightly from 2.76 in 1996 to 2.71 in 2000. The means are statistically
different (t = 4.49, df = 29529, p < .001), but the change is slight given the large
sample size. This is opposite of the hypothesized direction of change. Students
in 2000 were more supportive of affirmative action in college admissions than in
1996. The mid-point for the scale is 2.5 with mean responses for each year
considerably above the mid-point still indicating an overall desire to abolish
affirmative action in college admissions.

Agreement with the statement, “Racial discrimination is no longer a major
problem in America" increased from 1.68 in 1996 to 1.84 in 2000 (t = -19.75, df =
32492, p < .001). Even though the change is significant, using 2.5 as the mid-
point of the scale again indicates that the means all lie on the side of
disagreement with the item. Though this is a substantial change in aggregate

student cohort attitudes toward the perception of racial discrimination in the US,

85

Table 14. Mean Responses of California Freshmen for each dependent variable by year

 

Item 1996 1998 2000

Afﬁrmative action in college admissions
should be abolished a

Mean 2.76 - 2.71
N 14750 - 20232
Standard Deviation 1.063 - .956

Racial discrimination is no longer a
. . . a
major problem in America

Mean 1.68 1.79 1.84
N 15036 19024 20781
Standard Deviation .755 2766 .759

Importance of helping to promote racial
understanding

Mean 2.66 2.76 2.79
N 14858 18504 20269
Standard Deviation .925 .897 .897

 

Note: The abolishing affirmative action item was not asked on the 1998 CIRP Freshmen Survey.

a . .
Measured on a 1 to 4 scale where 1 = disagree strongly, 2 = disagree somewhat, 3 = agree
somewhat, and 4 = agree strongly

b . . .
Measured on a 1 to 4 scale where 1 = essential, 2 = very important, 3 = somewhat important, 4
= not important

the trend is equally present before and after the implementation of Proposition
209 in 1998.

The trend is similar for the item measuring belief in the importance of
helping to promote racial understanding, which declined from 2.34 in 1996 to
2.21 in 2000. Though not as dramatic as the previous item, there is still
significant change (t = 13.34, df = 31234, p < .001). The two items together
provide an initial indication that in the years around Proposition 209, student
attitudes toward racial diversity shifted away from recognizing racial
discrimination as a major problem in American and away from promoting racial

understanding.

86

Percent Distributions

In order to capture more detail in how responses changed over time, I
computed the percent distribution for each dependent variable by individual
answer choices for each year. Though changes in means were relatively small,
there was a shift toward more centric views for each of the dependent variables.
Table 15 shows the percent distribution for the affirmative action item and the
change from 1996 to 2000 (X2 = 515.64, df = 3, p < .001). The percentage of
people who disagreed strongly fell 4.8% and the percentage that agreed strongly
fell 7.1% from 1996 to 2000. There is movement toward the center of the scale

on afﬁrmative action in college admissions after Proposition 209.

Table 15. Percentage distribution for “Afﬁrmative action in college admissions should be
abolished” by year

 

 

Affirmative action in college Disagree Disagree Agree Agree

admissions should be abolished Strong Some Some Strong
1996 15.3 25.4 27.2 32.1
2000 10.5 32.7 31.8 25.0

 

This trend is apparent in the mean breakdowns by racial group as well.
Appendix A shows the mean scores for each of the dependent variables across
both years by race. Mean scores for whites decreased .24 (p<.001) and for
Asian-Americans .05 (p<.05). For African-Americans and Hispanics/Latinos
mean scores increased .33 (p<.001). So, whites and Asian-Americans who tend
to more strongly oppose affirmative action in college admissions held less
opposition in 2000 compared to 1996. African-Americans and Hispanic/Latinos
who tend to more strongly support afﬁrmative action in college admissions were
less supportive in 2000 compared to 1999. Leading up to the passage of

Proposition 209, there was significant media attention and increased public

87

Table 16. Percentage distribution for “Racial discrimination is no longer a major problem
in America” by year

 

 

Racial discrimination is no longer a Disagree Disagree Agree Agree

major problem in America Strong Some Some Strong
1996 47.4 39.4 11.1 2.2
1998 39.6 43.5 14.8 2.1
2000 35.8 46.2 15.9 2.1

 

awareness about affirmative action (Nicholson, 2003). As the media attention
shifted to other issues and events the 2000 freshmen cohort would have faced
less exposure to mainstream media coverage of affirmative action than the
preceding cohorts as they prepared to enter college.

Table 16 shows the change in percent distributions for the item “racial
discrimination is no longer a major problem in America” (X2 = 527.82, df = 3, p <
.001). The percentage of respondents who disagreed strongly dropped 11.6%
while the percentage who disagreed some increased 6.8% and the percentage
who agreed some increased 4.8% from 1996 to 2000. Similar to the affirmative
action item, there was a higher percentage of responses in the middle of the
scale with the exception of the percentage that agreed strongly, which remained
relatively unchanged.

Percent distributions for the “importance of helping to promote racial
understanding” item are displayed in Table 17 (X2 = 181.19, df = 3, p < .001).
The majority of freshmen in each year indicated that helping to promote racial
understanding was either not important or somewhat unimportant. The
percentage of respondents indicating that promoting racial understanding is
essential decreased 3.3% and the percentage that indicated it was somewhat

important decreased 3% over the five-year span. The percentage that indicated it

88

Table 17. Percentage distribution for “Importance of helping to promote racial
understanding” by year

 

 

Importance of helping to Essential Somewhat Somewhat Not
promote racial understanding Important unimportan Important
t
1996 12.7 27.8 40.7 18.8
1998 9.9 25.4 43.5 21.2
2000 9.4 24.8 43.3 22.5

 

was not important increased 3.7% and the percentage that indicated it was
somewhat important increased 2.6%. Combined with the change in means, the
percentage changes show a clear decline in the importance of helping to
promote racial understanding from 1996 to 2000.

For the affirmative action dependent variable there was movement to the
center of the scale. More polarized views in 1996 are likely the result of
increased media attention around Proposition 209. There was an increase in the
percentage of respondents who believed that racial discrimination is no longer a
major problem in America and decline in the percentage who believed in the
importance of helping to promote racial understanding.

Correlation Matrices

The descriptive statistics are useful in seeing detailed changes over time,
but they do not account for other variables included in the study. The
multivariate regression analyses provide a more thorough understanding of how
each of the independent variables, controlling for the others, impacts the
dependent variables. I computed correlations between each of the dependent
variables combining data from 1996 and 2000 to determine the extent to which

each measured separate constructs. Table 18 displays the correlation matrix for

89

Table 18. Correlation matrix for all dependent variables

 

 

Item Abolish affirmative Racial Promote racial
action in college discrimination is no understanding
admissions longer a problem

Abolish affirmative 1.000

action in college

admissions

Racial discrimination is 171*
no longer a problem ' 1000

Promote racial 209* 224* 1.000
understanding

 

Note: Correlations computed using Spearman’s Rho
*
p S .05

all dependent variables. Low correlations suggest that all items can be treated
independently in the analysis. Table 19 displays the correlation matrix for all
independent variables. Large correlations between parent’s educational
attainment and parent’s estimated income and between average high school
grades and college entrance examscores could have resulted in unacceptable
levels of multicollinearity.

To reduce the impact this would have on the explanatory power of the
regression analyses, composite scales were created for the variables with
correlations over .5. SES, a new variable, was formed adding the values for
parent’s educational attainment and parent’s estimated income. The new variable
formed a scale from 230. Another new variable, academic preparation, was
created using the same procedures employed by Sax and Arrendondo (1999).
The new variable was computed by dividing the college entrance exam score by

100 to form a scale from 4 to 16 and then adding the 8-point scale of average

90

0cm McmEmeam mEm: omSano 30:99.8 550 __< .> mLmEmLo 9.6: “393800 m “202

mowa. Fo.wa

.3.

 

0009

N00.

 

¥*m—.O.l *FFO. *¥Nmo. *¥©—‘O.I *VFO. ¥¥NVO. ¥¥®FO. gmm> >®23m
oooF moor ssvmo. voo. Foo. :09. .330... .3me wmmzoo :0 86:0
. . . . . . . mmzoom
000 w *pnmwm ¥¥ONN ¥¥O©m ¥¥NFN ¥¥MNO *me mem mocmbcm ®m@:00
. . . . . . $880
000 —. «kmmo clamor *ﬂmor *«omo - kkvmo _oor_om LEI mmme><
. . . . . 2:85
000 r kimom .«kNON «:«NNO I ¥¥mmo UwﬁmEzmw mpcmgmn—
. . . . EmEEmz<
000 F imam h.CFFmo 3.50 .mcozmosom m.Fc8mn_
83 .218. .380. maaesmaomm
08F .88. F868. _8_:__on_
oooF Moscow
mmLoow 8080
$960 mew Bozom mEooE EmEEmz< >
me> :0 mocmzcm :9: 86:53 _mco_:mo:om m :2:sz 30.062

32:40. $650 $260 @3521 3:de m.:c8mn_ \momm .mo_:__0n_ mcmvcmo Em:

 

«Santa; «sebaceous =a Lou x32: cozﬂotoo .3 835...

91

Table 20. Correlation matrix for SES and Academic Preparation

 

 

Item SES Academic Preparation
SES 1.000

Academic Preparation .260" 1000

Gendera .096“ .187“

Political Ideology -.O16** .033“
Race/Ethnicitya .246” .195“

Choice of College .003 .005

Survey Year .044“ .011*

 

Note: a Computed using Cramer’s V. All other correlations computed using Spearman’s Rho
** *
p S .01 p S .05

high school grades to form a 20-point scale. Table 20 shows the correlations
between the new composite variables and all other independent variables.
Chow’s Test and Regression Analyses

I compared 1996 and 2000 regression equations for each of the
dependent variables using Chow’s Test to determine whether significant
differences existed between the two years. Table 21 displays the Chow Test
comparisons of the regression equations between 1996 and 2000 for each of the
dependent variables. All three dependent variables revealed signiﬁcant

differences between 1996 and 2000. The F-test demonstrates that for each of the

Table 21. Chow Tests comparing separate regression equations for 1996 and 2000 for each
dependent variable

 

 

Item F df
Abolish affirmative 4654* 9, 30950
action in college

admissions

Racral discrimination 5428* 9, 31486
IS no longer a

problem

Promote racral 3635* 9, 30939

understanding

 

Note: * p < .001

Table 22. Regression and t-test comparisons for “Abolish affirmative action in college
admissions” in 1996 and 2000

 

 

Item 3 996 3000 T-test comparisons
(R =.251) (R =.133)
"“2 C991 378* 3098*
(061) (051)
Gender * *
-.139 -.153
-.643
(.016) (.014)
Political Ideology _ * _ *
.297 .148 11.605***
. . (010) (008)
African-American _1 234* -.841* 7 127*“
A ‘ A . (.044) (.034) ‘
sran- merrcan * *
-.280 -.202 2.704“:
. . . (.022) (.018)
Hispanic/Latino _1 000* -.556* 13 405*“
(.026) (.022) ’
SES 005* .005 501
P (.001) (.001) '
Academic reparation 012* .018 *
C fc (.002) (.001) 2.485
hoiceo olle e * *
9 4038 4030 .462

(.014) (.011)
Note: *** p < .001 ** p <01 * p < .05

dependent variables the regression equations for 1996 are not equal to the
regression equation for 2000. However, the test does not reveal where the
differences lie within the equations. 80, t-test comparisons were computed
comparing the regression coefficients from 1996 to 2000 for each dependent
variable.

Table 22 shows the regression coefficients and t—test comparisons for
“Abolish affirmative action in college admissions.” Gender was a significant
, predictor across both years with men more likely to oppose affirmative action in
college admissions. Political ideology was a significant predictor of attitudes
toward affirmative action in college admissions in 1996 and 2000. Those with

more conservative views were more likely to oppose affirmative action in college

admissions in both years, but more so in 1996. All three racial minority groups
were more likely than white students to favor keeping afﬁrmative action in college
admissions, but differences between the attitudes of white students and minority
students was greater in 1996 around the passage of Proposition 209. In line with
the findings of Sax and Arrendondo (1999), Asian-American students had less
favorable attitudes toward affirmative action in college admissions than African-
American and Hispanic/Latino Students. SES and Academic preparation were
minor but signiﬁcant predictors in 1996, but not in 2000. Choice of College was
small, but significant predictor in both years with no statistical difference in the
predictive power of the variable across the two years.

Regression equations were constructed for each racial category to more
closely examine the differences between racial groups. Table 23 shows the
results of the regression analyses and t-test comparisons for “Abolish affirmative
action in college admissions” across the four racial categories. For all four racial
categories those who held more conservative political views were more likely to
favor abolishing affirmative action in college admissions in 1996 than in 2000.
The difference between coefficients is small, but white students with higher SES
levels were more likely to favor abolishing affirmative in 2000 than in 1996. For
Hispanics/Latinos higher levels of SES were more strongly correlated with the
desire to abolish affirmative action in college admissions in 1996 than in 2000.
Higher levels of academic preparation for white students were more strongly
associated with the desire to abolish affirmative action in college admissions in

2000 than in 1996. Asian-American students who reported attending less than

94

 

 

 

8. v a . S. v 8.. 8. v a... ”202
88.: :8: :8: $8.: 88.: :8: 65.: 85.: 88:8
8. o8. 88. .8F 88.- .80.- 8. 80. 80.- 8.- :88. :88. :o 8.95
88.: :8: 88.: $8.: :8: $8: 80.: 88: 8:885
NO... MOO. NCO VF. iiimNO. tiaNNO. WFK FOOF VOOI iiiwmﬁu «item—‘0. «tic—.0. 0_E0UNU<
a8: 88.: 88.: $8.: $8: 68: a8: 80.:
.288- 80. 2.20. 8F :88. m8. 8.- F8. 80. :38. .88. 80.- mmm
88.: 88.: :8: $8: :8: :8: SS: :20: 30.08.
atimv.V «LIFVNON «:0me susVN.N is¥MNOK kicmwrf ikMV.N WOO. «:15er i¥i®®.m iiiww—‘f #iimmmr _m05__on_
68.: :8: 68.: :8: $8: $8.: $5.: 68.:
8. 80.- .80.- 8. 148.- :8 F .- FF. 88.- 80.- 8. F- .....8 F .- 1.8 F .- .880
$2.: $2.: 62.: 94F: 88: a8: 88: 88:
.- iiiOmN.N «$in —. .N .. iitmvm.N ¥4¥©®®.N r swammwg‘ aisVOF.N r #iiNOV.m «LING—WV “Qwuhmur:
:8: 88 82 :8: 88 82 :8: 88 82 :8: 88 82
oczmdoEmamf cmocmE<ém6< cmocmE<émoE< m:_c>> Em:

 

93.6 3:52.208 3 :mcoﬁmEua 32.3 E cocoa 8235.5.“ 5:23.18 55358”. .3 838.

95

Table 24. Regression for “Racial discrimination is no longer a major problem in America”

in 1996 and 2000

 

 

Item 3996 3000 T-test comparisons
(R =.059) (R =.046)

Intercept 2294*“ 2348*”
(048) (042)

Gender - 129*“ - 095*“ *
. - 1.
(.013) (.011) 967

Political Ideology -_131*** -.128*** 322
(008) (007) '

African-American -.448*** "439*“ .208
(034) (028)

Asian-American -.181*** __091*** but
(.018) (.015) 3874

Hispanic/Latino _ 222*“ - 150*“ **
. - . 7
(.020) (.018) 2 6 8

SES _'003*** .001 mm
(.001) (001) 3527

Academic Preparation __oo3* _.004*** -,958
(.001) (.001)

Choice of College .017 018* 088
(.011) (.009) '

 

** *

Note: *p<.001 *p<.01*p<.05

their first choice institution were more likely to prefer eliminating affirmative action
in college admissions in 1996 than in 2000.

Table 24 shows the regression coefficients and t-test comparisons for the
dependent item “Racial discrimination is no longer a major problem in America.”
Males were slightly more likely in 1996 than in 2000 to believe that racial
discrimination is no longer a major problem. Whites were more likely than all
three minority groups to believe that racial discrimination is no longer a problem
for both years, but differences were slightly larger in 1996 than in 2000. The low
R2 values indicate that the model, which was originally designed to measure
attitudes toward affirmative action in college admissions, is less appropriate for

this outcome. Additional variables or constructs might improve the predictability

96

 

 

 

8.8. 8.0.8... 88.81.1902

68.: 88.: $8.: 88.: 68.: 68.: 88.: 38.: 88:00

9.. 80. 80. 8. F8. 88.- 8F 88. 88.- 2F- F8. 80. :o 880

80: 80: 80.: 80.: 88.: 80.: 88.: 80: 839898

2. .80.- 80.- 8F- :88. F8. 8.- 80. F8. 8. .88.- 80.- 2688:.
:8: 80.: 88.: 80: 88.: 88.: :8: :8:

8F 88. 80.- 8F 8.. .88.- 8. 88.- 88.- 1.8.8 88. 188.- mmm

88.: 88.: 88.: 88.: 68.: a8: a8: 88.: 8208.

8. .88.- 1.88.- 8.- ....88.- 8.8.- 8.- 88. 28.- 8.- 1.82.- 1L2. 85:8
:8: $8: 68.: 88: :8: 68: :8: :8:

¥m®._‘ aimmor «##QN v.1 O©.r #imNOf VWOF «VN. #1 i F? F .r F r01 ticNm.N «atVGOf iikom F .r LQUCQO
82.: 8F: 88: 8F: 8: :2: :8: 88.:

- ...m8.F 1.83 - ...8F.N .....8.F - .....8F..F ....m8.F - 1.34.8 1.88.8 8222
:8: 88 82 :81 88 82 :8: 88 82 :8: 88 82

oczmdoEmamf cmocmE<ém6< cmocmE<émoE< QE>> E0:

 

032m 2:52.508 >0 :00_..0E< E 80320 00.22: a Lego. o: 0_ cozmﬁEtomE 3001.15: coinemom .3 0.00...

97

Table 26. Regression for “Importance of helping to promote racial understanding” in 1996

 

 

and 2000
Item 3 996 2000 T-test comparisons
(R =.110) (R2=.O7O)
'“tercept 3.471 *** 3.430***
(058) (049)
Gender -.156 *** -091 *** ***
(.015) (.013) "3'2“
Political Ideology __222 *** -_173 *** ***
(.009) (.008) '3'612
African-American -.769 *** -.606 *** **
(.041) (.033) '3'071
Asian-American _ 258 *** _ 183 mm H
(.021) (.017) '2‘744
Hispanic/Latino -.383 mm -.282 mm H
(.024) (.021) ““52
SES .001 .002 * _ 885
(.001) (.001) '
Academic Preparation __001 {003 *
(.002) (.002) 1.185
Choice of College .024 .027 * 170
(.013) (.010) "

 

**

Note: * p < .001

**p<.01*p<.05

of the model, but these initial findings suggest that during the height of the

Proposition 209 debate, white and male students were more likely to hold

opinions in their own self-interest.

Table 25 displays the regression coefﬁcients and t-test comparisons for

“Racial discrimination is no longer a major problem in America” by each racial

category. For white students, a more conservative political ideology was a

signiﬁcant predictor of desire to abolish afﬁrmative action in college admissions

across both years. Males and those with higher SES levels were more likely in

1996 compared to 2000 to believe that racial discrimination is no longer a

problem in America. African-Americans females more likely to believe that racial

discrimination is still a major problem in the US. Among Hispanic/Latino

98

 

99

 

 

8. v a . 8. v a .. 8. v a... ”902

:8: .80: :8: :8: .80: 88: :8: :8: :8: 82.8

8. m8.- m8. - 88. 88.- 8. 2- 80. 20.- ..8: 88. .88. .o 865

:8: .88: :8: .88: :8: :8: :8: :8: 8:885

8.: .88.- 8.- 8. 88. 88. 8. So.- 28 8. .88.- .88.- 2882
:8: :8: :8: :8: :8: .88: :8: :8:

8. 88. 88. 8. :8. o8. 8.- 80.- 88.- 8. o8. 88.- mmm

:8: :8: :8: .88: :8: 68: .20: :8: 8068.

0V. Fi iti©®0f «ix-WV—‘f imm. _..i itiNO P .I iN-Q _x .I ma. ##ON F .i OWOF iiﬁmm.Ni «ELL. PNK «a... OVN... _m0_t_On_
.88: :8: :8: :8: :8: :8: :8: .20:

mm. «.itNVF... iiMNr... «.00. F.- it¥OOrV tam _x .i imwf mwOi «mm—‘f a*¢®W.MI iiiowOf 3?... QQFV .mUCQQ
.8: :2: :2: 62: .28 68: 68: .88:

i ***rm0.m itiMNmN.‘ i {itvomio‘ aiiN —. F .m i iiiONN.N iiiVOW.N i i§t®®©.m «ithm.m uamohmarz
:8.-. 88 82 :8: 88 82 :8: 88 82 :8: 88 82

05.38.53... cmotmE<-cm_w< cmocmE<ém0E< 9E>> Em:

 

“.305 0.252.309. >0 ..mc.o:8200:: .309. 03an 3 9.3.0.. :o 00:0tan... ho: :o_mmo._m0m. KN 03a..-

students, gender was a more significant predictor in 1996 than in 2000 with
women more likely than men to disagree with the item. The low R2 value
suggests the model accounts for only a small portion of the overall variance.

Table 26 presents the regression coefficients and t-test comparisons for
“Importance of helping to promote racial understanding.” Gender was a more
significant predictor in 1996 than in 2000 with women more likely to believe in the
importance of promoting racial understanding. A less conservative political
ideology was more significantly related to support for promoting racial
understanding in 1996 than in 2000. Students with more self-reported liberal
political ideologies were also more likely to believe that helping to promote racial
understanding is important. All three racial minority groups were more likely than
white students to believe that promoting racial understanding is important, but
more so in 1996 than in 2000.

Table 27 displays the regression coefﬁcients and t-test comparisons for
1996 and 2000 on the dependent item “Importance of helping to promote racial
understanding.” Females across all four racial categories were more likely than
males to indicate that helping to promote racial understanding is important. For
white, African-American, and Asian-American students, being female was more
significantly related to the belief that promoting racial understanding is important
in 1996 than in 2000. For white and Asian-American students, a liberal political
ideology was more significantly related to support for promoting racial
understanding. Attending less than a first choice institution was more negatively

associated in 1996 than in 2000 with the perceived importance of promoting

100

racial understanding for white students. For Asian-American students, attending
one’s first choice institution was more positively related to support for promoting
racial understanding in 2000 than in 1996.

Appendix A shows the mean responses for each of the dependent
variables by race for 1996 and 2000. African-American students were most
supportive of affirmative action in college admissions and most concerned about
racial diversity across both years. Appendix B shows mean responses for each
dependent variable by race and gender for 1996 and 2000. For each racial
category and across both years the mean scores for women were more favorable
toward affirmative action in college and racial diversity. African-American women
in particular were the most supportive of afﬁrmative action in college admissions
and most concerned about racial diversity.

Summary

In this chapter, I have provided a detailed look at the descriptive and
inferential statistics included in the study. Students were slightly more favorable
toward affirmative action in college admissions, but less concerned about racial
discrimination or promoting racial understanding. The descriptive statistics show
clear trends in how California freshmen responded on each of the outcome
variables. Students were less polarized on the affirmative action item with more
responses in the center of the scale.

The regression analyses revealed poor model fits, especially in 2000 for
each of the equations. The variables, in less politicized times, were less

predictive of the outcome variables offering additional support that student

101

attitudes were less polarized in 2000 than in 1996. The regression analyses
revealed that women and those with more liberal political ideologies were more
likely to support affirmative action in college admissions, to consider racial
discrimination as a remaining problem in the US, and to believe in the
importance of promoting racial understanding. All three racial minority groups
when compared to whites were more supportive of affirmative action in college
admission and more concerned about racial discrimination and promoting racial

understanding.

CHAPTER 5

DISCUSSION

In this chapter I offer an analysis of the findings and draw conclusions
about the implications of the study to scholars, practitioners, and policymakers.
Drawing upon the original research questions I explore the differences among
the dependent variables and then turn to the predictive ability of each of the
independent variables. Finally, I offer insights on how others may use the results
of the study to inform scholarship, practice, and policy.

This study is a first step in examining the relationship between banning
affirmative action and student attitudes toward affirmative action in college
admissions and racial diversity, but additional work is needed. Though the case
for the educational benefits of diversity have been well documented (e.g., Gurin,
P., 1999; Gurin et al, 2002; Hurtado et al, 1998; Smith & Associates, 1997), the
political battle over the relative importance of the benefits of diversity versus a
desire for a college admission system that treats people the same regardless of
race is heating up.

Research Question 1
What differences exist between aggregate attitudes of California freshman
cohorts at four-year institutions toward affirmative action in college admissions
and racial diversity before and after the passage of Proposition 209?
In this study, I have shown how California freshmen attitudes toward

affirmative action in college admissions and racial diversity differed before and

103

after Proposition 209. There were significant changes in attitudes from 1996 to
2000 for the affirmative action item and both of the racial diversity items with the
mean of each item moving closer to the mid-point of the scale. Students were
generally opposed to affirmative action in college admissions, but more so in
1996 than in 2000. This finding is a contrast to the hypothesis for this dependent
variable. It was expected that the policy would legitimize opposition to affirmative
action in college admissions, but students were more supportive of affirmative
action in college admissions is 2000 than in 1996. The difference in mean scores
dropped slightly from 2.76 to 2.71. Though the difference was significant, a drop
of .05 in the mean score is quite small. It is possible that the increased media
attention and more polarized views led to a greater level of opposition to
affirmative action in college admissions in 1996, but the mean changed only
slightly from 1996 to 2000.

Across both years an overwhelming majority of students believed that
racial discrimination is still a major problem in America, but the majority did not
believe that it was important enough to help promote racial understanding. In
2000 compared to 1996, students were substantially less likely to believe that
racial discrimination is a problem in America and were less likely to believe that
helping to promote racial understanding is important. Students in 2000 were
significantly more likely to believe there are fewer racial problems in the US.

These trends are interesting given the increasing racial disparities in
income, net worth, housing, employment, and education in the US. (Bostic,

1996; Bucks, Kennickell, & Moore, 2006; Schmidt, 2007b). Postsecondary

104

institutions continue to invest resources in diversity and multicultural
programming (Gurin, 1999), but diversity programming has increasingly moved
away from the promotion of equity (Hurtado, 2005; Tapia, 2007). The decreased
belief that racial discrimination still exists and that promoting racial understanding
is important marks a contrast to the increasing racial differences in society. As
the racial gap widens, higher education should be challenging students and
faculty to do more to address the social problems that lead to racial disparities. In
order to address those challenges, students must increasingly understand how
racial minorities are disproportionately impacted in the US.

In the University of Michigan cases in 2003 the Supreme Court
determined that affirmative action can only be used as a tool to achieve diversity
if diversity benefits all students (Hurtado, 2005). The ruling forces institutions to
measure the value of affirmative action programs by how they impact diversity on
campus. This move away from promoting racial equity to diversity is a stark
contrast to the civil rights movement of the 1960s The current study is limited by
the items in the CIRP instrument, but the results suggest that California students
are becoming less concerned about issues of race. Given the investment that
postsecondary institutions are making on diversity efforts, such a shift in attitudes
toward race is surprising.

In the current study, I hypothesized that the ban on afﬁrmative action
would lead to less favorable attitudes toward affirmative action in college
admissions and racial diversity. While this was true for racial diversity, it was not

true for affirmative action in college admissions. Though affirmative action

105

includes many other groups besides racial minorities, such policies are typically
viewed as targeting race (Aberson, 2003; Hurtado, 2005; Mukherjee, 2000).
Then it would stand to reason that attitudes toward affirmative action in college
admissions would move in the same direction as attitudes toward racial diversity.
However, the current study demonstrates that the issue is more nuanced as
attitudes toward affirmative action in college admissions and diversity shifted in
opposite directions. It may be that respondents view affirmative action in college
admissions as more than just racial preferences.

I have also shown in the current study how aggregate California student
attitudes moved toward more centrist views on affirmative action in college
admissions and racial diversity after the implementation of Proposition 209. The
previous research by Sax and Arrendondo (1999) and Zamani (2000) relied on
data only from 1996, but the inclusion of data from 1998 and 2000 provides for a
clearer picture of the trajectory of student attitudes toward racial diversity and
affirmative action in college admissions. It could be that in the absence of
affirmative action in college admissions, there is less tension over the policy or it
could be that less media attention in 2000 produced fewer polarized views.

Research Question 2
Do gender, political ideology, race/ethnicity, parent's educational attainment,
parent's estimated income, average high school grade, college entrance exam
scores, and college choice predict California freshmen attitudes toward
affirmative action in college admissions and racial diversity at four-year

institutions?

106

In the current study, I found that the previous variables used to predict
attitudes toward affirmative action in college admissions were applicable for the
California 4-year freshman cohort in 1996. However, the regression analyses
provide evidence that the factors were less predictive of attitudes toward
affirmative action in college admissions in 2000. SES and Academic Preparation
were not significant predictors in 2000. Additionally, the equations exhibited less
predictive power in 2000 compared to 1996. During the build up to Proposition
209, the variables included in this study might have been more relevant in
predicting attitudes toward affirmative action in college admissions, but student
attitudes in 2000 were less apt to follow the patterns from 1996. A significant
drop was found in the relationship between the affirmative action outcome
variable and political ideology. Significant drops were also found across all racial
categories as well for the affirmative action outcome variable.

Combined with the percent distributions, the regression analyses show
less polarized views in 2000 than in 1996 on the issue of affirmative action in
college admissions. Political ideology, race, and academic preparation were all
less significant predictors in 2000 than in 1996. Though it is unclear whether
Proposition 209 had an impact on this trajectory, increased media attention and
dialogue might have contributed to the more polarized views in 1996 leading up
to Proposition 209 (Nicholson, 2003; Sax & Arrendondo, 1999).

Men and those with more conservative political ideologies were more
likely to report that racial discrimination is no longer a major problem in American

across both years. All three racial minority groups were more likely than whites to

107

believe that racial discrimination is still a problem. Though the regression
coefficient was very low, academic preparation was a significant predictor across
both years with higher academic preparation correlated to greater concern for
racial discrimination. Lower SES levels in 1996 and not attending one’s choice of
college in 2000 were positively correlated with the belief that racial discrimination
is no longer a major problem in America.

Women and those with more liberal political ideologies were more likely to
believe in the importance of promoting racial understanding across both years.
All three racial minority groups were more likely than whites to believe in the
importance of promoting racial understanding across both years. Lower levels of
SES, higher levels of academic preparation, and attending one’s top choice for
college were all correlated with belief in the importance or promoting racial
understanding for 2000. SES, academic preparation, and choice of college were
not significant predictors in 1996.

Research Question 3
What differences exist between factors used to predict aggregate attitudes of
California freshman cohorts at four-year institutions toward affirmative action in
college admissions and racial diversity before and after the passage of
Proposition 209?

Using Chow’s test, I found significant differences between the regression
equations for 1996 and 2000 for the affirmative action in college admissions,
racial discrimination is no longer a problem, and helping to promote racial

understanding outcome variables.

108

T-tests of the regression coefficients for each of the outcome variables
were computed to determine what variables contributed to the signiﬁcant
differences. I offer a discussion of the differences between 1996 and 2000 for
each of the predictor variables below. The variables included in the study
performed moderately well in predicting attitudes toward afﬁrmative action in
college admissions in 1996, but not as well in 2000. The same items performed
poorly for the racial diversity outcome variables across both years.

Gender

Gender was a significant predictor of attitudes toward affirmative action in
college admissions for whites and Asian-Americans across both years and for
Hispanics/Latinos in 1996 with men more consistently opposed to the use of
affirmative action in college admissions. Because women have traditionally
benefited from affirmative action policies, it is not surprising that women would be
more likely to support affirmative action in college admissions. Previous research
has also found that women tend to support affirmative action more than men
(e.g., Kravitz & Plantania, 1993; Meader, 1998; Sax & Arrendondo, 1999;
Zamani, 2000). Zamani (2000) found that for two-year college students, gender
was a significant predictor of attitudes toward affirmative action in college
admissions across all racial groups.

In the current study gender was not a significant predictor for African-
American students indicating that African-American men and women were
equally likely to support affirmative action in college admissions. Gender was

also not a significant predictor for Hispanics/Latinos in 2000. Though gender was

109

a significant predictor for Hispanics/Latinos in 1996 with women more likely than
men to support affirmative action in college admissions, the regression coefficient
was quite small. This result suggests that race has more of an impact on student
attitudes toward affirmative action in college admissions than gender. There were
no significant differences in the predictive power of gender on attitudes toward
from 1996 to 2000 for any of the racial groups.

Gender was a significant predictor of the belief that racial discrimination is
no longer a major problem in America with women more likely to believe that it is
still a major problem. For whites and Hispanics/Latinos being female was a more
significant predictor in 1996 than in 2000, but being female was a more
significant predictor in 2000 for African-Americans. For African-Americans,
gender was not a significant predictor in 1996 but being female was signiﬁcantly
related to believing that racial discrimination is still a problem in America for the
2000 cohort. Appendix B shows that male and female African-Americans have
both moved toward believing that racial discrimination is no longer a problem, but
males more so than females.

Gender was also a significant factor for the dependent variable
“importance of helping to promote racial understanding” and was a more
significant factor overall in 1996 than in 2000. For whites, African-Americans, and
Asian-Americans being female was a more significant predictor in 1996 than in
2000. The regression results for all three dependent variables suggest that

women are generally more supportive of afﬁrmative action in college admissions,

110

believe that racial discrimination is still a problem, and that promoting racial
understanding is important.
Political Ideology

Political ideology was a more significant predictor of attitudes toward
affirmative action in college admissions in 1996 than in 2000 for all four racial
groups, but especially with whites. Consistent with the ﬁndings of Sax and
Arrendondo (1999) and Zamani (2000), I found in the current study a relationship
between opposition to affirmative action in college admissions and more
conservative political ideologies with one exception. The variable was not a
significant predictor of attitudes toward affirmative action in college admissions in
2000 for African-American respondents indicating that in that year African-
American students regardless of their political affiliations supported affirmative
action in college admissions.

Table 11 displayed the political ideology percentage distributions for both
years, which showed the sample was slightly more conservative in 1996. The
significant change in regression coefficients for each racial group from 1996 to
2000 suggests that political ideology was a major factor in shaping attitudes
toward affirmative action in college admissions for California freshmen. It is
unclear from the current study what role Proposition 209 had in shaping attitudes
toward affirmative action in college admissions, but the more significant
relationship between conservative political ideologies and opposition to
affirmative action in college admissions in 1996 is likely explained by the

increased attention given to the issue of affirmative action.

111

There was a relationship between conservative political ideologies and the
belief that racial discrimination is no longer a problem in America for white,
Asian-American, and Hispanic/Latino students, but there were no significant
differences in the predictive power of this variable between 1996 and 2000. For
the dependent variable “importance of helping to promote racial understanding,"
a more conservative political ideology was a more significant predictor in 1996
than in 2000 for whites and Asian-Americans. In both cases, those with more
liberal views were more likely to believe that promoting racial understanding is
important.

SES

SES was a significant factor in 1996 for the regression model with the
affirmative action dependent variable, but was not a significant factor in 2000.
Racial breakdowns indicate that SES was only a significant factor in 1996 for
Hispanic/Latino students with higher levels of SES associated with the desire to
abolish affirmative action in college admissions. SES was a significant factor in
2000 for white and Asian-American students with higher levels of SES
associated with the desire to abolish affirmative action in college admissions. Sax
and Arrendondo (1999) also found SES to be a small but significant factor for a
national sample of 1996 CIRP data. In their study, a positive correlation existed
between SES and desire to abolish affirmative action in college admissions for
white, Asian-American, and Hispanic/Latino students. Higher levels of SES for
African-Americans were associated with the desire to keep affirmative action in

college admissions likely do to the contentious ballot initiative in 1996. Zamani

(2000) found that for two-year college students higher levels of SES were
correlated with the desire to abolish affirmative action in college admissions for
white students only.

In the current study, the relationship between SES and attitudes toward
affirmative action in college admissions are less clear given the mixed findings
over the two years. .The results provided by Sax and Arrendondo (1996) and
Zamani (2000) were not replicated with the sample drawn from California. The
small beta coefficients for each of the affirmative action regression models is
evidence that SES is not a major predictor of attitudes toward affirmative action
in college admissions, but in some cases can account for a small portion of the
overall variance.

Higher levels of SES were negatively associated with the two racial
diversity dependent variables in 1996, but the beta coefficients were low at -.003
and —.002. SES was not a significant predictor for either outcome inl2000. The
racial breakdowns showed that lower levels of SES were only a significant
predictor of belief that racial discrimination is no longer a problem for whites and
Asian-Americans. As was the case with the affirmative action item, SES has little
impact on attitudes toward racial diversity.

Academic Preparation

Like SES, the beta coefficients were small indicating that academic
preparation was not a major predictor of attitudes toward affirmative action in
college admissions. However, there were several significant findings of note.

Higher levels of academic preparation were positively correlated with the desire

113

to abolish affirmative action in college admissions for white and Asian-American
students for both years but there was a stronger correlation in 2000 than in 1996
for white students. Sax and Arrendondo (1999) found a positive relationship for
white, Asian-American, and Hispanic/Latino students. Zamani (2000) found the
same pattern, but only for white freshmen at two-year institutions. The absence
of similar results among African-Americans and Hispanic/Latinos demonstrates
the importance that race plays in predicting attitudes toward affirmative action in
college admissions. Whites and Asian-Americans are less likely to support
affirmative action in college admissions overall. The combination of being white
or Asian-American and having higher levels of academic preparation leads to
greater opposition to affirmative action in college admissions confirming the
ﬁndings of Sax and Arrendondo (1999).

Academic preparation was a small but significant predictor of the belief
that racial discrimination is no longer a major problem for white, Asian-American,
and Hispanic/Latino students in 2000, but not in 1996. Higher levels of academic
preparation were positively associated with placing a greater level of importance
on helping to promote racial understanding for white and Hispanic/Latino
students in 2000, but not in 1996. In sum, higher levels of SES are associated
with believing that racial discrimination still exists and the importance of
promoting racial understanding, but those with higher levels of academic
preparation are more likely to oppose affirmative action in college admissions as

a mechanism to combat that discrimination.

114

Choice of College

Consistent with the findings of Sax and Arrendondo (1999), I found that for
white and Asian-American students in California attending less than the student’s
first-choice institution was correlated with the desire to abolish affirmative action
in college admissions across both years. For white students, the correlation was
significantly higher in 2000 than in 1996. This is interesting given that affirmative
action policies were not in place in selecting the 2000 California freshmen cohort.
This finding may indicate that white students not attending their ﬁrst-choice
institution still blame affirmative action. For Asian-American students the
correlation was significantly lower in 2000 than in 1996, which may indicate that
this group is less likely to blame affirmative action for their choice of institution.
The variable was not a significant predictor of attitudes toward affirmative action
in college admissions for African-American or Hispanic/Latino students. The
combination of being white or Asian-American and not attending one’s ﬁrst-
choice institution led to greater opposition to affirmative action in college
admissions.

Choice of college was a significant predictor of believing that racial
discrimination still exists today with race included in the model in 2000. There
was a small, positive relationship between attending one’s first-choice institution
and believing that racial discrimination is no longer a major problem in American
for 2000. However, the variable was not a significant predictor for 1996 or for any
of the regression models by race. Attending one’s first-choice institution was

negatively associated with placing a high level of importance on promoting racial

understanding for the overall regression model in 1996. The relationship only

held for white students in 1996 and for Asian-American students in 2000.
Research Question 4

If differences are found between the variables used to predict attitudes toward

affirmative action in college admissions and racial diversity, how did these vary

by racial group?

African-American, Asian-American, and Hispanic/Latino students were
significantly less likely than white students to favor abolishing affirmative action in
college admissions. The largest gap existed between white and African-American
students. The gap between the attitudes of white students toward affirmative
action in college admissions and the attitudes of African-American, Asian-
American, and Hispanic/Latino students was greater in 1996 than in 2000.
Appendix A shows how white and Asian-American students became more
tolerant of affirmative action in college admissions in 2000. In contrast, African-
American and Hispanic/Latino students were more likely to oppose affirmative
action in college admissions in 2000 than in 1996.

Though the regression model including race for the affirmative action
dependent variable performed well in 1996 it did not perform as well in 2000.
Table 23 shows the breakdown by racial groups. Every factor except for SES in
1996 was significant for white students. For Asian-Americans, SES in 1996 and
College Choice in 2000 were not significant. Overall, the factors were less

applicable to African-American and Hispanic/Latino students. Political ideology in

116

1996 was the only significant factor for African-Americans, meaning the group is
largely homogenous on the independent variables included in the study.

For the dependent variable “racial discrimination is no longer a major
problem in America,” African-American, Asian-American, and Hispanic/Latino
students were significantly more likely than white students to disagree. For
Asian-American and Hispanic/Latino students the difference was significantly
greater in 1996 than in 2000. For white and Hispanic/Latino students, gender and
political ideology were significant factors across both years. Political ideology
was also a significant factor for Asian-American students across both years and
gender was significant in 2000. The regression model performed poorly in both
years, but race, gender, and political ideology are factors that should be explored
further in examining beliefs about racial discrimination.

For the dependent variable “importance of helping to promote racial
understanding," all three racial minority groups were significantly more likely than
white students to place a greater importance on promoting racial understanding,
but more so in 2000 than in 1996. Gender and political ideology were significant
predictors for white, Asian-American, and Hispanic/Latino students. Again, the
models performed very poorly for both years, but the findings are similar to a
study conducted by Umbach and Milem (2004), in which they found that race,
gender, and interactions with people of another color were significant predictors
of attitudes toward racial diversity.

White students were significantly different from students in the other three

racial groups in their attitudes toward affirmative action in college admissions and

117

racial diversity. The differences between racial groups could actually be larger
given previous research that found that white respondents sometimes provide
socially desirable answers rather than their honest opinions (Cobb, 2001). Still, it
is clear that race continues to play a major factor in shaping policy attitudes with
the largest differences between white and African-American students.
Key Findings

There are four key findings from the study that l highlight here. First, the
mean changes for the affirmative action variable and the two racial diversity
variables moved in opposite directions. There was an increase in support for
affirmative action in college admissions in 2000 compared to 1996, counter to the
original hypothesis. At the same time there was a decrease in concern over racial
discrimination and in promoting racial understanding. This finding suggests that
attitudes toward affirmative action in college admissions and attitudes toward
racial diversity are distinct from one another. Affirmative action is often viewed
primarily as racial preferences (Aberson, 2003; Hurtado, 2005, Mukherjee, 2000).
However, the findings from the current study suggest that respondents do not
view affirmative action in college admissions and racial diversity in the same way.

The second key finding pertains to more centrist views about affirmative
action in college admission after the ban in California. More polarized views
about afﬁrmative action in college admissions in 1996 were likely to due to
Proposition 209 and the media build up about the issue (Nicholson, 2003). For
each racial group from 1996 to 2000, there was movement toward the middle of

the scale for attitudes toward affirmative action in college admissions. More

118

centrist views in 2000 make sense as students in that cohort would likely have
less concern over affirmative action policies and would have been less exposed
to the media influence regarding affirmative action. The rhetoric over affirmative
action is often intense with the media having particular influence in how the issue
is presented to the public (Kellstedt, 2000). The data in the current study
suggests that in the absence of intense media scrutiny and a major ballot
proposition, student attitudes toward affirmative action in college admissions are
more moderate than the typical rhetoric over the issue.

The third key finding is that being male, having a more conservative
political ideology, and being white were significant predictors of opposition to
affirmative action in college admissions and less concern for racial diversity. The
significant coefficients for these three predictor variables on all three outcome
variables for both years demonstrate the importance of these variables in
predicting attitudes toward affirmative action in college admissions and racial
diversity. The consistency for each of these predictor variables across both years
and all three dependent variables is noteworthy. Future research into attitudes
toward affirmative action in college admissions and racial diversity should
account for each of these variables. Furthermore, campus staff and faculty can
use this data to provide a general sense of how particular groups of students will
view affirmative action in college admissions and racial diversity. Less consistent
findings among the other predictor variables limit such generalizations.

Fourth, the data indicate that race is the most significant variable in

predicting attitudes toward affirmative action in college admissions and racial

119

diversity. Similar to the finding of Sax and Arrendondo (1999), whites and Asian-
Americans hold similar opposition to affirmative action in college admissions
while African-Americans and Hispanics/Latinos are more supportive. The
regression analysis for the afﬁrmative action outcome variable by racial groups
shows that higher levels of academic preparation and choice of college are only
significant predictors for whites and Asian—Americans. In 2000 with a less tense
political climate, none of the variables predicted opposition to afﬁrmative action in
college admissions for African-Americans and having a more conservative
political ideology was the only significant predictor for Hispanics/Latinos. For
whites in 2000 every variable was a significant predictor and for Asian-Americans
in 2000 every variable except college choice was a significant predictor of
attitudes toward affirmative action in college admissions. The model is less
applicable in measuring attitudes toward affirmative action in college admissions
for African-American and Hispanic/Latino students.
Lhnﬁaﬂons

The CIRP Freshman Survey provided a broad sample for the current
study, but the use of a secondary data set limited the variables and the years
available. The study is particularly hampered by the absence of the affirmative
action item on the CIRP Freshman Survey before 1996 and in 1998. The current
study could have offered a more complete story had the question been asked
before 1996 allowing for a more complete picture of the trajectory of attitudes

toward affirmative action in college admissions. Including data beyond the 2000

120

cohort could also provide useful insight into the more recent trajectory of student
attitudes toward affirmative action in college admissions and racial diversity.

The sample was limited to freshman attending four-year postsecondary
institutions in California. Students at two-year institutions and students outside of
California may have different views on affirmative action in college admissions
and racial diversity. The current study examined differences between cohorts, but
more longitudinal research is needed to examine how students develop attitudes
toward racial diversity and affirmative action in college admissions over the
college years. Additional research is needed to establish a baseline of student
attitudes toward racial diversity and then examines how that changes as students
advance in through college.

The R2 value for the affirmative action dependent variable dropped from
.251 in 1996 to .133 in 2000 indicating that the model had less predictive power
in 2000. Political ideology, race, and academic preparation were more significant
factors of attitudes toward affirmative action in college admissions in 1996
leading up to the ban on affirmative action in California. Given the lack of model
fit in 2000, more work is needed to improve the model for predicting attitudes
toward affirmative action in college admissions. More exploratory work is needed,
but the CIRP Freshmen Survey is limited by the variables included each year.
Yet, the CIRP Freshmen Survey offers a unique opportunity to explore affirmative
action and racial diversity using longitudinal data.

The low R2 values for the three racial diversity regression models indicate

a need to improve the models. Measuring attitudes toward racial diversity

121

requires exploring multiple dimensions beyond just race. Other items could have
been included from the CIRP Freshman survey that might have provided a more
robust model for the diversity outcome variables. I chose to include independent
variables that had previously been used to predict attitudes toward affirmative
action in college admissions, but these items performed less well for the racial
diversity outcome variables. In order to develop a more robust measure of
student attitudes toward diversity, more exploratory work is needed with the
CIRP data across multiple years.
Suggestions for Future Research

The current study offers additional insight into the attitudes of freshman
toward affirmative action in college admissions and racial diversity. The data from
1996 and 2000 indicate that student attitudes, at least in California, have shifted
significantly over the five year period. I found in the current study that previous
factors used in regression models to predict attitudes toward affirmative action in
college admissions were less applicable in 2000 and that the model was less
applicable in measuring attitudes toward racial diversity. I did find a consistent
relationship between gender, political ideology, and race on each of the outcome
variables. Males, those with more conservative political ideologies, and white
students were more likely to oppose affirmative action in college admissions and
less concerned about racial diversity across both years. Given these findings and
their consistency with previous research (e.g., Meader, 1998; Sax & Arrendondo,

1999, Zamani, 2000), these variables should be included in studies measuring

student attitudes toward affirmative action in college admissions and racial
diversity.

In the current study, I also found that race was the most significant
predictor of attitudes toward afﬁrmative action in college admissions. Though
other factors such as SES and college choice were significant predictors, on the
whole, they applied only to whites and Asian-Americans. Higher levels of SES
and not attending one’s first-choice college were not significantly related to
attitudes toward affirmative action in college admissions for African—American
and Hispanic/Latino students. This indicates that among African-American and
Hispanic/Latino students, affirmative action in college admissions is supported
regardless of SES or choice of college. Because whites and Asian-Americans
are more likely to oppose affirmative action in college admissions in general, the
addition of other variables appears to add toward opposition. However, race is
the most significant predictor of attitudes toward affirmative action in college
admissions.

The current study revealed more centrist views toward affirmative action in
college admissions across all four racial categories. Future research could
explore whether attitudes toward affirmative action in college admissions become
more polarized because of other major policy events around the issue. The
absence of the afﬁrmative action item on the CIRP Freshman Survey prior to
1996 prevents the current study from using a pre-post design. With other states
considering ballot initiatives to eliminate affirmative action, researchers can

explore whether similar results exist across different years and states. The CIRP

123

Freshmen Survey provides a useful tool for the current study because the survey
is housed in California. However, other states may have smaller, less
representative samples using the CIRP dataset.

The current study provides initial evidence that students became less
concerned about racial diversity but more supportive of affirmative action in
college admissions from 1996 to 2000. The current study does not offer data to
sufficiently explain this finding. It does indicate that students have a nuanced
understanding of affirmative action and do not necessarily see it as just a race-
based policy. This finding could suggest that less concern about racial diversity
goes in hand with a decrease in opposition to affirmative action in college
admissions. However, this seems unlikely. Though students reported less
concern about racial discrimination and promoting racial understanding, the shift
toward more support for affirmative action in college admissions is likely due to
less polarization around the issue in 2000. Additional research is needed to
determine how students view affirmative action in college admissions and racial
diversity differently.

Researchers using the CIRP or other similar datasets are limited to a finite
set of questions that may not adequately measure the intended constructs. l was
interested primarily in the impact of Proposition 209 on attitudes toward
affirmative action in college admissions and racial diversity, but the current study
can not attribute causality. More complex survey designs that ask specific
questions about affirmative action policy events could provide more direct data

about the impact that such policies have on student attitudes. More work is

124

needed by researchers and postsecondary institutions to gather longitudinal data
on student attitudes toward affirmative action in college admissions and racial
diversity. Such a framework allows institutions to see how students on campus
are changing over time. It would allow postsecondary institutions to examine how
certain events, whether they are related to state policy or campus happenings,
impact student attitudes.

The current study uses quantitative methods to explore student attitudes
toward racial diversity and affirmative action in college admissions, but more
qualitative work is needed to examine how students make sense of affirmative
action. Previous research has shown that people do not fully understand
affirmative action (Zamani & Brown, 2003). Student development professionals
could benefit from more exploratory work on attitudes toward affirmative action in
college admissions and racial diversity. Though separate from racial diversity,
affirmative action as a policy is intended to increase diversity on campus. More
qualitative work is needed to explore how the two concepts are related, which
may also offer additional assistance in building more robust quantitative
instruments to measure the two constructs.

Implications for Promoting Diversity within Higher Education

The passage of Proposition 209 in California marked a major turning point
in the battle over afﬁrmative .action. In the current study, I have shown how
student attitudes toward affirmative action in college admissions and racial
diversity changed after affirmative action was banned in California. The current

study shows that the 2000 freshmen cohort entered college believing that racial

discrimination was less of a problem than the 1996 cohort and that promoting
racial understanding was less important. Appendix A and Appendix B show that
the trend toward less concern for racial diversity is present for male and female
students across all four racial categories.

The data indicates that in the absence of affirmative action policies in
college admissions, students are less concerned about racial diversit.
Thernstrom and Thernstrom (1997) argued that race-sensitive admissions
increases racial hostility among students. Though evidence has been lacking to
support this claim, the current study indicates that across all four racial
categories race becomes less of a factor without affirmative action admissions
policies. However, the interpretation of this finding depends on one’s perspective
about the role of race on college and postsecondary campuses. If the objective is
to have a color-blind campus, then this finding suggests that in the absence of
affirmative action in college admissions, students arrive to college more color-
blind. However, this belief may ignore racial divisions that are prevalent in
society.

The decrease in concern for racial diversity by students is important given
the ongoing disparities between racial groups in the US. Statistics for housing,
education, income, and wealth indicate that racial divisions still exists within the
US. (Bostic, 1996; Bucks, Kennickell, & Moore, 2006; Schmidt, 2007b), but
across all four racial groups the trend indicates that students believe that
discrimination is less of a problem. Colleges and universities actively promote

diversity as an intended learning outcome and this should include the historical

126

legacy of discrimination in the US. (Chang, 2002; Hurtado et al., 1999). The
CIRP survey questions are not nuanced enough to make distinctions between
students perception of historical discrimination and views on the role of race in
contemporary society, but the decrease in concern for racial diversity indicates
that practitioners seeking to educate students about the importance of racial
diversity may have a longer way to go in educating students about existing racial
discrimination and the importance of promoting racial understanding.

For campuses seeking to promote diversity as a learning outcome for
students, the CIRP Freshman Survey data can provide a baseline to measure
entering students’ attitudes toward diversity, but to capture more detail regarding
student attitudes toward racial diversity additional techniques should be
employed. Gathering longitudinal data about student attitudes toward diversity is
becoming increasingly important to establish the benefits of affirmative action in
college admissions and diversity programming. Without such data,
postsecondary institutions will struggle to justify policies and funding devoted to
increasing diversity.

Those in higher education must do more to articulate the importance of
examining racial disparities and develop purposeful educational opportunities for
students to consider the role that race plays in society. As attacks on affirmative
action mount in other states, postsecondary institutions should actively address
the topic of race within the curriculum. Examining the racial gaps that still exist is

needed to determine the relevance of affirmative action programs. Failing to

 

account for these differences could have serious consequences for racial
minorities in the US.
Conclusions

The passage of Proposition 209 in California was a major policy event with
significant ramifications for higher education in the state and across the country.
Since California banned affirmative action in 1996, Texas, Florida, Georgia,
Washington, Michigan, and Nebraska have banned the use of afﬁrmative action
in college admissions as well. The proposal to ban the use of afﬁrmative action in
Colorado in 2008 was rejected by voters with only 50.7% of the vote. Though the
current study showed only minor changes in student attitudes toward affirmative
action in college admissions, it could be that small changes among voters could
decide the fate of affirmative action in the near future.

Universities have an interest in the outcome of the debate over affirmative
action. “The mission of virtually every college and university extends beyond the
needs and rights of the individual student and institution to include as well an
aspiration to improve the communities and lives of people who live beyond the
university wall” (Whitt, Chang, & Hakuta, 2003, p. 10). The public, governments,
and the courts will inevitably decide the fate of affirmative action in the United
States, but more work is needed by the higher education community to fully
explore the outcomes of eliminating afﬁrmative action.

The current study is a ﬁrst step in looking more broadly at the longitudinal
outcomes of banning affirmative action. Though previous research has examined

the longitudinal outcomes of banning affirmative action on student enrollment,

more work is needed to examine alternative outcomes. The psychological climate
and behavioral climate on campus are an integral part of institutional diversity
and should be regularly assessed. If done regularly, campuses in states that
have passed measures to eliminate afﬁrmative action should be able to examine
the impact that such measures have on institutional diversity and campus
climate.

As the debate over affirmative action continues to mount, postsecondary
education will be pressed to justify the use of race-conscious admissions
policies. The impact that race-based policies have on student development
should be at the center of the debate given the importance that diversity plays in
educating students of all races. However, due to the historical discrimination
against minority groups in the US. and'persistent disparities between racial
groups in education and the workforce, higher education must ensure that racial
and ethnic minority groups are represented adequately on campus (Loo &
Rolison, 1986). If representation is lacking, the psychological and behavioral
dimensions of campus climate will suffer as well (Hurtado, Milem, Clayton-

Pedersen, & Allen, 1998).

129

83:00.00 n v 0:0 .:0to:E_ .o: u _. 00:2, 000.: v o. F 0 :0 005000.).

a

zmcobm 0050 n v 0:0 20:98 00500.: n F 0.0:; 0000 v o. r 0 :0 005000.). 0

“00:963. 0. “mm...“ H0:02

 

 

:8: 8:. 2:. :8: 8:0. :8. :8: :8. 80. :8: m8. :8. .v Q: 8830: 98:90
. :8.: 8:: :8: .88: 88 :8: .22: 8.: :8 :8:: 2 :2 88 8: z
.080: :8.: 8.: :2.:: 8.: 8.: .82: 2.: 8.: 8:0: 8.: 8.: .029 0: 80.2
0 96:06:02:
060: 08an
9 @520: :o 00:0:085
:8: :::. 8:. :8: 8:. :8. :8: 80. 80. :8: 8:. 8:. .v a: 8830: 288.0
:8: 88 0:8 .080: 88 88 .82: 20 :8 .2:::: 38: :08 8: z
.800: 8:: 8.: :8. 2 2: 2.: :0: .2 3: m: 8.: :82: 8.: ::.: .028 c 80.2
0 00:0E<
:_ E039: 8.0.: 0 :0m:o_
o: w. :o_.0:_E:0m_: .0.00m
:88: 8. :8. .8: :8. m8. :8: :8. 80. :8: 2m. :8. .v a: 8830: 28:30
.88: 8:: 8: .88: 88 88 .8: 2: 8: : 8 :2 2:: 082 88 8: z
:8:: 2.: 8.: :8:: :0: ::.: 8:0: 8.: :0: : 8.2: 8.: 8.: .028 0: :82
a 88:80
0: 030:0 0:28.800
0m0=oo :_ 8.80 02:08:56.
:8: 88 82 .8... 88 82 .8.-. 88 82 :8: 88 82

 

o:..0-..0.:0:0_I

 

:00:0E<-:0_w<

 

:00:0E<-:00E<

0.__..>>

 

:00» 0:0 000: :3 0.:0:0> E02080 :000 .2 0.005%? :005. .:< 0.00.:

< X.DZm.n_n.<

130

.0..:0mw0 u 0 0:0 E0002: .0: I : 0:0:3 0.000 0 0. : 0 :0 0050005.

 

0
30:08.. 00:00 u 0 0:0 30:00.0 00:08.0 n : 0:0:2, 0.000 0 0. : 0 :0 005000.). 0
000. 000. 000. :00. :00. 0:0. 000. :00. 50030:: 0:00:90
::0 0:0 0:: wow 0000 0000 00 :0 :0 :0 z
::.N 00.: 0:: :00 00.: 0:.N 00.: 00.0 :005.
0 0:.0:0:m:00::
.060: 0.0::0:0 0. 0:.0.0: :0 00:00006.
000. 0:0. :0:. N00. 0::. :N:. 00:. 00:. 8.8300 0:00:05
0:0 0mm 00: 00: 00:: 0000 0000 00:0 2
00.: :N: 00.: 00.: 00.: 00.: 00.: :0: :005.

0 00.:0E< :. 80.00::

5.0:: 0 :00:0. 0: m. :0..0:.E.:00.0 .060”.

: :0. 00:. 0:0. 000. 000. 000. 0N0. 000. :o.:0.>0o 0:00:05
0:0 0:0 omm 0cm 0000 0N00 mam 00N0 Z
00.: 00.: 00.: :0: N0.N mod 00.0 0:.0 c005.

m 88.08 8 288
mCmeFCUm mmmzoo C_ Cozom m>5mCtE<

000.0. 000: ooom 000: ooom 000: ooom 000:
0.0E0n. 0.0.2 0.0::0n. 0.0.2
:00.:0E<-:00.::< 0:.:>>

:00: 0:0 .:00:0.« .000: :0 0.00.:0> 0:00:0000 :000 :0: 000:0000: :005. :0 0.00:.

 

m X.DZMn.n_<

131

.0.::0000 n 0 0:0 800008. :0: n : 0:002, 0.000 0 0: : 0 :0 005000.).

0

>.0:0::0 00:00 u 0 0:0 20:080 00:000.0 n : 0:0:3 0.000 0 0: : 0 :0 0050005. 0

 

132

 

000. :00. :00. 000. 000. 0:0. 0:0. 0:0. 50030:: 0:00:05
0::: 00:: 000: 000 0:0: 000: :00: 000: 2
00.0 00.0 00.0 00.0 00.0 00.0 0:.0 00.0 :00.).
0 0:.0:0:0:00::
.0.00: 0:080:0 0: 0:.0.0: :0 00:0:008.
00:. 000. 00:. ::0. 00:. 0:0. 00:. 0::. 800500 0:00:05
:00: :00: :00: 0:0 0:0: 000: 000: 000: z
00.: 00.: 0:: 00.: 0:: 00.: 00.: :0: :00.).
0 00.:08< :. 80.090
5.08 0 :00:0. 0: 0. :0.:0:.8.:00.0 .0600.
::0. 0:0. :00. :00. 000. 000. :00. 000. 800300 0:00:05
:0: : 00:: 000: 000 000: 0 :0: 000: 0:0: 2
::.0 :0: 00.0 00.: 00.0 :00 0:.0 0:.0 :00.).
0 00:0..000 00 0.00:0
0:0.00800 000:00 :. :0000 02:08:00.0
0000 000: 0000|.000: 0000 000: 000Il000:
0.080“. 0.0.2 0.080“. 0.0.).

 

0:.:0._\0.:000.I

 

:00.:08<-:0.0<

:00: 0:0 .:00:0m .000: :0 0.00.:0> ::00:0000 0000 :0: 000:0000: :00.). 00.803 :0 0.00...

 

BIBLIOGRAPHY

Aberson, C. L. (2003). Support for race-based afﬁrmative action: self-interest and
procedural justice. Journal of Applied Social Psychology. 33, 1-15.

Affirmative action. (2004). The American Heritage® Dictionary of the English
Language, Fourth Edition. Retrieved November 02, 2006, from
http://www.answers.com/topic/affirmative-action

Alexander, M. (2000, October 16). Elite for hire: Company business and
marketing. Industry Standard. Retrieved February 11, 2007, from
http://www.findarticles.com/p/articles/mi_mOHWW/is_42_3/ai_66672918

America, R. F. (1986). Affirmative action and redistributive ethics. Journal of
Business Ethics, 5(1), 73-77.

American Psychological Association (1996). Affirmative Action: Who Beneﬁts?
Washington, DC: Author. Retrieved February 11, 2007, from
http://www.apa.org/pubinfo/affirmaction.html

American Psychological Association. (1997). Testimony of the American
Psychological Association: H. R. 1909 ’The Civil Rights Act of 1997'
[Testimony]. Washington, DC: Author. Retrieved February 11, 2007, from
the American Psychological Association Web site:
http://www.apa.org/ppo/testimon.html.

Anderson, T. H. (2004). The Pursuit of Fairness: A History of Affirmative Action.
Oxford: Oxford UP.

Anderson, T. H. (2005). The strange career of affirmative action. South Central
Review, 22(2), 110-129.

Andolina, M. W., & Mayer, J. (2003). Demographic shifts and racial attitudes:
How tolerant are whites in the most diverse generation. The Social
Science Journal, 40, 19-31.

Antonio, A. L. (2001). Diversity and the influence of friendship groups in college.
Review of Higher Education, 25(1), 63-89.

Antonio, A. L., Chang, M. J., Hakuta, K., Kenny, D. A., Levin, 8., & Milem, J. F.
(2004). Effects of racial diversity on complex thinking in college students.
Pyschological Science, 15(8), 507-510. .

Astin, A. W. (1993). Assessment for excellence. Phoenix, AZ: Oryx.

133

Astin, A. W., & Sax, L. J. (1998). How undergraduates are affected by service
participation. Journal of College Student Development, 39(3), 251-263.

Bacon, J. (1996, November 12). California students protest affirmative action
ban. USA Today, p. 3A.

Bali, V. A., & Alvarez, R. M. (2004). The race gap in student achievement scores:
Longitudinal evidence from a racially diverse school district. Policies
Studies Journal, 32(3), 393-415.

Bastedo, M. N. (2003, November). Cascading minority students in higher
education: Assessing the impact of statewide admissions standards.
Paper presented at the Association for the Study of Higher Education
Conference, Portland, Or.

Bikson, T. K., & Law, S. A. (1994). Global preparedness and human resources:
College and corporate perspectives. Santa Monica, Calif: RAND
Corporation.

Blacks remain an extreme minority at university of california campuses. (2005,
October 6). Diverse Issues in Higher Education, 22(17), 9.

Bobo, L. D., & Fox. C. (2003). Race, racism, and discrimination: Bridging
problems, methods, and theory in social psychological research. Social
Pyschology Quarterly, 66(4), 319-332.

Bostic, R. W. (1997). The role of race in mortgage lending: Revisiting the boston
fed study. Board of Governors of the Federal Reserve System Finance
and Economic Discussion Series #97-2. Retrieved October 12, 2007, from
http://ssrn.com/abstract=21 35

Bowen, W. G., & Bok, D. (2000). The shape of the river: Long-term
consequences of considering race in college and university admissions.
Princeton, NJ: Princeton University Press.

Bowman, C. (1996, April 13). Liberal to rally against the right: S.F. march
tomorrow in support of affirmative action. San Francisco Chronicle, p. A14.

Brown, M. C. (2001). Collegiate desegregation and the public black college.
Jouma/ of Higher Education, 72(1), 46-62.

Brown, S. K., & Hirschman, C. (2006). The end of affirmative action in
washington state and its impact on the transition from high school to
college. Sociology of Education, 79, 106-130.

Bucks, B. K., Kennickell, A. B., & Moore, K. B. (2006). Recent Changes in US.

 

Family Finances: Evidence from the 2001 and 2004 Survey of Consumer
Finances. Federal Reserve Bulletin. Retrieved October 12, 2007, from
http://www.federalreserve.gov/pubs/osslossZ/2004/bul|0206.pdf

Cain, B. E., & Macdonald, K. (1997, Dec. 3 -5). Affirmative action as a wedge
issue: Prop 209 and the 1996 presidential election. Paper presented at the
Latino Civil Rights Crisis, Cambridge, Massachusetts. Retrieved February
5, 2007, from http://www.civilrightsproject.harvard.edu/research/latin097
llatin097.php

California Postsecondary Education Commission. (n.d). Custom Data Reports.”
Retrieved July 18, 2008 from http:l/www.cpec.ca.gov/OnLineData/
OnLineData.asp

Carnevale, A. P., & Fry, R. A. (2000). Crossing the great divide: Can we achieve
equity when generation y goes to college? Princeton, NJ: Educational
Testing Service.

Carter, S. L. (1991). Reflections of an afﬁrmative action baby. New York: Basic
Books.

Chandler, K. (2005, August 18 - 24). Black enrollment in florida colleges
plummets as percentage of hispanics surges. Westside Gazette, p. 3.

Chang, M. J. (1996). Racial diversity in higher education: Does a racially mixed
student population affect educational outcomes? Unpublished doctoral
dissertation, University of California, Los Angeles.

Chang, M. J. (2000). Improving campus racial dynamics: A balancing act among
competing interests. The Review of Higher Education, 23(2), 153-175.

Chang, M. J. (2002). Preservation or transformation: Where’s the real
educational discourse on diversity. Review of Higher Education, 25(2),
125-140.

Chang, M. J., Witt, D., & Hakuta, K. (2003). Afﬁrmative action practices in a
broader context. In M. J. Chang, D. Witt, J. Jones, & K. Hakuta (Eds),
Compelling Interest: Examining the Evidence on Racial Dynamics in
Colleges and Universities (pp.170-183). Stanford, CA: Stanford UP.

Chavez, L. (1998). The Color Bind: California’s Battle to End Affirmative Action.
Berkeley: University of California Press.

Citrin, J. (1996). Affirmative action in the people’s court. The Public Interest, 122,
39—48.

135

Clawson, R. A., Kegler, E. R., & Waltenburg, E. N. (2001). The legitimacy-
conferring authority of the us. supreme court: An experimental design.
American Politics Research, 29(6), 566-591.

Cobb, M. D. (2001). Unobtrusively measuring racial attitudes: The consequences
of social desirability effects. Dissertation Abstracts lntemational, 62, 2869.
(UMI No. 3023034

Cooper, K. J. (2000, August 16). University of Georgia to appeal ruling against
affirmative action. Washington Post, A10.

Crosby, F. J., lyer, A., & Clayton, S. (2003). Affirmative action: Psychological
data and the policy debates. American Psychologist, 58(2), 93-115.

Crosby, F. J., lyer, A., & Sincharoen, S. (2006). Understanding affirmative action.
Annual Review of Psychology, 57, 585-611.

Fain/veather, J. S. (1995). Myths and realities of academic labor markets.
Economics of Education Review, 14(2), 179-192.

Fairweather, J. S. (2005). Beyond the rhetoric: Trends in the relative value of
teaching and research in faculty salaries. Joumal of Higher Education,
76(4), 401 -422.

Farkas, G. (2003). Racial disparities and discrimination in education: What do we
know, how so we know it, and what do we need to know. Teachers
College Record, 105(6), 1119-1146.

Feldman, S., & Huddy, L. (2005). Racial resentment and white opposition to
race-conscious programs: principles or prejudice. American Journal of
Political Science, 49(1), 168-183.

Fischer, K. (2005, April 22). Class-rank plan faces trouble in texas. Chronicle of
Higher Education, 51(33), p. A25.

Ghilagaber, G. (2004). Another look at chow’s test for the equality of two
heteroscedastic regression models. Quality & Quantity, 38, 81-93.

Glaeser, E. L., & Vigdor, J. L. (2001, April). Racial segregation in the 2000
census: Promising News. Retrieved February 11, 2007, from The
Brookings Institution, Center on Urban & Economic Policy Web site:
httpzllwww.brookings.edu/es/urban/census/glaeser.pdf

Glazer-Raymo, J. (1999). Shattering the myth: Women in academe. Baltimore:
Johns Hopkins

Green, D. O. (2004). Fighting the battle for racial diversity: A case study of
michigan’s institutional responses to gratz and grutter. Educational Policy,
18(5), 733-751.

Gujarati, D. (1970, February). Use of dummy variables in testing for equality
between sets of coefﬁcients in two linear regressions: A note. American
Statistician, 24(1), 50-52.

Gurin, P. (1999). The compelling need for diversity in higher education: Expert
testimony in gratz, et al. v. bollinger, et al. Michigan Journal of Race &
Law, 5, 363-425.

Gurin, P., Dey, E. L., Hurtado, S. & Gurin, G. (2002). Diversity and higher
education: Theory and impact on educational outcomes. Harvard
Educational Review, 72, 330-366.

Hajnal, Z. & Louch, H. (2001). Are there winners and losers: Race, Ethnicity and
California’s Initiative Process. San Francisco: Public Policy Institute of
California.

Hall, R. M., & Sandler, B. R. (1984). Out of the classroom: A chilly campus
climate for women? Washington, DC: Association of American Colleges.

Healy, P. (1998, October 30). Foes of preferences try a referendum in
washington state: Opinion is divided on afﬁrmative action, but the debate
is quiet at the state’s flagship campus. Chronicle of Higher Education, p.
A34.

Heilman, M. E. & Blader, S. L. (2001). Assuming preferential selection when the
admissions policy is unknown: The effects of gender rarity. Journal of
Applied Psychology, 86, 188-193.

Henderson—King, D. & Stewart, A. J. (2000). Learning about social diversity: The
undergraduate experience and intergroup tolerance. Journal of Higher
Education, 71(2), 142-164.

Higher Education Research Institute. (n.d.). CIRP Program Overview. Retrieved
online October 31, 2008 from http://www.gseis.ucla.edu/heri/
cirpoverviewphp

Horn, C. L., & Flores, S. M. (2003). Percent Plans in College Admissions: A
Comparative Analysis of Three States’ Experiences. Cambridge, MA: The
Civil Rights Project at Harvard University.

Hurtado, A. (2005, Winter). Toward a more equitable society: Moving fon/vard in

137

 

 

the struggle for affirmative action. The Review of Higher Education, 28(2),
273-284.

Hurtado, S. (2001). Linking diversity and educational purpose: How diversity
affects the classroom environment and student development. In G. Orﬁeld
(Ed), Diversity Challenged: Evidence on the Impact of Afﬁrmative Action
(pp.187-203). Cambridge, MA: Harvard UP.

Hurtado, S., Dey, E., 8 Trevino, J. (1994). Exclusion or self-segregation:
Interaction across racial/ethnic groups on college campuses. Paper
presented at the American Educational Research Association conference,
New Orleans.

Hurtado. S., Milem, J. F., Clayton-Pedersen, A. R., & Allen, W. R. (1998).
Enhancing campus climates for racial/ethnic diversity: Educational policy
and practice. Review of Higher Education, 21(3), 279-302.

lnkelas, K. K. (2003). Diversity’s missing minority: Asian paciﬁc American
undergraduates’ attitudes toward affirmative action. The Journal of Higher
Education, 74(6), 601-639.

lnkelas, K. K. (2004). Does participation in ethnic cocurricular activities facilitate a
sense of ethnic awareness and understanding: A study of asian pacific
american undergraduates. Journal of College Student Development,
45(3), 285-302.

Kahlenberg, R. D. (1996). The Remedy: Class, Race, and Affirmative Action.
New York: Basic Books.

Kane, E. W., & Kyyro, E. K. (2001). For whom does education enlighten: Race,
gender, education and beliefs about social inequality. Gender and Society,
15(5), 710-733.

Kellstedt, P. M. (2000). Media framing and the dynamics of racial policy
preferences. American Journal of Political Science, 44(2), 245-260.

Kinder, D. R., & Winter, N. (2001). Exploring the racial divide: Blacks, whites, and
opinion on national policy. American Journal of Political Science, 45(2),
439-456.

Laubscher, M. (1994). Encounters with difference: Student perceptions of the
role of out-of-class experiences in education abroad. Westport, CT:
Greenwood Press.

Lewis, J. (2001). Constructing public opinion: How political elites do what they
like and why we seem to go along with it. New York: Columbia UP.

138

Lieb, D. A. (2008, January 8). Affirmative action ballot language unfair, judge
rules. Retrieved November13, 2008, from
http://www.columbiamissourian.com/
stories/2008/01/07/affirmative-action-ballot-language-unfair-judge-ru/

Loo, C. M., & Rolison, G. (1986). Alienation of ethnic minority students at a
predominately white university. Journal of Higher Education, 57, 58-77.

Look what happens when afﬁrmative action is banned: Black students are
pushed down into second- and third-tier institutions of higher education.
(2001-2002, Winter). Journal of Blacks in Higher Education, 34, 82-94.

Loury, G. C. (1998). Performing without a net. In G. E. Curry (Ed. ), The
Affirmative Action Debate (pp. 49-64). Cambridge, MA: Perseus Books.

Marin, P., & Lee, E. K. (2003). Appearance and Reality in the Sunshine State:
The Talented 20 Program in Florida. Cambridge, MA: The Civil Rights
Project at Harvard University.

Meader, E. W. (1998, November). College student attitudes toward diversity
and race-based politics. Paper presented at the Annual Meeting of the
Association for the Study of Higher Education, Miami, FL.

Milem, J. F ., & Hakuta, K. (2000). The benefits of racial and ethnic diversity in
higher education. In D. Wilds (author), Minorities in higher education:
Seventeenth annual status report (pp.39-67). Washington, DC: American
Council on Education.

Mondak, J. J. (1994). Policy Legitimacy and the Supreme Court: The Sources and
Contexts of Legitimation. Political Research Quarterly, 47(3), 675-692.

Moore, J. (2005). Race and College Admissions: A case for Affirmative Action.
Jefferson, NC: McFarland & Company.

Moore, K. (1982). Women and Minorities. Leaders in Transition: A National Study
of Higher Education Administrators. University Park, PA: Center for the
Study of Higher Education, Pennsylvania State University. (ERIC
Document Reproduction Service No. ED225459)

Morfin, O. J., Perez, V. H., Parker, L., Lynn, M, Arrona, J. (2006). Hiding the
politically obvious: A critical race theory preview of diversity as racial
neutrality in higher education. Educational Policy, 20(1), 249-270.

Moses, M. S. (2001). Affirmative action and more favorable contexts of choice.
American Educational Research Journal, 38(1), 3-36.

Mukherjee, R. (2000). Regulating race in the california civil rights initiative:
Enemies, allies, and alibis. Journal of Communication, 50(2), pp. 27-47.

Newman, J. D. (1989). Affirmative action and the courts. In F. A. Blanchard & F.
J. Crosby (Eds), Affirmative Action in Perspective (pp. 31-50). New York:
Springer-Verlag.

Nicholson, S. P. (2003). The political environment and ballot proposition
awareness. American Journal of Political Science, 47(3), 403-410.

Paternoster, R., Brame, R., Mazerolle, P., & Piqueor, A. (1998). Using the correct
statistical test for the equality of regression coefficients. Criminology,
36(4), 859-866.

Peterson, M. W., & Spencer, M. G. (1990). Understanding academic culture and
climate. New Directions for Institutional Research, 68, 3-18.

Pike, G. R. (2002). The differential effects of on- and off-campus living
arrangement on students' openness to diversity. NASPA Journal, 39(4),
283-299.

Proposal 2: Frequently asked questions. (n.d.). Retrieved February 11, 2007,
from the Michigan Civil Rights Initiative Web site:
http://www.michigancivilrights.org/media/MCRI_FAQs.pdf

Pusser, B. (2004). Burning Down the House: Politics, Governance, and
Affirmative Action at the University of California. Albany: State University
of New York Press.

Raza, M. A., Anderson, A. J., & Custred, H. G. (1999). The Ups and Downs of
Affirmative Action Preferences. Westport, CT: Praeger.

Rendon, L. |., Novack, V., & Dowell, D. (2005). Testing race-neutral admissions
models: Lessons from California State University-Long beach. Review of
Higher Education, 28(2), 221-243.

Rothman, S., Lipset, S. M., & Nevitt, N. (2002, Fall). Diversity and afﬁrmative
action: The state of campus opinion. Academic Questions, 52-66.

Sax, L. J., & Arrendondo, M. (1999). Student attitudes toward affirmative action in
college admissions. Research in Higher Education, 40(4), 439-459.

Schmidt, P. (2006, November 17). Michigan overwhelmingly adopts ban on
affirmative—action preferences: Foes of the ballot measure vow to keep
fighting while supporters eye new fronts. Chronicle of Higher Education,
53(13), p. A23.

140

Schmidt, P. (2007a, June 1). What color is an a: Colleges take on a persistent
but rarely discussed issue - the poor grades earned by many minority
students. The Chronicle of Higher Education, 53(39), A24.

Schmidt, P. (2007b, October 19). Five more states curtail affirmative action:
Ballot measures pushed by ward connerly are likely to win passage.
Chronicle of Higher Education, 54(8), p. A1.

Sedlacek, W. E., Helm, E. G., & Prieto, D. O. (1997). The relationship between
attitudes toward diversity and overall satisfaction of university students by
race (Report No. UMCP-RR-3-97). College Park, MD: Counseling Center.
(ERIC Document Reproduction Service No. ED 411 752)

Selingo, J. (2006, November 17). A new era for higher education. Chronicle of
Higher Education, p. A1.

Smith, D.G., & Associates. (1997). Diversity works: The emerging picture of how
students beneﬁt. Washington, DC: Association of American Colleges and
Universities.

Springer, L., Palmer, 8, Terenzini, P., Pascarella, E., & Nora., A. (1996).
Attitudes toward campus diversity: Participation in a racial or cultural
workshop. Review of Higher Education, 20(1), 53-68.

Suthammanont, C. M., & Peterson, D. (2004). Affect, cognition and the
conditional nature of race-related policy attitudes. Paper presented at the
annual meeting of the The Midwest Political Science Association,
Chicago, Illinois. Retrieved October 5, 2007, from
http://www.allacademic.com/meta/p82357__index.html

Tapia, R. A. (2007, September 28). True diversity doesn’t come from abroad.
Chronicle of Higher Education, 54(5), p. B34.

Texas 10 percent plan has not improved minority representation, republican
leader says. (2005, Feb. 10) Black Issues in Higher Education, p. 14.

Thernstrom, S., & Thernstrom, A. (1997). America in Black and White: One
Nation Indivisible. New York: Simon & Schuster.

Thurmond, V. A., Wambach, K., Connors, H. R., & Frey, B. B. (2002). Evaluation
of student satisfaction: Determining the impact of web-based environment
by controlling for student characteristics. The American Journal of
Distance Education, 16(3), 169-189.

Timar, T. B., Ogawa, R., Orillion, M. (2004). Expanding the university of

141

california’s outreach mission. The Review of Higher Education, 27(2), 187-
209.

Trent, W., Owens—Nicholson, D., Eatman, T. K., Burke, M., Daugherty, J., &
Norman, K. (2003). Justice, equality of educational opportunity, and
affirmative action in higher education. In M. J. Chang, D. Witt, J. Jones, &
K. Hakuta (Eds), Compelling Interest: Examining the Evidence on Racial
Dynamics in Colleges and Universities (pp.22-48). Stanford, CA: Stanford
UP.

Trow, M. (1999). California after racial preferences. The Public Interest, 135, 64-
85.

US Bureau of the Census. (1975). Historical Statistics of the United States,
Colonial Time to 1970, Bicentennial Edition. Washington, DC: US.
Government Printing Ofﬁce.

US. Census Bureau (1990). General Population and Housing Characteristics:
1990. Retrieved June 18, 2008 from US. Census
httpzllfactfinder.censusgov

US. Census Bureau. (2002). Census 2000 Summary File 1 (SF1) — 100 Percent
Data, Table DP-1 Proﬁle of General Demographic Characteristics: 2000.
Retrieved 11 February 2007 from US. Census
http://factfinder.census.gov.

US. Department of Education. (2006). A Test of Leadership: Charting the Future
of U. 8. Higher Education. Washington, DC.

Umbach, P. D., & Milem, J. F. (2004). Applying holland’s Wpology to the study of
differences in student views about diversity. Research in Higher
Education, 45(6), 625-649.

University of California. (n.d.). Statistical Summary and Data on UC Students,
Faculty, and Staff. Retrieved online May 8, 2008 from
http://www.ucop.edu/ucophome/uwnews/stat/

University of California at Los Angeles. (n.d.). CIRP Freshman Survey: Reliability
and Validity. Retrieved online October 31, 2008 from
http://www.gseis.ucla.edu/heri/PDFs/C|RP_Reliabi|ity_Validity.PDF

University of Texas. (2005). Statistical Handbook 2004-2005. Retrieved online
May 8, 2008 from http://www.utexasedu/academic/oir/

University of Washington. (n.d.). Student Headcount by Ethnicity and Student

142

Level. Retrieved online October 29, 2008 from
http://www.washington.edu/admin/factbook/taba5.pdf

Vernez, G., Krop, R. A., & Rydell, P. (1999). Closing the Education Gap: Benefits
and Costs. Santa Monica: RAND.

Vernon-Gerstenfeld, S., & Burke, E. (1985). Affirmative action in nine large
companies: A field study. Personnel, 62(4), 54-60.

Virtanen, S. V., & Huddy, L. (1998). Old-fashioned racism and new forms of
racial prejudice. The Journal of Politics, 60(2), 311-332.

Weiss, R. (1997). We Want Jobs: A History of Afﬁrmative Action. New York:
Garland.

Whitt, E. J., Edison, M. l., Pascarella, E. T., Terenzini, P. T, & Nora, A. (2001).
Influences on student openness to diversity and challenge in the second
and third years of college. Journal of Higher Education, 72(2), 172-204.

Wiedeman, R. (2008, November 14). State ballots on stem cells and race are
decided. Chronicle of Higher Education, 55(12), A1.

Wise, T. J. (2005). Afﬁrmative Action: Racial Preference in Black and White.
New York: Routledge.

Witt, D., Chang, M. J., & Hakuta, K. (2003). Introduction. In M. J. Chang, D.
Witt, J. Jones, & K. Hakuta (Eds), Compelling Interest: Examining the
Evidence on Racial Dynamics in Colleges and Universities (pp.1-21).
Stanford, CA: Stanford UP.

Witt, D., & Shin, C. (2003). Historical summary of afﬁrmative action. In M. J.
Chang, D. Witt, J. Jones, & K. Hakuta (Eds), Compelling Interest:
Examining the Evidence on Racial Dynamics in Colleges and Universities
(pp.185-201). Stanford, CA: Stanford UP.

Witt, J. L. (1990). Affirmative action and job satisfaction: Self-interested vs. public
spirited perspectives on social equity: Some sobering findings from the
academic workplace. Review of Public Personnel Administration, 10(3),
73-93.

Zamani, E. M. (2000). Aspiring to the baccalaureate: Attitudes of community
college student toward affirmative action in college admissions.
Dissertation Abstracts International, 61(5), 1724. (UMI No. 9971236)

Zamani, E. M., & Brown, M. C. (2003). Affirmative action in postsecondary

educational settings: The historic nexus of meritocracy and access in US.
higher education. Higher Education Policy, 16, 27-38.

144

 

 

IljlliijjjilljjjjIjjljjl