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Enumerating Black identity in higher education

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Enumerating Black identity in higher education

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Enumerating Black Identity in Higher Education
by
Jocelyn Y. Stewart

Rossier School of Education
University of Southern California
A dissertation submitted to the faculty
in partial fulfillment of the requirements for the degree of
Doctor of Education

December 2021

© Copyright by Jocelyn Y. Stewart 2021
All Rights Reserved

The Committee for Jocelyn Y. Stewart certifies the approval of this Dissertation

Jose A. Gomez
Nicole Maccalla
Erika Patall
Patricia Tobey, Committee Chair

Rossier School of Education
University of Southern California
2021

iv
Abstract
This study examines the impact of federally mandated race categories and methodology on the
enumeration of Black identified students at a public university in the western United States. The
purpose of this work is to explore how Black identified individuals who are multiracial or
multiethnic make meaning of race categories and to examine the effectiveness of current
enumeration practices in reflecting the self-reported identity of individuals in this population.
Interviews with Black identified multiracial students provided qualitative data. An analysis of
institutional records (secondary data) collected by the university yielded quantitative data. The
research led to several key findings: (a) the use of the federally mandated definition of Blackness
led to an undercount of Black identified students, (b) applying an all-inclusive whole assignment
methodology resulted in a measure of Black identity that was larger than the population reported
using the federal methodology and provided an approach that respects and acknowledges the
self-identity expressed by participants, (c) the disaggregation of the “two or more races” category
allows for a fuller view of the student population, and (d) individuals who have experienced
identity denial use race surveys to assert their identity and as a vehicle to talk back to the survey
creators. These findings have implications for creating nuanced and useful enumeration
methodologies in higher education, methodological approaches that more accurately reflect the
way multiracial individuals report and experience identity in the 21st century.

v
Dedication
To my parents, Simeon and Ida.
To the memory of my friend and mentor Frank D. Godden.

vi
Acknowledgements
I was blessed to have the love and support of a very wide circle of family and friends
throughout this journey. Without this support, my dissertation experience would have been far
less fulfilling. While this group is too numerous to name in full, I extend my deepest gratitude to:
Glenda and Marvin Halsey, Antonia and Lowell “Chris” Christian, Simeon and Jennifer Stewart,
Autumn and Diante Luckey, Dr. Yasmin and Gregory Delahoussaye, Karen Bilbrew, Paula
Bryant, Dr. Kwame Cooper, Aunt Dolores Sheen, the Stewart-Taylor Family, Vanessa Bradley,
LaShauna Warren, Bernadette Smith, Glenda Taylor-Goree, Rozella Boyce, Carla Rivera, Sheila
Dixon-Howard, Alvenia Wideman, Lynell George, Adrienne Martin, Yumiko Whitaker and my
church family; and to the next generation: Brandon Smith, Shanae Smith, Jasmine Christian,
Lauren Halsey, Dominic Halsey, Aujane, Dael, D’yani, Londyn, Sage, and Simeon for being my
inspiration. To Dr. Tiffany Young, Dr. Lisa Jo Keefer, and Jillian Beck, for sharing this journey
with me and providing encouragement, support, and fun.
Thank you to my wonderful dissertation committee chair and committee: Dr. Patricia
Tobey, Dr. Jose Gomez, Dr. Nicole Maccalla, and Dr. Erika Patall. A special thank you to those
individuals who participated in my study and trusted me with their stories.

vii
Table of Contents
Abstract .......................................................................................................................................... iv
Dedication ....................................................................................................................................... v
Acknowledgements ........................................................................................................................ vi
List of Tables ................................................................................................................................. ix
List of Figures ................................................................................................................................. x
Chapter One: Redefining Race ....................................................................................................... 1
Background of the Problem ................................................................................................ 3
Statement of the Problem .................................................................................................... 5
Purpose of the Study ........................................................................................................... 6
Significance of the Study .................................................................................................... 8
Limitations and Delimitations ............................................................................................. 9
Definition of Terms........................................................................................................... 10
Organization of the Study ................................................................................................. 12
Chapter Two: Review of the Literature ........................................................................................ 14
Race Identity and Identification ........................................................................................ 15
Racial Identity ................................................................................................................... 16
Identity Denial and Identity Assertion .............................................................................. 18
Racial Identification and the History of Race Categories ................................................. 21
The Same Population, Different Numbers ........................................................................ 31
The Importance of Data Methodology .............................................................................. 33
QuantCrit Theory .............................................................................................................. 37
Summary ........................................................................................................................... 39
Chapter Three: Methodology ........................................................................................................ 41
Rationale for the Methodology ......................................................................................... 42

viii
Phase 1: Quantitative ........................................................................................................ 44
Phase 2: Qualitative .......................................................................................................... 50
Chapter Four: Findings ................................................................................................................. 53
Participants (Quantitative) ................................................................................................ 54
Results Research Question 1 ............................................................................................. 54
Discussion Research Question 1 ....................................................................................... 55
Results Research Question 2 ............................................................................................. 56
Discussion Research Question 2 ....................................................................................... 58
Results Research Question 3 ............................................................................................. 59
Discussion (Quantitative).................................................................................................. 62
Participants (Qualitative) .................................................................................................. 63
Results Research Question 4 ............................................................................................. 67
Results Research Question 5 ............................................................................................. 73
Summary ........................................................................................................................... 80
Chapter Five: Discussion .............................................................................................................. 82
Findings............................................................................................................................. 83
Implications for Practice ................................................................................................... 92
Conclusion ........................................................................................................................ 94
References ..................................................................................................................................... 98
Appendix A: Timeline of Race Categories in Education............................................................ 111
Appendix B: Interview Questions ............................................................................................... 112
Appendix C: Information Sheet for Exempt Research ............................................................... 117
Appendix D: Informed Consent for Research ............................................................................ 119

ix
List of Tables
Table 1: 2007 Final Guidance on Reporting Aggregate Racial and Ethnic Categories 24
Table 2: Race Category Variables 43
Table 3: A Black Identified Population at Public University 57
Table 4: Two or More Races Category Disaggregated 60
Appendix B: Interview Questions 112

x
List of Figures
Figure 1: Black and Black/Multiracial Identification at Public University 55
Figure 2: Comparative Analysis of Disaggregated Two or More Races Category 60
Figure 3: From Identity Denial to Identity Strategy 86
Appendix A: Timeline of Race Categories in Education 111

1

Chapter One: Redefining Race
For more than a decade, a federally mandated methodology has determined how race is
categorized, counted, and reported on the campuses of colleges and universities in the United
States (U.S. Department of Education, 2007). Data on race and ethnicity that is used by federal
agencies and often posted on the websites of colleges and universities is shaped by this little-
known methodology (College Navigator, n.d.). In 2009, the U.S. Department of Education
implemented a policy that mandated the methodology for race data collection and reporting with
the stated goal of standardizing race data practices and providing sufficient options for racial
self-identity given the nation’s growing diversity (Office of Management and Budget, 1997; U.S.
Department of Education, 2007). The new policy placed the data collection methods in line with
the 2000 U.S. Census, which was the first in the nation’s history to invite respondents to mark
one or more races (Jones & Smith, 2001). Yet, the methodology, when applied in higher
education, may have also produced unintended consequences for the racial demographics of
institutions by contributing to the decrease and/or increase of subpopulations, including Black
students.
A key element of the methodology is the taxonomy for collecting and reporting race and
ethnicity. The definition of Blackness that is required for reporting race data was narrowed in the
methodology so only students who identify themselves as Black only are included in the Black
race category (Office of Management and Budget, 2001). This practice excludes individuals who
are Black and multiracial and those who are Black and Latino or Afro Latino. The resulting
Black definition contrasts sharply with the nation’s historic use of hypodescent or the “one drop
rule” to determine who is Black. Under that practice, people who possessed any African heritage
2

were categorized as Black (Hickman, 1997; Ho et al., 2015; Jordan & Spickard, 2014). The
methodology rewrote race taxonomy and retired the “one drop rule.”
Some researchers have questioned these categories and methodology because of their
potential detrimental impact on Black students. Some expressed concern that the methodology
would lead to an undercount of Black identity (Lee & Orfield, 2006) and obscure the needs of
Black multiracial populations (James, 2012). The policy changes have complicated the
interpretation of data by making it more difficult to compare pre-1997 data with later data sets
that utilized a different definition of the Black racial category beginning in 2009 (Bates et al.,
2019). Such comparison is necessary to track performance in metrics and for civil rights
monitoring. The guidance that accompanied the new policy pointed to several bridging methods
as a means of comparison over time (Office of Management and Budget, 2001). The creators of
the guidance also acknowledged that some subpopulation numbers would decrease but
downplayed the significance of this decline (Office of Management and Budget, 2001).
The issue is not just one of personal preference versus institutional accounting, given the
many ways race data is used on college and university campuses. Scholars have examined a long
list of Black student experiences in higher education in relationship to race, including admissions
(Contreras et al., 2015), campus climate (Harper & Hurtado, 2007), stereotype threat (Rydell et
al., 2017), and postgraduate enrollment and completion (Tienda & Zhao, 2017). Race counting is
also important for civil rights monitoring (Lee & Orfield, 2006; Zuberi, 2001). In the 21st
century, a growing number of educators use data to inform policy decisions (Pazzaglia et al.,
2016).
This dissertation problematizes the race categories and methodology implemented by the
U.S. Department of Education. I do not refute the existence of racial disparities in outcomes or of
3

achievement gaps identified by scholarship that relies on this data. Instead, this study
hypothesizes that the tabulation and reporting of race and ethnicity results in an undercount of
Black identified students. Further, this methodology does not require the reporting of the specific
combinations of multiracial students, including those who identify as Black. The failure to know
and acknowledge the decline caused by collection and reporting practices may obscure outcomes
and efforts to create appropriate services and interventions.
Background of the Problem
California has the fifth largest population of Black people in the nation, but Black
students remain underrepresented on the campuses of the state’s public university systems
(Campaign for College Opportunity, 2021). Overall, Black students made up only 4% of
California State University (CSU) campuses in 2018 (California State University, 2018;
Contreras et al., 2015). The underrepresentation of Black students was greater at individual
campuses, particularly those that are considered more prestigious (Contreras et al., 2015). At the
University of California, Berkeley, the UC system’s flagship campus, the population of Black
students was just 1.9% in 2016; at Cal Poly San Luis Obispo, Black students were only 0.7% of
the population (Costley, 2018; Harper & Simmons, 2019). The data on Black students who are
admitted to public universities in California suggests students are struggling. Only 9% of Black
CSU freshmen complete a degree in 4 years and 57% of Black CSU freshmen do not complete a
degree within 6 years (Bates et al., 2019).
The underrepresentation of Black students at public universities means fewer of them
enjoy the benefits of higher education and a college degree, including the CSU’s success in
pushing students up the ladder of economic mobility (Chetty et al., 2017). A landmark
longitudinal study published by the Equality of Opportunity Project examined universities’
4

success in graduating students who go on to experience measurable upward socioeconomic
mobility (Chetty et al., 2017). Students moved from the bottom 20% of the income ladder to the
top 20%. Among the list of institutions identified for leading the nation were those in the CSU
system (Chetty et al., 2017). The nationwide leader was California State University, Los Angeles
(Cal State LA). Yet, in 2018, the total Black student population of Cal State LA was only 3.3%
(Cal State LA, Office of Institutional Effectiveness, 2020).
The data show that California’s Black population has the capacity for greater
representation on the campuses of the state’s public universities (Campaign for College
Opportunity, 2021). The state’s public university systems, however, have not translated that
potential into greater Black student enrollment and success. While other factors may contribute
to the low numbers of Black students on public university campuses, including Proposition 209,
which led to the end of affirmative action (Campaign for College Opportunity, 2015), the
potential to grow the population still exists. This gap in Black student potential and Black student
success calls for a close examination of factors affecting what we know about this population,
including the methodology used to collect and report race and ethnicity data in higher education.
Under the federal methodology, all multiracial respondents are reported in a broad racial
category labeled “two or more races” (Office of Management and Budget, 2001). As a result,
individuals who may identify themselves as Black by checking the box, would not be recognized
as such under this methodology if they also checked another race or ethnicity. For example, if he
were a student, President Barack Obama, whose father was Kenyan and mother was White,
would not be reported in the Black or White race categories. Obama would be labeled as “two or
more races.” Vice President Kamala Harris would join Obama in that category. She would not be
identified as a Black and Indian woman, the distinction that made her run for the vice presidency
5

historic. Abolitionist Frederick Douglass, a former slave, would also be reported in the “two or
more races” category. Actress Halle Berry, recording artist Prince, and the rapper Drake would
also be placed in the “two or more races” category. Because the methodology defines racial
categories, it may also have created a disconnect between the ways individuals who identify as
Black and multiracial and multiethnic report their identity and the way they appear in
institutional data.
Statement of the Problem
In the years since the implementation of the federally mandated methodology, key
questions remain. It is not known how the methodology changed the count of Black identified
students at colleges and universities or subpopulation trends over time. Although some studies
have examined how differing methodologies change population counts (Gullickson & Morning,
2011; Perez & Hirschman, 2009), a gap exists in our understanding of such changes in the
context of higher education, specifically in the aftermath of the 2009 policy change and
methodology implementation. The methods used to collect and report data on Black students at
colleges and universities in the United States may fail to accurately measure Black student
presence and Black student outcomes (Lee & Orfield, 2006). This is a significant problem in
California, a diverse state where an achievement gap persists between Black students and
majority students in college going rate, persistence, and other outcomes (Bates et al., 2019).
Copious data reveal racial disparities in student outcomes and experiences (Aud et al., 2010;
Campaign for College Opportunity, 2021). However, recent scholarship on collecting and
interpreting quantitative data suggests that research design and choices that shape data outcomes
should be rigorously questioned as a starting point for critiquing such data (Garcia et al., 2017;
Gillborn et al., 2017).
6

The extent of public awareness of the federal methodology for race data collection and
reporting is not clear. The policy has broad implications for higher education data and for
individual representation. Yet, it is not known if individuals who identify as Black and
multiracial know how the methodology represents their identity. In the aftermath of the 2000
census, discussions about multiracial identity increased and researchers examined many
dimensions of the issue of multiracial identity. These questions remain.
Purpose of the Study
The purpose of this mixed methods study is to determine how race and ethnicity data for
Black identified students at the pseudonymous Public University have changed in the years
following the implementation of a federally mandated policy and the implications of the change
for individuals. A longitudinal analysis of the data produced by a narrowing of the Black racial
category mandated by the policy is central to this study. Data collected from interviews offers a
view of the experiences of individuals who are Black and multiracial.
This study will use a convergent mixed methods design, in which quantitative data and
qualitative data are collected separately, analyzed separately, and then compared (Creswell &
Creswell, 2018). The study consists of two phases, quantitative and qualitative. The quantitative
phase will explore the numerical representation of Black identity and the identity information
hidden in the “two or more races” category. The qualitative phase of the study will explore the
experience of racial identification for individuals who are Black and multiracial and multiethnic,
the meaning attached to selecting racial categories, and the expectations associated with self-
identification.
The research was guided by five research questions:
7

1. What are the key 10-year demographic trends for the Black student subpopulation
and the Black multiracial/multiethnic subpopulation at Public University?
2. How does the demographic profile (number and proportion) of Black students at
Public University change when an all-inclusive whole assignment bridging
methodology is applied to the student population?
3. What are the most frequent race combinations found at Public University when
the “two races or more category” is disaggregated?
4. How do Black multiracial or multiethnic people who have experienced identity
denial view and interact with race and ethnicity survey questions?
5. How does the reporting of Black identity, as mandated by the federal government,
align with expectations and assumptions for reporting held by Black multiracial or
multiethnic people?
The theoretical lens for this study was QuantCrit, a branch of Critical Race Theory (CRT)
rooted in the core idea that quantitative numbers should be interrogated because they are not pure
but reflect decisions and views of researchers (Garcia et al., 2017). QuantCrit further asserts the
value of personal narratives in interrogating and understanding numbers (Garcia et al., 2017).
The conceptual framework for this study proposes that lived experiences, sometimes over
decades, influence how individuals self-identify on race surveys, yet a federal methodology that
mandates how race is measured on U.S. campuses (Office of Management and Budget, 2001),
imposes race categories that usurp self-identity. This study hypothesizes that this federal
methodology leads to an undercount of Black identified students. The qualitative section of this
study will explore how people who are Black and multiracial approach race surveys and their
expectations for how their data will be used. This study defines Black identified students as those
8

who self-identify as Black solely or as Black and another race or ethnicity. QuantCrit is an
appropriate lens for this mixed methods study because it promotes an in-depth questioning of
data, and it centers the voices of individuals reflected in and affected by the data.
Significance of the Study
This study builds on research that seeks to explain how the federal methodology used to
collect and report race and ethnicity data can change population counts (Gullickson & Morning,
2011; Perez & Hirschman, 2009). These studies acknowledge race as a construct, and as such
view the race categories and the requirements for reporting as part of the construct. My research
aims to expand the discourse on Black students and Black multiracial students by situating race
category definition and reporting as a central element of discussion in higher education. Those
tasked with supporting excellence in academia should know the student population as it defines
itself. This study prioritizes the identity choices of respondents and their narratives as an
alternative way to interpret data on race.
The race taxonomy and methodology used to count Black students produces data that is
widely consumed (College Navigator, n.d.). Students, faculty, staff, administrators, and other
stakeholders in higher education make decisions, identify problems, and shape programs and
interventions based in part on race data. Some of these statistics reside on the websites of
colleges and universities on pages dedicated to campus demographics or profiles. The U.S.
Department of Education hosts a national database known as the College Navigator that allows
students to access a wide range of statistics, including race data on thousands of colleges
(College Navigator, n.d.).
Race survey data can play a significant role in determining if Black students can see
themselves belonging at a particular college or university. A study of Black students found that
9

low percentages of Black students at a university can have a profound impact on student
decisions (Contreras et al., 2015). Contreras et al. (2015) found that high achieving Black high
school students reported that they researched race data and were deterred from applying to
certain University of California campuses by the exceedingly low percentage of Black students.
Because students perceived campuses with low numbers of Black students as unwelcoming, they
pursued other options outside of the public system, including Ivy League universities and
Historically Black Colleges and Universities, or HBCUs (Contreras et al., 2015).
Researchers have emphasized the centrality of research design and survey instruments in
the attempt to find accurate answers to questions of interest (Brockopp & Hastings-Tolsma,
2003; Creswell & Creswell, 2018). Teranishi (2007) argued that when researchers select
populations for inclusion in research, exclusion of other populations—and what is lost by their
exclusion—should be an explicit concern. He questioned the universal applicability of race
methodology to all groups and the assumption of comparability. Increasingly, researchers using
the quantitative components of Critical Race Theory have argued that the research design and
instruments of quantitative data must be heavily scrutinized if they are to be useful for creating
social justice (Garcia et al., 2017). Teranishi (2007) proposed that researchers should ask
questions about the motivation of the research, which may lead to a choice of different research
approaches. This dissertation will build upon the work and recommendations of previous
researchers by implementing recommended approaches to race data specifically (Teranishi,
2007) and quantitative data (Garcia et al., 2017).
Limitations and Delimitations
Because this research uses existing secondary data collected by the university, the study
will be limited to the variables and methodology used. It would have been cost prohibitive to
10

collect data as extensive as that which was already available. Another possible limitation will be
the comparability of race and ethnicity data to any data on student outcomes. If the data on
student outcomes was not collected using the same taxonomy as that used in the collection of
race and ethnicity data, a direct comparison may not be possible. The research will also be
limited by the years of data that the university makes available.
The research is delimited to an examination of Black students and multiracial students
and multiethnic students with Black identity. Using a different methodology for categorizing and
enumerating these students may have ramifications for other subpopulations. While recognizing
this impact, it is beyond the scope of this study to explore each subpopulation. The purpose of
my research was to explore the impact of race categories on these groups. This study does not
explore racial categories in light of new commercially available genetic testing procedures, but
as more people learn their genetic makeup, an exploration of socially constructed race categories
may help place the genetic testing results in context.
Definition of Terms
This section provides definitions of key terms, policies, theories, and constructs that are
central to a discussion of race and ethnicity. These definitions explain the usage of the terms in
the context of this study.
Afro Latino: A person of African descent with Latin American roots, or a multiracial
person with one Black parent and one parent or foreparent with Latin American roots.
All-inclusive whole assignment: In this form of enumeration, a student is assigned to
every racial category they select on a survey. The student’s response is enumerated as a full
response in that category, which means the total will exceed 100% (National Forum on
Education Statistics, Race/Ethnicity Data Implementation Task Force, 2008).
11

Biracial: A person who identifies with two races.
Black identified: This study uses Black identified to refer to individuals who identify
themselves as Black, regardless of their ethnicity or their selection of additional races in defining
their identities.
Black multiracial/multiethnic: This term is used in this study to refer to students who
identify as Black in combination with another race or ethnicity.
Bridging: Bridging refers to the process of making race data collected using pre-2009
standards comparable to data collected using post-2009 standards (National Forum on Education
Statistics, Race/Ethnicity Data Implementation Task Force, 2008).
Disaggregated data: Disaggregated data refers to numerical data that has been broken
down into smaller parts.
Federal race methodology: The term federal race methodology refers to the manner of
collecting and reporting race data set as a minimum standard by the Office of Management and
Budget and implemented by the U.S. Department of Education in 2009 (Office of Management
and Budget, 2001). Under this methodology, only students who self-identify as Black and no
other race or ethnicity are reported as Black. International students and students who are not
documented are not included in the count.
Fractional assignment: This term refers to the practice of fractionating and assigning
multiracial individuals to more than one race category when enumerating or categorizing by race
(Mays et al., 2003).
Identity assertion: As defined by Cheryan and Monin (2005), identity assertion is a
process in which a person proves to others that they belong to a particular group.
12

Identity denial: Identity denial refers to the experience of multiracial, multiethnic or
multicultural individuals being denied membership in the groups with which they identify
(Albuja et al., 2019; Cheryan & Monin, 2005).
Known number: This research uses known number to acknowledge that the true number
of students in any racial or ethnic group is based on limited and often incomplete data. It further
acknowledges the huge gulf in knowledge caused by the growing percentage of students who
select “other” or refuse to select a race or ethnicity category. Thus, the resulting demographic
information and numbers are those that can be known based on the available data.
Mixed race: Of more than one race.
Monoracial: One race.
Multiethnic: A person who identifies with more than one ethnicity.
Multiracial: A person who identifies with more than one race.
Office of Management and Budget (OMB): The Office of Management and Budget’s
mission is to carry out the U.S. president’s policy, budget, management, and regulatory
objectives, as well as to meet the agency’s statutory responsibilities (The White House, n.d.).
This agency created the federal policy on race and ethnicity data collection and reporting that
was implemented on college and university campuses in 2009.
Organization of the Study
The study is organized to provide a road map of the research. Chapter One outlined the
background of the problem, the statement of the problem, the purpose of the study, the
significance of the study, limitations and delimitations, and a definition of terms. Chapter Two is
a literature review that explores research, history, and ideas that are central to the topic of this
study. Chapter Three details the manner in which the study will be conducted, including the
13

sample population, instrumentation, data collection, and data analysis. In Chapter Four
quantitative and qualitative results and findings are presented. The results are detailed and
illustrated with charts, graphs, and figures. Chapter Five offers a discussion of the results,
implications for practice, and recommendations for future research.

14

Chapter Two: Review of the Literature
The enumeration of students is foundational to constructing an accurate profile of a
university or college student body, yet the counting of race is nuanced, historically complex, and
presents an increasing challenge to the field of higher education. By mandating the use of
specific racial categories and reporting methods in 1997, the U.S. Department of Education
sought to standardize enumeration and address its complexities (Office of Management and
Budget, 1997). However, in the years since then, there has not been a national study to determine
the effectiveness of mandated race data collecting and reporting methodology in accurately
capturing Black identity on college and university campuses in the United States. Further, there
is a gap in our knowledge of the ways in which the federally mandated race data collecting and
reporting methodology may impact the count of Black identified students in higher education. It
is also not known how Black multiracial and Black multiethnic students engage with race survey
questions and understand the ways in which race data is reported.
The purpose of Chapter Two is to provide a context for the current research and to
demonstrate how it is built on and expands existing knowledge about counting Black identified
students in higher education. As such, the literature review examines themes that are key to the
enumeration of Black multiracial identity in higher education. This discussion weaves together
the salient strains of scientific research, public policy, history, and data practices. The review
offers a view of the foundation on which the current study will be built.
How people choose to identify racially versus how they are identified in surveys is a key
topic in the discussion. Within the area of Black multiracial self-identification, key concepts and
themes include race fluidity, identity denial, microaggressions, and identity assertion. An
important component of the discussion of enumeration is the sweeping federal policy changes in
15

1997 that altered race data collecting and reporting nationwide and their implications for self-
identification. An examination of bridging methods details the various approaches available to
interpret data prior to and after 1997 and the various population counts they produce. In the
United States, counting students by race and ethnicity is a standard, federally sanctioned practice,
yet because of enumeration’s wide-ranging influences, complex history, and future implications,
this examination and the current study are merited.
QuantCrit, a branch of Critical Race Theory (CRT) that calls for a critical approach to
examining quantitative data, such as race data, provides the theoretical framework for this
research study. There are five tenets of QuantCrit: (a) racism as complex, deeply embedded, and
not easily quantified; (b) categories are not natural or given and units of analysis must be
evaluated; (c) numbers are not neutral and must be interrogated; (d) data cannot speak for itself;
the experiential knowledge of groups and people is critical; and (e) statistical analyses have a
role to play in the push for social justice (Garcia et al., 2017). Given the nature of the research
questions, this literature review is shaped around tenets b, c, and d. The tenets of QuantCrit
provide a framework for questioning the construction of race categories as well as the data that
result from race categorization. QuantCrit also acknowledges the role that experiential
knowledge of groups and individuals can play in understanding quantitative data. QuantCrit is
built on the concept of questioning numbers and questioning numbers is central to this research
study.
Race Identity and Identification
In the decades since 2000, when the census first instructed respondents to “mark one or
more races to indicate what this person considers himself/herself to be,” (Jones & Smith, 2001,
p. 1), qualitative and quantitative studies have explored dimensions of multiracial identity. These
16

studies reveal the layers of complexity that make up multiracial identity and the importance of
categories, terminology, and word choice. Some scholars distinguish between an individual’s
racial identity and racial identification. Internal racial identity has been defined as what an
individual believes about their race (Harris & Sim, 2002). Racial identification often refers to the
way people identify themselves on surveys and demographic forms (Brunsma, 2005). This
fundamental distinction is central to a significant body of research about multiracial and
multiethnic identity.
Racial Identity
Scholars view racial self-identity as a salient aspect of a person’s identity (Brown et al.,
2011) and positive identity as key to positive psychosocial functioning, mental health, and
academic outcomes among adolescents of color (Rivas-Drake et al., 2014). Among Black youth,
a more positive racial/ethnic identity was associated with desirable coping behaviors (Zaff et al.,
2002). In a study of young Black girls, Belgrave et al. (2004) found that participation in a
cultural intervention increased positive racial/ethnic identity and decreased relational aggression
such as gossiping, verbal insults, and exclusion of others. Affirmation and belonging were
associated with less depressive symptoms among early adolescent youth (Mandara et al., 2009).
The process of determining self-identity is considered a significant milestone in the
development of youth of color (Rivas-Drake et al., 2014). Gullickson and Morning (2011)
describe race in the United States as a cognitive dimension of social interaction that people use to
understand their social world (Gullickson & Morning, 2011). Decuir-Gunby (2009) identifies
race as one of the most significant socially constructed variables within identity development.
The later years of adolescence correspond with the time a student on a traditional educational
path enters a college or university. Some scholars place these later years, 18 to 22, in a period of
17

life defined as emerging adulthood (Syed & Mitchell, 2013) and identify this time as an
important period of defining oneself and race as a part of that development.
Fluidity
Many scholars agree that racial self-identity is not a fixed or permanent feature but is
fluid and varies with context (Harris & Sim, 2002; Johnston et al., 2014). As an inherently
developmental process, race can change over time and place (Charmaraman et al., 2014). Studies
on fluidity in racial identity provide evidence of its existence with the same respondents
providing different self-identification (Harris & Sim, 2002, Johnston et al., 2014). In their
analysis of the patterns of racial classification in the National Longitudinal Study of Adolescent
Health, Harris and Sim (2002) found that 12% of youth offered different identities when asked
nearly identical questions about race. This work underscores the importance of context, home
versus school. Their analysis of students found that 54% of youth who identified as multiracial at
home were not identified as multiracial in school data. Similarly, 75% of students who were
identified as multiracial in school data were not multiracial at home. Johnston et al. (2014) found
similar inconsistencies when examining the responses of students to three race surveys that
utilize different terminology and race options. In their study, a significant number of responses
changed in accordance with changes in the options offered on surveys, thus highlighting the role
of word choice and race categories offered on race fluidity. What is most consistent in these
studies is that for many adolescents of color, race is socially constructed and fluid (Harris & Sim,
2002).
Various factors may influence race fluidity and inconsistency in self-reporting race,
particularly in younger people. Harris and Sim (2002) pointed to differing perspectives on race
between parents and their children, a mismatch between the parents’ identity and that of the
18

child, and whether a parent is present during the interview. Patterns of identification may be
historical, such as the “one drop rule” that for decades identified anyone of African descent as
Black, or contemporary, and they may coexist (Gullickson & Morning, 2011). Brunsma (2005)
found that identification is based on the options that are available to an individual and may result
from the structure and discourse of identification. Racial identity may be situational (Renn,
2000) and influenced by geography, family socialization, family functioning, community
socialization, gender, class, and sexual orientation (Root, 2003). Some individuals may select
“some other race” when asked their racial identity because survey categories are insufficient or
possibly to signal a rejection of the notion of race itself (Dowling, 2014). Given complexities
such as these, some scholars have expressed concern that post-2000 race conceptualizations may
not capture the nuances inherent in race self-identity among youth (Harris et al., 2015).
Implications for Race Survey Responses
The complexity of racial self-identity has implications for surveys and demographic
forms that include questions about race and ethnicity. The work of Johnston et al. (2014)
underscores the role of word choice and options offered on race fluidity. Their findings contrast
with the work of Hirschman et al. (2000), who concluded that the addition of more race options
in the 2000 census had only a slight impact on the composition of the population. Racial self-
identity on a survey is not a reflection of a fixed identity for some individuals but can be seen as
a negotiation between the individual and the survey or demographic form (Townsend, 2009). A
demographic survey captures an individual’s race in a particular situation or context.
Identity Denial and Identity Assertion
The experiences of identity denial and identity assertion are particularly relevant to an
exploration of the enumeration of students by racial identity because they underscore the
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importance of personal context. Identity denial is the experience of being denied membership in
a group with which one identifies (Albuja et al., 2019; Harris & Sim, 2002; Talbot, 2008;
Townsend, 2009). This is particularly resonant for multiracial, multiethnic, and multicultural
students because of their multiple and intersectional identities. Identity assertion is the
experience of an individual seeking to prove or assert their membership in a particular group
(Cheryan & Monin, 2005). Studies on these experiences provide insight and evidence of the
backdrop for an individual’s decision approach to determining self-identity and self-
identification.
Identity Denial
Studies on identity denial can be placed into two categories: those in which a
participant’s identity was actively denied (Albuja et al., 2019) and those in which a participant
was provided inadequate options to self-identify (Townsend, 2009). In a key study, Albuja et al.
(2019) examined this experience in bicultural students, whose American identity was questioned,
and biracial students whose Whiteness was questioned, and found that these students reported
more stress and were more likely to act in a manner that reasserted their identities.
Identity denial can be exhibited in and caused by surveys and forms. When a survey does
not provide the options for multiple race selections a person may experience identity denial
(Townsend, 2009). Root (2003) created a list of 50 comments and questions drawn from a
questionnaire on the experiences of multiracial people that includes a reference to self-
identification in surveys: “You have difficulty filling out forms asking for a single race” (p. 134).
While the question presumes a problem, it confirms the experience of survey taking as a distinct
experience for people who are multiracial. Being forced to choose one race on a demographic
form can be a wrenching experience for multiracial individuals and can elicit negative emotions;
20

being relegated and labeled “Other” elicited a similar response (Johnson et al., 1997). Townsend
(2009) found that the failure to provide adequate options for full expression of self-identity in
surveys can lead to a form of identity denial that lowered test performance, self-esteem, and
motivation.
Multiracial Microaggressions
Studies on multiracial experiences have resulted in the identification of the phenomenon
known as multiracial microaggressions (Harris, 2017; Johnston-Guerrero et al., 2020). Racial
microaggression has been studied extensively since the 1970s and is defined as the everyday
subtle, race-based assaults that people of color confront. Multiracial microaggressions are a
specific form of this assault in which people who are multiracial endure unique microaggressions
related to their multiraciality. Root (2003) identified 50 experiences common to multiracial
people. Building on this work, Johnston and Nadal (2010) created a taxonomy of multiracial
microaggressions. This taxonomy includes five major categories of experience (Nadal et al.,
2011): exclusion or isolation, exoticization and objectification, assumption of monoracial or
mistaken identity, denial of multiracial reality, and pathologizing of identity and experiences.
These categories represent experiences that research has found to be commonly experienced by
people who are multiracial. This taxonomy has provided a system of categorization of
microaggression. Inherent in this scheme is the idea that while people of color experience
microaggressions, there are experiences that are unique to people who are multiracial.
In the taxonomy of multiracial microaggressions, identity denial is a form of
microaggression and has been written about as such in the work of Harris (2017) and Townsend
(2009). These microaggressions may be perpetuated by structures and by what they label as
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monoracial communities of color (Harris, 2017). Thus, multiracial and multiethnic individuals
may experience identity denial.
Identity Assertion
Identity assertion is defined as a process in which a person proves to others that they
belong to a particular group (Cheryan & Monin, 2005). After experiencing identity denial, an
individual may respond with an assertion of their identity. Cheryan and Monin (2005) examined
this process in studies of Asian American students and found that those who were asked by a
White experimenter, “Do you speak English?” spent more time engaged in an activity that
confirmed their American identity. The work of Cheryan and Monin (2005) supports the idea
that identity denial can elicit a reassertion of the threatened identity. Similarly, Harris et al.
(2015) found that the act of completing a survey or demographic form that questions race can
elicit responses that are a reaction to what the form does not offer (Harris et al., 2015).
Racial Identification and the History of Race Categories
From 1930 to 2000, the U.S. census and other federal surveys on race did not provide an
opportunity for multiracial individuals to report their full identity (Jones & Smith, 2001). The
census and other surveys allowed respondents to select one race only, thus, forcing multiracial
individuals to make an impossible choice. They could choose to report one identity and ignore
the other part of their identity, they could select “other,” or they could not respond to the
question at all. Thus, this monoracial approach to race data collection did not reflect the
complexities of race or the history of race in the United States.
Hypodescent: Categorizing and Counting People of African Origin
Throughout much of the history of the United States, counting people of African origin
was not complex or nuanced because the presence of any African ancestry guaranteed that
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society would view that person as Black, Negro, Colored, Afro-American, or African American
(Hickman, 1997; Jordan & Spickard, 2014). This practice of hypodescent was informally known
as “the one drop rule” (Hickman, 1997). Under this rule, even people who physically appeared
White enough to live their lives as White people were counted in the U.S. census as Colored,
Negro, or Black (Hickman, 1997). During the era of slavery in the United States, “the one drop
rule” meant that the children, grandchildren, and great-grandchildren of White slave owners and
an enslaved woman were treated as Black and enslaved (Hickman, 1997). Under this rule, a
Black person could only give birth to a child who would be viewed as Black, regardless of the
race of the other parent. This practice ensured that the slave-owning class would continue its
ownership of Black “property” (Hickman, 1997; Jordan & Spickard, 2014).
An Increase in Diversity
In the decades of the ’80s and ’90s, the United States experienced an increase in
multiracial births and marriages and racial diversity that set the stage for changes in race
categories and methodology. An analysis conducted by the Pew Research Center found that 14%
or one-in-seven infants born in the United States in 2015 were multiracial or multiethnic
(Livingston, 2017). That number was about three times the share in 1980 (Livingston, 2017).
In Black America, the increase in multiracial and multiethnic marriages was even greater
for the period between 1980 and 2015. Of all the multiracial and multiethnic marriages, the
greatest rise was among Black newlyweds, according to an analysis by the Pew Research Center
(Livingston & Brown, 2017). The percentage rose from 5% in 1980 to 18% in 2015. Black men
drove this trend at a rate double that of Black women (Livingston & Brown, 2017). About 24%
or nearly one fourth of newlywed Black men had married a spouse of a different race or
ethnicity. The Pew Research Center analysis found that during the same period, about 12% of
23

newlywed Black women had married a spouse who was of another race or ethnicity (Livingston
& Brown, 2017). And the trend increased for Black men with bachelor’s degrees, who married
interracially or inter-ethnically at a rate of 30% versus 13% for Black women with bachelor’s
degrees (Livingston & Brown, 2017).
A Historic Expansion of Race and Ethnicity Categories
Against this backdrop of demographic change, the collection and reporting of race
changed in the United States following a 2007 policy change. (See Appendix A for a timeline of
historical changes to race categories in education.) The Standards for the Classification of
Federal Data on Race and Ethnicity (Statistical Policy Directive No. 15) issued by the OMB
played a key role in standardizing categories for collecting data on race and ethnicity (Office of
Management and Budget, 1997). OMB determined that anyone of any race who possessed some
Hispanic origin would be counted as solely Hispanic (Aliyeva et al., 2018; Lee & Orfield, 2006).
As part of this change, OMB now treated the Hispanic category not as a race, but as an ethnicity
or ethnic origin (Table 1). It added a question that preceded the question of race: Are you
Hispanic? (Office of Management and Budget, 1997). The second policy change allowed
multiracial individuals to select more than one race on the survey. Data from this question was
reported in a new category “two or more races.”
The 1997 policy change recognized the need for individuals who are multiracial or
multiethnic to express their full self-identity in race surveys and demographic forms. The policy
expanded options for racial and ethnic identification, from five racial categories for data
collection to 64 possible combinations of race and ethnicity codes (National Center for
Education Statistics, 2018). Before the policy change, a Black and White multiracial person had
to choose one race over the other when completing a survey because the taxonomy allowed for
24

only one response. With the policy change, that same person could select both Black and White.
The expanded identification options under the new policy extended beyond a biracial identity.
People who identified with three or four races could also include them on the surveys. Just as the
2000 U.S. Census offered more options for identity since the first decennial census in 1790
(Jones & Smith, 2001), demographic forms and surveys based on the new policy offered
individuals more ways to identify themselves in official documents than ever before.

Table 1
2007 Final Guidance on Reporting Aggregate Racial and Ethnic Categories
Scenario Ethnicity Race(s) Federal reporting
category
1 For Hispanic and any one
race, report as “Hispanic.”

Hispanic/Latino Asian Hispanic/Latino of
any race
2 For Hispanic and any
combination of races, report
as “Hispanic.”

Hispanic/Latino Asian
Black or African
American
Hispanic/Latino of
any race
3 For Non-Hispanic and any
one race, list that race.
Not
Hispanic/Latino
Native Hawaiian
or Other Pacific
Islander
Native Hawaiian or
Other Pacific
Islander

4 For Non-Hispanic and any
combination of races, report
as “two or more races.”
Not
Hispanic/Latino
American Indian
or Alaska Native
White
Two or more races

Note. Adapted from Managing an Identity Crisis: Forum Guide to Implementing New Federal
Race and Ethnicity Categories (NFES 2008-802) (p. 39), by National Forum on Education
Statistics, Race/Ethnicity Data Implementation Task Force, 2008. In the public domain.

25

OMB officials wrote that respect for individual dignity should guide the methods used to
collect data on race and ethnicity. Self-identification was identified as the preferred means of
gathering information about race and ethnicity except in rare instances (Office of Management
and Budget, 1997). The OMB further advised: “do not tell an individual who he or she is, or
specify how an individual should classify himself or herself” (Office of Management and
Budget, 1997, D. OMB’s Decisions). The emphasis on self-identification and the wishes of the
respondents suggest that the individual’s self-identification should take precedence both in race
collecting after 1997 and in bridging methods. This emphasis is repeated in the final guidance
issued for the implementation of the revised policy (U.S. Department of Education, 2007).
Although not explicitly stated, the policy change expanded options on surveys and demographic
forms, and expanded options could lessen the likelihood of identity denial experiences.
While the new policy expanded options for collecting race and ethnicity data, for
reporting purposes the policy called for aggregating the data into seven categories, a practice that
raised concerns from commentators in public feedback (U.S. Department of Education, 2007).
The designers of the new policy were aware of worries expressed by some that the aggregation
of data into the “two or more races category” might result in a decline in the numbers of some
racial groups, specifically the Black racial group and the White racial group. In a written
response, the U.S. Department of Education said it anticipated that any changes would not cause
a significant shift in student demographics because the changes would not be large enough.
Further, the Department of Education in its written response to this criticism said that the policy
changes would lead to greater accuracy. And in response to concerns about the complexity of
tracking data over time, the department referenced its bridging methods as a means of reporting
data trends over time (U.S. Department of Education, 2007). Ultimately, the Department of
26

Education determined that the value of the policy outweighed any problems that might arise from
aggregating data for reporting.
Bridging Methods
Although the policy change provided an important benefit to the individual in the form of
expanded ways to identify themselves, the policy change left colleges and universities unable to
compare pre-2009 and post-2009 data sets without a bridging methodology (U.S. Department of
Education, 2007). Bridging is the process of making race data collected using pre-2009 standards
comparable to data collected using post-2009 standards (Office of Management and Budget,
2001). Bridging acts as an interpreter, allowing for understanding between data sets that speak
different languages. Colleges and universities track and compare race related data over years to
determine progress in outcomes such as admissions, retention, and graduation. Bridging was
necessary to continue that tracking. In the final guidance for the policy, the Department of
Education noted that educational institutions “may propose to ‘bridge’ the ‘two or more races’
category into single-race categories or the new single-race categories into the previous single-
race categories” (U.S. Department of Education, 2007). A report produced by the National
Forum on Education Statistics offered 13 data bridging methods. The new policy presented
bridging as a solution and offered guidance (Office of Management and Budget, 2001).
The new policy reflected an awareness of the challenges that come with using bridging to
track data. Bridging methodologies can make the process of race data reporting more complex
and more burdensome (National Center for Education Statistics, 2018; U.S. Department of
Education, 2007). The new policy did not mandate bridging, instead it left institutions to
determine if they would adopt a bridging methodology, and which type. However, the final
guidance for the policy requires that the same bridging technique be used throughout a college or
27

university. Thus, inherent in the implementation of the new policy was the understanding of the
need for a tool to allow data from previous reporting methods to be relevant to post-2007 data
and latitude in the use of such a tool.
Types of Bridging Methods
A major distinction between bridging methods is whether multiracial students are
counted as a whole person (whole assignment) or in parts (fractional assignment) (Office of
Management and Budget, 2001). In whole assignment methods, a multiracial person is assigned
to a particular racial category or categories as a full person. In these options, the population totals
and percentages may exceed 100% because people are counted in each category they select
(Office of Management and Budget, 2001). Alternatively, in fractional assignment, a multiracial
person can be assigned in fractions to more than one racial group. For example, a person who
selects American Indian and selects Black on a survey would be assigned 50% to the American
Indian race category and 50% to the Black category.
Some bridging methodologies require two data sets: a population for which single race
subcategories are known, and a second set derived from surveys that provided respondents the
opportunity to select more than one race (Office of Management and Budget, 2001). Data
collected in the National Health Interview Survey (NHIS) was used because the surveys had, for
decades, provided respondents with the opportunity to select more than one race (Centers for
Disease Control, 2020; Mays et al., 2003; Office of Management and Budget, 2001). The NHIS
offers a nationally representative data set with a large enough number of individuals who
identified with specific combinations of racial groups. Because NHIS is considered the best
source for extrapolating how a respondent who had selected multiple race groups would respond
if a single race was offered, it has figured prominently in some bridging methodologies.
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The U.S. Office of Management and Budget defined and outlined several different
bridging approaches (Office of Management and Budget, 2001). These approaches demonstrate
the varied ways researchers may approach the task of bridging data. These methods also
demonstrate how one population can yield very different counts because of choices made by
researchers. The following are examples of bridging methodologies presented by the Office of
Management and Budget (2001).
Deterministic Whole Assignment. The OMB defines these methods as using fixed
determined rules to determine the one race category a multiracial person will be assigned to
(Office of Management and Budget, 2001). In the Smallest Group rule, biracial individuals who
select White and one other race are assigned to that other race. Individuals who select three or
more races are assigned to the racial group with the fewest number of individuals who selected
that race alone and not in combination with other races. Using the Largest Group Other Than
White rule, individuals who select White and another race are assigned to the other race,
however, those who select two or more racial groups not including White, are assigned to the
racial group that has the highest number of individuals who selected that group alone and not in
combination with other racial groups. The Largest Group rule assigns multiracial people to the
race group with the largest number of individuals who selected that race only, not in combination
with others. Any individual who selects White and another race is assigned to the White group.
Multiracial individuals who select races other than White are assigned to the one race with the
highest number of individuals who selected that race alone and not in combination with others.
The plurality method uses data from the NHIS to determine assignments of multiracial
individuals into single race categories. The NHIS has conducted surveys since 1957 (Centers for
Disease Control, 2020) and allowed multiracial individuals to select more than one race 15 years
29

before the U.S. census offered multiracial identification (Office of Management Budget, 2001).
The survey captures the first two races selected. Respondents who identify themselves as
belonging to more than one race are then asked to indicate the race that they identify with most.
The CDC then determined the proportion of individuals who identified most with each race in
that race combination. Under the plurality method, multiracial individuals are assigned to the one
race group that received the highest number of individuals indicating it as their main race.
Deterministic Fractional Assignment. The OMB defines deterministic fractional
assignment as methods that assign a fraction to the individual race categories that a multiracial
person identifies (Office of Management and Budget, 2001). The fractions must add up to one. In
deterministic equal fractions, individuals who select more than one race are assigned in equal
fractions based on the number of racial groups they selected. An individual who selected two
groups would be assigned half to each group, while a person who selected three racial groups
would be assigned one third to each group and a person who selected four groups would be
assigned one fourth to each group. The Deterministic NHIS Fractions method assigns multiracial
individuals to racial groups in categories based on the responses and proportions determined by
the NHIS. Thus, an individual who selects Black and Asian, is assigned in fractions to each
group based on NHIS responses.
Probabilistic Whole Assignment. Probabilistic methods use probabilistic rules to assign
a multiracial person to just one of the 1997 racial categories (Office of Management and Budget,
2001). The term probabilistic refers to the fractions used to select one race category. In these
methods multiracial responses may be randomly assigned to one category or another or others.
An American Indian and White response might be assigned to either the American Indian
category or the White category. OMB referenced two possibilities. In one option, multiracial
30

responses are assigned to one racial category based on equal fractions. In the other, multiracial
responses are assigned to categories using NHIS fractions drawn from survey responses.
All-Inclusive Whole Assignment. In an all-inclusive approach, individuals are included,
in whole, in every racial group they selected (Office of Management and Budget, 2001). The
percentage of each racial group reflects the percent of the total population who selected that
group. Because people may be counted in two or more racial groups, the sum of the percentages
will exceed 100%.
Choosing Bridging Methods
The OMB evaluated bridging methods based on a series of criteria, including the
method’s effectiveness in measuring change over time, what researchers called “of greatest
importance” (Office of Management and Budget, 2001). They define the ideal bridging method
as one that recreates the population distribution before the new policy, meaning the only
difference is a function of change over time, “but also assigns an individual’s response to the old
category that would have been chosen” (Office of Management and Budget, 2001). In examining
the counts produced by the methods, OMB analysis found that the largest group, deterministic
whole assignment method, the plurality method, and the deterministic fractional assignment
methods yielded counts that were closer to the reference distributions than the other deterministic
whole assignment methods and the all-inclusive method.
Similarly, Allen and Turner (2001) identified four major options for bridging race data
and found fractional assignment to be the method most likely to produce accurate results. Their
research examined race data from the first U.S. census in which multiple race selections were
permitted and compared the findings to previous years when only one race category was
allowed. In the first option, only those individuals who selected one race would be counted in
31

that racial category. In the second option, individuals would be counted in each of the race
categories they selected, even if they selected more than one race. In the third option, individuals
who select more than one category would be assigned to only one category, based on some
determination or probability. The last major option, fractional assignment, or apportioning,
places individuals who selected more than one race into single race categories in fractions.
While some research points to a form of fractional tabulation as an often accurate bridge
for racial data, OMB researchers suggested that several factors should be considered when
determining methods for tabulation (Office of Management and Budget, 2001). The ease with
which the method can be used, its applicability in various contexts, and its statistical soundness
or defensibility are cited. These factors are nearly all directed to researchers or personnel who are
tabulating the collected data, rather than to survey respondents. But two criteria are directed to
the respondents: the ease of explaining the method to the public and the congruence of the
methods with the wishes of respondents. OMB’s inclusion of bridging methods and its
concurrent guidance in selection, underscored the challenges of race enumeration, not only for
those counting but for those who are counted.
The Same Population, Different Numbers
The idea of a singularly accurate means of counting and reporting race data has been
called into question by scholars who have used different methodologies to count the same
population—and produced different counts. Gullickson and Morning (2011) used a definition of
multiracial that includes individuals whose mix occurred in a genealogically distant past. Based
on this definition they found that multiracial Americans would grow from more than 2% to 40%
of the total population. Lee and Orfield (2006) tallied students in a national database twice: once
using pre-1997 methodology and again using the federal race methodology. The researchers
32

found that the numbers of Black identified and White identified fourth and eighth grade students
dropped and reading scores dropped in some states, even though the overall population of
students enumerated was the same (Lee & Orfield, 2006). Dowling (2014) noted that the
numbers of Latinos reporting their racial identification as White or “some other race” declined
significantly when the U.S. Census Bureau treated the Hispanic category as a race rather than an
ethnicity or origin. Best (2004) analyzed a controversy over the size of the Jewish populations in
the United States that was rooted in a determination of how Jewishness was defined. These
studies illustrate that tabulation rules that make up a bridging method can affect the counts of a
population (Mays et al. 2003), as can definitions.
The researchers’ analyses produced different racial counts for the same population of
individuals. The difference in population counts found by researchers examining the same
population speaks to the role of data methodology in determining outcomes. Given this fact,
Harris and Sim (2002) argued that the 2000 census and other demographic surveys calculate a
multiracial population, rather than the multiracial population.
Research provides contrasting views of how Black multiracial respondents would identify
themselves on a forced choice survey in which they must choose one race. The research of
Campbell (2007) cautions against assuming that respondents who identify as Black and
multiracial on a survey that allowed respondents to choose one race would identify as Black on a
forced choice survey. Campbell (2007) found significant variations within Black multiracial
groups and identified factors influencing identity choice, such as being born before or after 1965
and being married to someone who is not Black. Those born after 1965 and those who were
married to someone who is not Black were more likely not to identify as Black on a forced
choice survey. By contrast, of those who identified as Black and American Indian on a survey,
33

95% identified as Black on a forced choice survey. Allen and Turner (2001) found that among
those who identified as Black and White, a Black primary identity was more common than a
White primary identity. A methodology that does not acknowledge the importance of Black
identity for this group is not, Allen and Turner (2001) wrote, a fair measure of the size of the
nation’s Black population.
The Importance of Data Methodology
Race data continues to serve as a tool to monitor socioeconomic changes in
subpopulations over a span of time, which makes race data collection and reporting methods
relevant to a wide array of discussions. In areas such as voting, employment, housing, education,
legislative redistricting, and for program administration reporting (Johnson et al., 1997), data
comparisons are critical to tracking and understanding change. In higher education, race and
ethnicity are used to track enrollment, graduation, transfer, and drop-out rates for students, and to
create a demographic profile of faculty and staff. In healthcare, race and ethnicity data are used
in a variety of ways: to describe vital statistics, as a risk indicator for health outcomes, to
improve the delivery of health services, as a marker of unmeasured biological differences, and as
a proxy for other social factors (Mays et al., 2003). In the National Football League, race data
was used to determine the amount of pay that would be given to players who suffered dementia
as a result of playing (Belson, 2021). The practice, known as race norming, provided less payout
to Black players because it assumed that Black players started with lower cognitive skills than
White players. Former players and their families brought the practice to light and forced the NFL
to abandon the practice and agree to reassess Black players. Although race is generally accepted
as a social construct (American Psychological Association, 2019; Bang, 2015; Gillborn et al.,
2017), its consequences and implications in American society are real (Wilkerson, 2020).
34

Because of the continuing role of race as a measurement tool, studying race data and
methodology is important to the goals of identifying, understanding, and correcting societal
inequities.
In higher education, race and ethnicity data is used to track student demographics, student
outcomes, and to offer support services that meet student needs. Well-documented differences
between the performances of subpopulations of students have persisted. Data confirms that some
students of color in general, and Black students in particular, drop out of colleges and
universities at a higher rate than White students (Campaign for College Opportunity, 2021).
There is evidence to support the idea that colleges and universities can contribute to the
development of identity and thus retention. Harper and Hurtado (2007) found that involvement in
student organizations helped enhance Black students’ identity. They suggest that these
organizations should be supported and encouraged because they provide opportunities for
students to explore their identities and develop responses to social issues (Harper & Hurtado,
2007). Willis et al. (2019) demonstrated the feelings of isolation that some students may
experience on campus when the Black student population is small. Race data is used to track
campus diversity of the student population as well as faculty and staff (National Center for
Education Statistics, n.d.). Such data is reported on the websites of colleges and universities and
on the website of the U.S. Department of Education (College Navigator, n.d.)
Some scholars have challenged the federal race methodology because of its detrimental
impact on subpopulations of students. The National Commission on Asian American and Pacific
Islander Research in Education called the demand for disaggregated data a civil rights issue
(Teranishi et al., 2013). The needs of subpopulations of AAPI students can be masked in
aggregated data by the overall success of the larger group. The researchers noted that
35

disaggregated data informed research efforts and has been used to support retention efforts
through addressing the well-being of AAPI students on campus. The Campaign for College
Opportunity recommended that the state of California create an education data system to identify
trends facing Black students and solutions to improve outcomes (Bates et al., 2019). Without
such data, the state cannot understand barriers or successful practices, the researchers argued.
Eroding or Building Public Trust Through Data Practices and Methodology
Black America’s relationship with the research community has been shaped and deeply
damaged by a long history of cases of unethical and undisclosed methods and procedures (White
House, Office of the Press Secretary, 1997). The most infamous remains the Tuskegee Syphilis
Study, known commonly as the Tuskegee Experiment. In this case, hundreds of Black men in
Macon County, Alabama were told they were receiving medical treatment for “bad blood”
(Jones, 1993). Instead for 40 years, government-paid doctors withheld treatment from men with
syphilis so doctors could learn more about the disease. The doctors merely observed the
development of the disease, while the men became sick and died, or went blind or insane. For all
the outrage the Tuskegee Syphilis Study evoked, Black America’s exploitation at the hands of
some in the medical research community began long before the study and continued long after
(Washington, 2006). Enslaved Black people were subjected to grotesque experiments that led to
their deaths and maiming and to the creation of gynecological instruments; unwitting patients
were injected with toxic levels of plutonium; untold numbers of women, including civil rights
icon Fannie Lou Hamer, went to doctors for various ailments and only later learned that they had
been sterilized without their consent and knowledge and against their wishes (Washington,
2006). In 2010, the nation learned of the story of Henrietta Lacks, whose HeLa cells had been
36

used in research around the world since her death in 1951 but were donated by Johns Hopkins
without her knowledge or consent or that of her family (Johns Hopkins Medicine, n.d.).
Ethical failures in medical and scientific experiments have been acknowledged in official
apologies from the federal government, universities, and hospitals. A historic apology issued in
1997 by then President Bill Clinton acknowledged that the U.S. government “did something that
was wrong—deeply, profoundly, morally wrong” during the Tuskegee study (White House,
Office of the Press Secretary, 1997). Johns Hopkins University, which had treated Lacks,
acknowledged its failings and noted that what happened in 1951 would “never happen today”
(Johns Hopkins Medicine, n.d.). In April of 2021, the University of Pennsylvania and Penn
Museum apologized for its continued possession of the skulls of enslaved people used in the
research of Samuel Morton (Pritchett & Woods, 2021). A university report described Morton as
a Philadelphia-based physician and anatomy lecturer whose research was used to support white
supremacy, naturalize settler colonialism, and justify slavery (Mitchell, 2021). The Morton
Collection Committee, convened by the museum, found that the museum should acknowledge
that the crania were unethically acquired and apologize for the acquisition and continued
possession (Morton Collection Committee, 2021). The committee further found that the museum
should return the remains “to their descendants and communities of origin whenever possible as
a step towards atoning for the racist, unethical, and colonial practices which were integral to the
formation of these collections” (Morton Collection Committee, 2021, Executive Summary). In
2021, officials at the University of Pennsylvania and Princeton University acknowledged that the
universities kept and used the bones of a young victim who was killed in the infamous police
bombing of a Black neighborhood in Philadelphia (Levenson, 2021). In that incident in 1985, 11
people were killed and more than 60 homes were destroyed (Levenson, 2021). Of those who
37

died, five were children. In apologizing, a University of Pennsylvania statement said the original
reason for possessing the bones was to identify the victim, but they had been unable to do so
(Pritchett & Woods, 2021). Cases such as these and the publicity around them highlight the
breadth of ethical failures or mistakes in research in the Black community.
In the 21st century, fear and distrust linger and continue to inform Black America’s
relationship with scientific research, including vaccines for COVID-19. A study by the Pew
Research Center found that among Black Americans, 71% know someone who has been
hospitalized or died because of COVID-19 (Funk & Tyson, 2020). Black people were also less
inclined to be vaccinated than other races; 42% would do so, compared with 63% of Hispanic
and 61% of White adults and 83% of English-speaking Asian Americans (Funk & Tyson, 2020).
Notably, this study only reports responses for those who indicated a single race on the survey.
The responses of those who checked more than one race, and the races of those who indicate
their ethnicity as Hispanic, were not reported in the Pew Research Center findings.
QuantCrit Theory
As a branch of Critical Race Theory, QuantCrit centers race and examines its
implications for the systems and structures that undergird U.S. society (McCoy & Rodricks,
2015). QuantCrit aims its lens specifically at quantitative data with five tenets: (a) racism as
complex, deeply embedded, and not easily quantified; (b) categories are not natural or given and
units of analysis must be evaluated; (c) numbers are not neutral, and must be interrogated; (d)
data cannot speak for itself; the experiential knowledge of groups and people is critical; and (e)
statistical analyses have a role to play in the push for social justice (Garcia et al., 2017). Through
these five tenets, QuantCrit argues that quantitative data should not be treated as organic entities
38

(Gillborn et al., 2017). Instead, quantitative data should be handled as constructs with histories
and backstories that merit scrutiny.
Quantitative race data, as a byproduct of race, is a fitting subject for analysis through
QuantCrit. The tenets of QuantCrit have been applied to studies explored in this chapter.
Although the researchers do not situate their work in the realm of QuantCrit, they implement the
approach to race data that QuantCrit proposes through tenets b, c, and d. This approach can be
seen in studies that deconstruct data and/or propose alternative means of measuring race, such as
Gullickson and Morning (2011), Lee and Orfield (2006), and Mays et al. (2003).
Categories Are Not Natural and Interrogating the Numbers
Quantitative data possesses a veneer of neutrality, objectivity, and legitimacy that has
faced increased scrutiny by researchers (Garcia et. al., 2017; Gillborn et al., 2017). The idea that
numbers are neutral belies the many decisions that quantitative researchers must make to arrive
at a given data set (Gillborn et al., 2017; Teranishi, 2007). Gillborn et al. (2017) argued that
statistics are socially constructed and quantitative research is designed in much the same manner
as qualitative interviews. The notion that quantitative data is more rigorous and trustworthy is a
false perception that feeds adages such as “numbers don’t lie” (Anderson, 2008) and the numbers
speak for themselves (Gillborn et al., 2017). Best (2004) cautioned that statistics are social
products that reflect the process by which they are created. In the era of Big Data, this notion
persists and the reliance on data use for accountability and assessment has grown.
A Counter Narrative
Although QuantCrit is focused on quantitative data, it values the stories, experiential
knowledge, and experiences of people (McCoy & Rodricks, 2015). Solórzano and Yosso (2002)
define storytelling as useful in education research because it gives voices to marginalized
39

students, while also examining and countering majoritarian stories, also known as master
narratives. Although voice and stories would suggest qualitative research, voice can also be
heard in quantitative analysis. The respondents in the research of Dowling (2014) who identified
themselves as “some other race,” provided a numerical story. The numbers of students who
reject a racial binary, exhibited by their refusal to identify their race on surveys, could also be
viewed as a counter narrative (McCoy & Rodricks, 2015). The experiences, views, and concerns
of Black students in higher education regarding the low numbers of their peers on university
campuses and the implications for their experience adds depth to the numbers, speaking what
numbers alone do not express (Contreras et al., 2015).
Summary
The literature review provided context and a foundation for the current research. With
QuantCrit as the theoretical frame, the literature review explored research studies, public policy
decisions, theory, and history related to measuring race. There is evidence of a void in the
literature that confirms the need for additional research. Researchers have examined the elements
that are integral to race enumeration, such as identity development, identity denial (Albuja et al.,
2019; Harris & Sim, 2002; Talbot, 2008; Townsend, 2009) and identity assertion (Cheryan &
Monin, 2005), bridging methods (Office of Budget and Management, 2001), and the manner in
which race data methodology can influence race counts (Gullickson & Morning, 2011; Lee
& Orfield, 2006; Mays et al., 2003). Significant information exists about the implementation of
the federal race methodology that determines enumeration on the campuses of U.S. colleges and
universities (U.S. Department of Education, 2007). What is lacking is an exploration of the ways
these elements converge on a university campus and the change, if any, that occurs as a result of
the federal race methodology. The studies that compared population counts using different
40

methodologies examined non-university-based populations, thus confirming the importance of
conducting research of university-based populations. The literature review confirmed that there
is also an opportunity to build on the research by studying the experiences of Black multiracial
individuals and centering their voices in the discussion of race enumeration at U.S. colleges and
universities.
The theoretical concept for the current study states that the lived experiences of people
who are Black and multiracial influences how individuals self-identify on race surveys, yet a
federal methodology that mandates how race is measured on U.S. campuses (Office of
Management and Budget, 2001) imposes race categories that usurp self-identity. The theoretical
concept for this study is supported and advanced by the literature review. Chapter Three will
explain how the study will be conducted, including the research questions, population,
instrumentation, data collection, and data analysis.

41

Chapter Three: Methodology
This study examined the enumeration of Black identity at a 4-year, public university in
the western United States (Public University) and the implications of a federally mandated data
collecting and reporting methodology. A mixed methods approach provided an opportunity to
explore the personal and the public implications of the federal race data policy. The quantitative
analysis explored and quantified the role of the policy on the known number of Black identified
students in the years since the policy was implemented. The qualitative analysis examined how
Black identified multiracial and multiethnic individuals experience and view race surveys and
their expectations for the reporting of their racial identity.
The research was guided by five research questions:
1. What are the key 10-year demographic trends for the Black student subpopulation
and the Black multiracial/multiethnic subpopulation at Public University?
2. How does the demographic profile (number and proportion) of Black students at
Public University change when an all-inclusive whole assignment bridging
methodology is applied to the student population?
3. What are the most frequent race combinations found at Public University when
the “two races or more category” is disaggregated?
4. How do Black multiracial or multiethnic people who have experienced identity
denial view and interact with race and ethnicity survey questions?
5. How does the reporting of Black identity, as mandated by the federal government,
align with expectations and assumptions for reporting held by Black multiracial or
multiethnic people?
42

Rationale for the Methodology
The qualitative phase of the research utilized four in-depth interviews as a tool for data
collection. The intention of using this approach was to uncover the unique, deeply personal
experiences of university graduates who are multiracial and multiethnic. Such qualitative data is
important to understanding quantitative data on Black and Black multiracial, multiethnic
populations’ demographics. Research studies have explored various aspects of the multiracial
experience, including the fluidity of race and the role of social and cultural dynamics on self-
identity in students (Tracy et al., 2010). The work of Townsend (2009) provides support for the
idea that biracial and multiracial experience lower self-esteem, performance, and motivation
when they are forced to choose a single monoracial identity. A quantitative approach alone
would not provide an opportunity to explore these experiences and ideas.
A key advantage of a qualitative interview analysis was the opportunity to tell a more
complete story than a one case approach can offer. There are numerous Black multiracial and
multiethnic combinations possible on research surveys, such as Black and Native American,
Black and Asian, and Black and Filipino (Table 2). In their studies of mixed heritage
adolescents, Tracy et al. (2010) found that future research should consider the specific race
combinations of subjects. These combinations represent what may be vastly different
experiences. A multiple case study methodology allowed for a greater range of experiences,
representing individuals with different Black multiracial multiethnic heritages.
The quantitative phase of the study utilized a non-experimental correlational design.
Creswell and Creswell (2018) describe this design as one in which researchers use the
correlational statistic to describe or measure the relationship between two variables. In this
phase, I analyzed survey responses and population trends of Black identified students at Public
43

University from 2009 to 2020. The goal was to determine if a statistical relationship exists
between the numbers of students who identified as Black only and the number of students who
identified as Black and another race or ethnicity. A quantitative analysis allowed for a
description of the relationship between these two variables.

Table 2
Race Category Variables
Two or more races category (including Black) and Hispanic ethnicity
Black and American Indian
Black and Asian
Black and Hispanic
Black and Pacific Islander
Black, American Indian and Asian
Black, American Indian and Hispanic
Black, American Indian, Asian and Hispanic
Black, Asian, and Hispanic
Black, Asian, and Pacific Islander
Black, Asian, Pacific Islander and Hispanic
Black, Pacific Islander, and Hispanic
White and Black
White, Black and American Indian
White, Black and Asian
44

Two or more races category (including Black) and Hispanic ethnicity
White, Black and Hispanic
White, Black, American Indian and Asian
White, Black, American Indian and Hispanic
White, Black, American Indian, Asian and Hispanic
White, Black, American Indian, Asian and Pacific Islander
White, Black, American Indian, Asian, Pacific Islander and Hispanic
White, Black, Asian and Hispanic
White, Black, Asian and Pacific Islander

The quantitative analysis also allowed for a discovery of the racial combinations that
existed among students who selected two or more races on race and ethnicity surveys.
Researchers have found that disaggregating data can reveal important differences about
multiracial subgroups (Charmaraman et al., 2014; Tracy & Erkut, 2010; Tracy et al., 2010).
Thus, disaggregating data is an important tool to understand student identity and student needs.
Knowing these combinations informed the selection of interview participants for the qualitative
phase of the research.
Phase 1: Quantitative
Sample and Population
Public University is a racially and ethnically diverse university of more than 20,000
students. The overwhelming majority of its students are underrepresented minorities. The
university is a federally designated Hispanic Serving Institution (HSI), Minority Serving
Institution (MSI), and Asian American and Native American Pacific Islander Serving Institution
45

(AANAPISI). The target population for this study is the subpopulation of students who identify
as Black, who identify as Black and another race or races, or who identify as Black and Hispanic.
The target population is students who attended the university between 2009 and 2020 and
completed a race survey with answers other than “Decline to State” or “None of the Above.”
Instrumentation
In the quantitative phase, I analyzed secondary data, which were records on race and
ethnicity that were generated by students answering the fall survey conducted by Public
University between 2009 and 2020. This survey is a part of the application for admission to the
university and is completed online along with other parts of the admissions application. The
survey is designed to collect data for the Fall Enrollment component of the Integrated
Postsecondary Education Data System (IPEDS). IPEDS is a large-scale survey administered by
the National Center for Education Statistics (NCES) that collects institution-level data from
postsecondary institutions in the United States and U.S. jurisdictions (Aliyeva et al., 2018). The
survey collects data on several variables including race and ethnicity, age, first-generation status,
and Pell Grant recipient status and is a part of the application for admission to the university.
This study is primarily interested in institutional records on race and ethnicity created beginning
in 2009 through 2020. The IPEDS survey requires that universities collect data on race and
ethnicity with options that offer broad latitude in self-identity. Respondents may choose from
several race categories and may select as many races as they feel appropriate. Students may also
decline to answer the question.
The survey collects data on race and ethnicity in a section titled “Race & Ethnicity.”
Instructions advise applicants to select “any and all of the options in this section which you feel
best apply to you.” The instructions also inform students that their responses will have no impact
46

on application or financial aid eligibility and that the section is used for statistical purposes only.
The “Race & Ethnicity” section of the fall survey consists of two subsections: “Ethnicity” and
“Race.”
In the “Ethnicity” subsection applicants are asked: “With regard to your ethnicity, do you
consider yourself Hispanic or Latino?*” The asterisk indicates that this is a required field. To
respond to this question, applicants select options from a pull-down menu that includes “yes” or
“no.” Applicants who select “yes” from the pull-down menu, proceed to another question on
ethnicity. The applicant is next asked to “select one category below that best describes your
background.” The list of categories includes 22 entries spanning the Latin American world,
including Argentinian, Mexican, Puerto Rican, and Cuban. The list also includes umbrella entries
such as “Other Central American,” “Other South American,” and “Other Hispanic or Latino.”
Instructions in the “Race” subsection direct applicants to identify themselves racially
within the parameters of pre-selected categories. Applicants are asked to select from a list of
groups regardless of their answer to the question on ethnicity. The instructions state: “Please
select below one or more of the following groups in which you consider yourself a member.”
Five categories follow: American Indian or Alaska Native, Asian, Black or African American,
Native Hawaiian or other Pacific Islander, and White. At the end of the list of categories are two
additional boxes: Decline to State and None of the Above. The section does not include a write-
in option.
Each of the five categories in the “Race” subsection offers subcategories and students are
instructed to “select one sub-category below that best describes your background.” The
American Indian or Alaska Native category includes 33 options of groups, such as Chumash,
Mojave, Shoshone, or Gabrielino-Tongva. The list of 33 options includes two umbrella groups
47

“Other Alaska Native Tribe” and “Other American Indian Tribe.” Similarly, the Asian category
offers 23 subcategories, such as Bangladeshi, Chinese, Filipino, and Vietnamese. The list of
categories includes one umbrella group “Other Asian.” The Black or African American category
includes four options: African American, Black, Haitian, and Other African/Black. The Native
Hawaiian or other Pacific Islander category includes 24 subcategories, such as Carolinian, Fijan,
Samoan, Tongan, and four umbrella groups “Other Melanesian,” “Other Pacific Islander,” and
“Other Polynesian.” The White category includes the subcategories European, Middle Eastern,
North African, and the umbrella group “Other White.”
The end of the section on race and ethnicity includes two options that are not available in
earlier sections of the survey: (1) Decline to State and (2) None of the Above. These options
reside at the end of the list of White subcategories. There are no markings or physical spacing
that visually delineates the list of White sub-categories from these two options. Following the
two options there is a subsection titled “Summary.” This subsection includes one question:
“[University System] often needs to report ONLY ONE summary race/ethnicity description for a
person. Please select your reporting preferences.” Below this statement there is a pull-down
menu.
QuantCrit, a branch of Critical Race Theory that argues that numbers should be
interrogated, and units of analysis should be questioned, provided the theoretical framework for
the quantitative phase of the study (Garcia et al., 2017). In this framework, the unit of analysis
was the racial categories into which students are placed. The numbers that were interrogated
were the percentages that makeup the racial profile of the student profile reported by Public
University. I examined the demographic profile of Public University’s student population
48

through two race data reporting methods: the data reporting categories mandated by the federal
government and the categories used in an all-inclusive whole assignment bridging methodology.
Data Collection
In the quantitative phase of this study, the records were obtained from Public University
by a letter of request for the documents and through the use of its web dashboard archives.
Through the university’s dashboards, the public is able to access a wide range of unidentifiable
information about student populations over the years. Public University makes many years of
data available on its website. The website allowed for the downloading of files and for
combinations of variables to be explored.
Data Analysis
Question 1
What are the key 10-year demographic trends for the Black student subpopulation and the
Black multiracial/multiethnic subpopulation at Public University?
Question 2
How does the demographic profile (number and proportion) of Black students at Public
University change when an all-inclusive whole assignment bridging methodology is applied to
the student population?
Answering Questions 1 and 2
To answer questions 1 and 2, I used race and ethnicity data drawn from the IPEDS survey
completed by entering students at Public University over several years. For the first question, I
compared two data sets collected over 10 years: the population of students who identified as
Black only and the population of students who identified as Black and another race or ethnicity. I
examined the data to identify and compare the trends of the two student subpopulations. To
49

answer the second question, I examined selected race and ethnicity data from specified years. I
examined the population as defined by the federally mandated category of Black. For those same
years, I analyzed the data of students placed in the “two or more races” category, extracting and
tabulating all respondents who identified themselves as Black in combination with another race
or ethnicity. This type of tabulation, all-inclusive whole assignment bridging, produced a second
data set. I then compared the two data sets to determine how applying an all-inclusive whole
assignment bridging methodology changed the demographic profile with regard to Black
students.
Question 3
What are the most frequent race combinations found at Public University when the “two
or more races” category is disaggregated?
Answering Question 3
The purpose of examining the data of students in the “two or more races” category was to
determine the specific racial combinations that included Black identity present on Public
University’s campus. To answer the third question, I disaggregated the data of students who
selected “two or more races,” including Black, on the survey. This allowed for a compilation and
tabulation of the racial combinations present. I then determined the frequency of Black identity
among students who are categorized as “two or more races.” Disaggregation revealed the most
common Black multiracial subgroups in the student population for the reviewed years.
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Phase 2: Qualitative
Sample Population
In the qualitative phase, this study focused on a small, purposeful sample of multiracial
and multiethnic individuals who would be excluded from the Black category based on the
federally mandated race collecting and reporting methodology. The sample was limited to those
individuals who are Black and multiracial, have graduated from a college or university, and have
in the course of their college years taken a survey that included race and ethnicity questions.
Respondents included those who have earned undergraduate degrees, as well as those who have
completed graduate degrees. I relied on my personal network to identify potential participants. I
reached out to several individuals, some of whom, in turn, reached out to other individuals. From
a pool of eight potential participants, I selected four who represented different racial
combinations.
Instrumentation
Instrumentation for the qualitative phase consisted of semi-structured, one-on-one
interviews with four multiracial, multiethnic university graduates. The interview protocol
consisted of 17 questions designed to collect data that would answer the two qualitative research
questions (Appendix B). These research questions are grounded in two particularly relevant
types of studies found in the literature: identity denial and survey responses. Several researchers,
including Townsend (2009), have identified identity denial as a salient experience in the lives of
people who are multiracial. The work of Townsend (2009) confirmed that being denied the
opportunity to fully identify themselves on surveys can evoke an identity denial experience in
people. Charmaraman et al. (2014) noted, as have other researchers, that racial self-identity can
51

change over time and place. This previous research gave rise to the qualitative questions in this
study.
Data Collection
The interviews were conducted via Zoom, to ensure compliance with public health
protocols in light of the COVID-19 pandemic. The interviews ranged from 1 hour to roughly 1.5
hours. Each interview was audio recorded using the app Otter.ai, and a transcript was produced.
The transcript for each interview was reviewed for accuracy against the audio recording.
Data Analysis
Question 1
How do Black multiracial or multiethnic people who have experienced identity denial
interact with and view race and ethnicity survey questions?
Question 2
How does the reporting of Black identity as mandated by the federal government align
with expectations and assumptions for reporting held by Black multiracial or multiethnic people?
Analyzing Data for Questions 1 and 2
The transcript for each interview was hand-coded for themes. The coding involved
several levels, beginning with open coding and then evolving to themes that encompassed and
reflected the experiences and views of the respondents. These in-depth interviews yielded deep,
rich data. Responses to questions about the experience of being Black and multiracial and about
completing surveys and demographic forms about race and identity were coded and analyzed for
themes. These themes answer the research questions.
Chapter Four will outline the findings of the quantitative and qualitative data analyses.
The quantitative review was designed to address the first three research questions (1-3). The
52

results are presented and illustrated through graphs, charts, and tables. The qualitative thematic
analysis was guided by two research questions (4–5). The themes that emerged are outlined and
narratives excerpted from in-depth interviews are included.

53

Chapter Four: Findings
The purpose of this explanatory sequential mixed-methods study is to understand how
federal race policies shape demographic data at Public University and intersect with the personal
experiences and perspectives of graduates. The quantitative section of this study examined the
role of federally mandated racial definitions and reporting mandates in influencing the known
number of Black identified students at Public University. The qualitative section of the research
seeks to understand how graduates who have experienced identity denial interact with race
survey questions and what expectations they hold of how they will be represented in the data.
The research was guided by five research questions:
1. What are the key 10-year demographic trends for the Black student subpopulation
and the Black multiracial/multiethnic subpopulation at Public University?
2. How does the demographic profile (number and proportion) of Black students at
Public University change when an all-inclusive whole assignment bridging
methodology is applied to the student population?
3. What are the most frequent race combinations found at Public University among
Black multiracial students when the “two races or more category” is
disaggregated?
4. How do Black multiracial or multiethnic people who have experienced identity
interact with race and ethnicity survey questions?
5. How does the reporting of Black identity as mandated by the federal government
align with expectations and assumptions for reporting held by Black multiracial
people?
54

While limited in its longitudinal scope, this data analysis revealed significant trends and
relationships between subpopulations of students over more than a decade. This chapter will
begin with a discussion of the results and themes of the quantitative study, followed by a
discussion of the findings and themes of the qualitative section.
Participants (Quantitative)
Quantitative data was collected from survey responses of students at Public University
from 2005 through 2020. The participants answered questions about race and ethnicity as part of
an application to the university. The participants were U.S. citizens or residents. The responses
of international students and students who were not documented were not included in the
reviewed and analyzed records.
Results Research Question 1
A trend examination of Public University’s data on race and ethnicity from 2009 to 2020
found different demographic trends for the subpopulation of Black students and the
subpopulation of multiracial/multiethnic students who identify as Black (Figure 1). Between
2009 and 2020, the percentage of Black students declined every year, with the exception of 2019
when there was a .2% increase over the previous year. Conversely, the percentage of students
who identify as Black and multiracial or multiethnic has remained on an upward trajectory. From
0.4% in 2009, the proportion climbed to a high of 1.8% in 2015 and 2016. Although the
proportion of Black only students was higher at 4.4% in 2015 and 4.2% in 2016, the trend is
downward. From 2018 and 2019 to 2020 the proportion of Black identified multiracial or
multiethnic students plateaued at 1.6% of the population.
55

Figure 1
Black and Black/Multiracial Identification at Public University

Note. The percentages include all students: undergraduate (first-time freshmen and transfer
students) and graduate students.

Discussion Research Question 1
The data analysis found that the number of students who identify as Black alone
decreased steadily between 2009 and 2020. In 2009, 7.1% of the student population (1,456
students) identified as Black alone. This proportion included undergraduate, graduate, and
transfer students. By 2019, that number had fallen to a low of 3.5% or 921 students. In 2020, the
population of students who identified as Black only was 3.7% or 968 students.
56

A review of records from Public University found that over the years, a growing
proportion of the student population has identified as Black and multiracial or multiethnic. In the
fall survey, these students selected Black and at least one other race in defining their identity.
This subpopulation of students also includes those who identified as Hispanic and then listed
their race as Black or Black and another race. In 2009, the first year that the multiracial and
multiethnic options appeared on the survey, 0.4% of students or 83 students identified as Black
and another race or ethnicity. By 2020, that number had grown to 1.6% or 413 students. The
percentage increase in students who identified as Black and multiracial or multiethnic grew by
nearly 400% (397.59%) between 2009 and 2020.
Results Research Question 2
The use of the all-inclusive whole assignment methodology resulted in a population that
ranged from 6% to as much as 45% greater than the size of the Black alone population (Table 3).
The greatest percentage increase (45%) took place in 2019. Under this bridging methodology,
students are assigned to each of the racial categories they selected on the race survey. Thus, all
students who identified themselves as Black were counted as Black. They would also be
included in the other race categories they selected. Using this methodology, the number of Black
identified students increased every year from 2009 to 2020. For each of the last 5 years, the use
of the all-inclusive methodology led to a population that was at least 40% greater in size than the
percentage of students at Public University who identified as Black alone.

57

Table 3
A Black Identified Population at Public University
Year Black Black/Multi Total Black and Black/Multi % increase
2005 7.5% 7.5%
2006 8.2% 8.2%
2007 8% 8%
2008 7.9% 7.9%
2009 7.1 % 0.4% 7.5% 6%
2010 6.2% 0.8% 7.0% 12%
2011 5.7% 1.1% 6.8% 20%
2012 5.2% 1.4% 6.6% 27%
2013 4.9% 1.5% 6.4% 31%
2014 4.4% 1.6% 6.0% Data
missing
2015 4.4% 1.8% 6.2% 24%
2016 4.2% 1.8% 6.0% 42%
2017 4.0% 1.7% 5.7% 44%
2018 3.7% 1.6% 5.3% 42%
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Year Black Black/Multi Total Black and Black/Multi % increase
2019 3.5% 1.6% 5.1% 45%
2020 3.7% 1.6% 5.2% 43%

Note. The all-inclusive whole assignment methodology was used to create the Total Black and
Black/Multi percentages.

Discussion Research Question 2
The use of the all-inclusive whole assignment methodology resulted in the creation of a
reporting category that does not exist in the federal methodology. The data that resulted from the
use of this methodology created a category that includes students who identified themselves as
Black and no other race, and those students who identified themselves as Black and one or more
other races. For the purposes of this discussion, the term Black identified is used in reference to
these students.
In 2019, 3.5% of the population of undergraduate and graduate students identified as
Black alone, while 1.6% identified as Black and another race or races. When the all-inclusive
whole assignment methodology was applied, the total population of Black identified students
was 5.1%—a 45% increase over the number of students who identified as Black alone.
Because the new federal methodology went into effect in 2009, this analysis examined
the population data from this calendar year in depth. This transition year included data collected
using the previous definitions of race and ethnicity, as well as data collected under the then new
directive. Results from the first two surveys of the year are consistent with those of the previous
59

years. The winter survey found that 8% of the population was Black. The population according
to the spring survey was 7.9%. In the summer of 2009, the federal race methodology was
implemented. According to the summer 2009 survey, the population of Black students was 7.1%.
Similarly, in the fall, the population of Black students was 7.1%. However, when the all-
inclusive whole assignment methodology was applied, the percentage of Black identified
students was 7.5%.
Results Research Question 3
To answer this question, I analyzed disaggregated data from the “two or more races
category” where at least one race was Black. My comparative analysis found that the numbers of
students who selected two races (including Black) increased significantly from 2009 to 2020 for
every racial combination possible using the federal methodology (Figure 2). My analysis found
that the most frequent race combination among Black multiracial students at Public University in
2009, 2016, and 2019 was Black and Hispanic. In 2009, 32 students reported their identity as
Black and Hispanic, increasing to 165 students in 2016 and to 175 students in 2019 (Table 4).

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Figure 2
Comparative Analysis of Disaggregated Two or More Races Category

Table 4
Two or More Races Category Disaggregated
Two or more races category Fall 2009 Fall 2016 Fall 2019
Black and American Indian 7 36 17
Black and Asian 6 56 42
Black and Hispanic 32 165 175
Black and Pacific Islander 2 5 6
Black, American Indian and Asian 1 3
Black, American Indian and Hispanic 22 16
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Two or more races category Fall 2009 Fall 2016 Fall 2019
Black, American Indian, Asian and
Hispanic
3 2
Black, Asian, and Hispanic 2 13 5
Black, Asian, and Pacific Islander 3 5
Black, Asian, Pacific Islander and
Hispanic
3 1
Black, Pacific Islander, and Hispanic 1 1 2
White and Black 20 79 75
White, Black and American Indian 1 14 12
White, Black and Asian 2 10 12
White, Black and Hispanic 3 20 23
White, Black, American Indian and Asian 4 4
White, Black, American Indian and
Hispanic
19 5
White, Black, American Indian, Asian and
Hispanic
3
White, Black, American Indian, Asian and
Pacific Islander
1 7 1
White, Black, American Indian, Asian,
Pacific Islander and Hispanic
5 24 9
White, Black, Asian and Hispanic 1
White, Black, Asian and Pacific Islander 1

The second most frequent racial combination during these years was White and Black. In
2009, 20 students reported their identity as Black and White. The number of students who
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identified themselves as Black and White rose to 79 in 2016. In 2019, 75 students reported that
they were Black and White.
The third most frequent racial combination varied during the years 2009, 2016, and 2019.
In 2009, Black and American Indian was the third most frequent racial combination identified by
Black multiracial students. In 2016 and 2019, Black and Asian was the third most frequent racial
combination.
Discussion (Quantitative)
As a result of disaggregating the “two or more races” category, additional data is
available to define the student population with greater specificity. The disaggregation revealed
that the largest multiracial combination on the campus of Public University are students who
identify as Black and Latino. The percentage of students who identify as Black and American
Indian was relatively high, given the percentage of American Indian students who identify solely
as American Indian.
Without disaggregation, the students only exist in the data as an unspecified combination
of races. The specific elements that make up their identity are unknown unless the data is
disaggregated and analyzed as in this study. The fact that there are 64 combinations within the
“two or more races” category suggests that the category includes a wide range of people and
experiences.
Unanticipated Result
As a result of disaggregating the “two or more races” category, I identified what appears
to be an anomaly in the data. In 2016, 24 students selected the Black category and every other
race category offered when asked to identify themselves. Each of these students reported that
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they were White, Black, American Indian, Asian, Pacific Islander, and Hispanic. In 2009, only
five students identified themselves in this way. In 2019, the number was nine.
Participants (Qualitative)
The participants in the qualitative phase of this study were four professional women who
identify themselves as Black and as multiracial and who have graduated from a college or
university in the United States over the past 30 years. The women ranged in age from in their 20s
to in their 50s and none were recent college or university graduates. In the interviews, each
described the experience that has been defined as identity denial and each developed a means of
coping with its expression in race and ethnicity surveys and forms.
The responses of the participants are best understood in the context of their personal
histories. Family composition and upbringing, community relationships, educational settings,
and faith-based communities were referenced by the participants. A profile of each person’s
history was constructed based on their responses to the interview questions, including
biographical questions. The following biographical sketches provide context that may illuminate
the data drawn from the interviews. Pseudonyms are used to protect the identities of the
participants.
Ella
Ella’s mother is Japanese, and her father is African American. She holds a bachelor’s
degree. Ella and her siblings grew up in a predominantly Black neighborhood in Los Angeles,
steeped in Black culture. They were an immigrant family. Ella’s older siblings were born in
Japan and came to the United States with their mother when they were children. For them and
even for Ella, who was born in Los Angeles, there were steep learning curves. Her mother was
learning English by watching television, while her siblings navigated adolescence and young
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adulthood in a new country. Ella attended schools that were predominantly Black or were
diverse. She identified herself as Black and felt embraced by and a part of the culture. Ella
described her college experience at a predominately White institution as not traditional. She
worked two jobs to make ends meet and lived at home. When she did socialize on campus, she
found community at the Black Student Union. That spot on campus was where she most felt a
sense of belonging.
More than 20 years after graduating from college, Ella experienced a shift in the manner
in which she identified herself. This shift took place after accompanying her mother on a trip to
Japan. Ella’s mother had been in Nagasaki when it was bombed in World War II. Her mother
needed to return to Japan to prove that she was there as part of a program to offer reparations to
survivors. Prior to that period of Ella’s life, she did not identify much with her Japanese heritage
though she was deeply aware of it. She described the culture as very homogenous and not
welcoming of difference. After the trip and after having developed a different approach to life in
general, she began to embrace her multiracial identity more and now identifies as Black and
Japanese. Ella is in her 50s.
Miriam
Miriam’s parents married at a time when Black and White marriages were still a rarity.
Her father was White; her mother is African American. Miriam holds a bachelor’s and a master’s
degree. When Miriam was a child, the family lived in a small rural community in upstate New
York that was predominantly White. In high school she excelled academically and developed a
love for learning. Being a high achiever was a salient aspect of her identity. After a particularly
painful identity denial experience in high school, Miriam entered college and did not seek
relationships with Black students or the Black community and did not feel herself a part of the
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community. She viewed the Black community as something she did not want to be a part of
because of her identity denial experience.
Miriam’s perspective began to change in graduate school. She was part of an informal
community of students and others in her cohort at a competitive university. The Black
community was warm and welcoming and included people who were like her. An equally
important shift happened for Miriam as she began to read more about U.S. history and fiction
and nonfiction about race, history, and identity. These experiences and personal exploration led
to an embrace of her Black identity. That embrace has developed into a sense of purpose. Miriam
sees her presence and identity with the Black community as a means of combating false
narratives and a way to contribute to the uplift of the community.
Harriet
Harriet is in her 30s and identifies as Black and Chinese. Her mother is Black and
Chinese, and her father was African American. Harriet holds a bachelor’s degree. As a child,
Harriet moved smoothly between both cultures. After her parent’s divorce, she was raised
primarily by her paternal grandmother who is Black. During elementary and middle school in
Northern California, Harriet felt comfortable and in community. She had friends who were also
biracial, and she attended a school that was very diverse racially and ethnically. In high school
she moved with her mother and lived in Florida and then Colorado. In both schools, diversity
was low and her sense of being the only one was high, creating a feeling of isolation. Harriett
attended college in Colorado, and there she found community again. The university was
overwhelmingly White; Harriet was a part of a living-learning community and related to students
of different races, different mixes, and different cultures.
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In Harriet’s experiences, people are not able to identify her racial background. Someone
meeting her for the first time would not see that she is Black and Chinese. She has been
mistakenly placed in various racial groups. Often, she is thought to be Latina or some type of
European. This racial ambiguity has not lessened Harriett’s sense of her own self-identity. She is
comfortable identifying as Black and Chinese, but she prefers identifying as simply multiracial in
high stakes situations such as a job application. The term multiracial shields her identity from
bias, while also identifying her as a person of color. Harriet’s husband is Mexican, and she
identifies with the immigrant experience.
Journey
Journey is in her 30s and identifies as mixed, multicultural, and Black and White. Her
mother is Black, and her father is Jewish and Hungarian. Journey holds a bachelor’s and master’s
degree. Journey grew up in a home with both parents who each instilled in her a love and
appreciation for both cultures. In elementary school, Journey experienced an identity denial
event when she was forced to select one race on a demographic form that preceded a
standardized test. Journey attended Hebrew school and her bat mitzvah invitation was decorated
with kente cloth, a West African fabric. The invitation for this important rite of passage
acknowledged and paid respect to her identity as a person of African descent.
In high school, Journey was a high achiever. Among a diverse student body, she was
viewed as a role model for Black students. Although she identified as Black and Jewish and had
friends from both groups, there were times when she did not feel as welcomed by her Black
peers.
In college, Journey identified as mixed, multicultural, and Jewish and Black and found
community among a diverse gathering of people. She continued to oppose the notion of choosing
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between her identities. As a professional, Journey is active in efforts to increase Black
representation in her field. She is a key organizer and advocate for Black representation. The
comfort she felt in identifying as multicultural and Black and Jewish has continued.
Results Research Question 4
Two key themes emerged from the interview questions designed to answer this research
question: (a) survey responses serve as a form of identity assertion in response to present or
previous identity denial and (b) the survey questions are treated as a dialogue with an unseen
other.
Theme 1: Identity Assertion
Survey responses serve as a form of identity assertion in response to present or previous
identity denial. The respondents in the current study described identity denial experiences in
detail. Two individuals described very specific incidents. The other two described ongoing
experiences. The incidents and experiences left impressions that formed their strategy for
answering race questions on surveys and demographic forms.
Identity Denial
As a third grader, Journey was preparing to take a standardized test and was confronted
with a survey section that included questions about race. Back then, the instructions were to
“pick one.” Journey’s parents were a married biracial couple who were raising her to feel pride
and connection with all of her cultural heritage. That day in third grade, Journey remembered
feeling confused about what to pick and what it would symbolize. If she identified herself only
as Black, would she be denying her father, who was Hungarian and Jewish? If she identified
herself only as White and Jewish, would she deny her mother and her close-knit Black family
and their culture?
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I remember in third grade, bringing it up to my teacher. … I don't know what I'm
supposed to answer because it’s both [boxes]. … I just remember doing that and telling
my teacher like, ‘this isn't right.’ Why do I have to pick one? And I just, I genuinely
didn’t understand it because both my parents were in my household and I didn’t, I didn’t
know what else I should do. Um, and I just remember [the teacher] telling me like, ‘Yeah,
but it doesn’t matter; you just, just pick one. It doesn’t really matter.’ Like, that’s how the
teachers approached it when I was going through school.
The teacher’s admonition to just pick one and her contention that “it doesn’t really matter”
illustrate the disconnect that existed for decades between the shape of surveys and the way
people lived their lives. Contrary to the admonition of the teacher, and according to the research,
it is of great significance to those who embrace their membership in more than one racial or
ethnic group.
Miriam reported multiple experiences with identity denial that shaped her survey
responses, which changed over time. As a high school student touring a college, Miriam recalled
being placed with an all-Black group. In this example, the identity denial that she experienced
was not race-based, but academic. Miriam’s identity as a high school student included that of a
high achiever. She excelled in school taking honors and Advanced Placement classes and she
took pride in that aspect of her identity. On a sleepover college tour, however, she was matched
with a group of urban Black youth and spent the weekend with them. The presumption was that
these youth were her peer group. But Miriam’s sense of herself extended beyond race. She saw
the group of honor students and wondered why she had not been placed with that group. She
resented being denied membership in the group with which she felt the most affinity, race aside.
Her history as an honors student, one who excelled academically, was earned and significant to
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her. Her “people” were not Black city girls with whom she had been matched, but with a group
of high achievers, which would have been her natural group if not for her race. She watched as
the high achievers toured the library, while her group walked past it, uninterested.
Oh, so because of that experience, I did not even apply to that school. I was so
traumatized. I was like, but I was angry, ‘Why didn’t they put me in the honors group, the
honors tour group? Why did I have to be in an African American group?’ They didn’t ask
me. I didn’t have a choice. I qualified for both, but they chose to put me in the African
American group where I felt totally, totally out of place. And I was like, ‘What is it, I
don’t get to be in the honors group, because I'm Black? Because there weren’t any Black
kids in that honors group that I saw walking around, you know what I mean?
As an undergraduate student, Miriam chose not to identify as Black only because of her
experience of being denied acceptance into the group of high achievers. As an undergraduate she
steered clear of programs and experiences that centered African American culture. Miriam grew
up in a rural community in upstate New York, surrounded by trees and part of a mostly White
conservative community. Her experiences in a Black community were familial and Southern,
unlike the city girls from New York, who talked differently, behaved differently and were from a
lower socioeconomic background.
I know now that Blacks are not underachievers, but this was my experience at 16 years
old. I don’t want to be with the kids who just slough off the library. So, I really actively
did not participate in any type of African American groups or affinity groups or anything
like that in college and grad school because I didn’t see it as something that I needed or
frankly wanted to be a part of. That wasn’t my culture.
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Harriet’s identity denial experience has been ongoing. Others have assumed her to be
“European” or “Mexican.” In either instance, she is assumed to be foreign born. In the case of
those who identify her as Mexican (her husband is Mexican), she is also assumed to be a Spanish
speaker, though she is not. “Everything that I’m not, people have called me. You know? [They]
thought I was different races. But I’ve always felt the same,” she said.
Ella experienced two types of identity denial experiences. The most salient was a general
lack of acceptance by the Japanese community because of her and her family’s Black identity.
Japanese are very homogenous, a very homogenous community, unlike the Black
community where there’s a blending of culture, and there’s more of a ready acceptance of
others, you know, who don’t look like you or maybe, you know, [don’t] have the same
exact historical experience. So, I just didn’t spend a lot of time invested there because I
never felt embraced.
The second type of identity denial that Ella described came from outside of the two groups that
form her heritage. Ella, whose actual first name very immediately identified with her Japanese
heritage, described multiple friendly phone conversations in a work setting with an individual
who she’d never met. When the individual visited the office one day and saw Ella face-to-face
for the first time, the warmth faded. There was a gasp and the individual blurted out, “But you’re
Black!” as if Ella had been masquerading on the phone as a Japanese American. Thus, from the
Japanese community and from others, Ella experienced identity denial.
Strategy
The respondents all shared subsequent experiences of survey taking that were shaped and
informed by their experience of denial. These strategies vary greatly. Each described arriving at
her strategy individually and organically, based on lived experiences.
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After her experience in third grade, Journey described a distinct manner of answering
race surveys when instructions were to “pick one.” She developed the practice of altering her
responses between identifying as Black and identifying as White. She kept her own tally and
practiced an intentional form of fluidity designed to bring a greater sense of authenticity. If she
couldn’t be who she was in one survey, she would report her full identity across surveys.
I would switch it for every other test. So, one test I would be White, and then the next test
I would be Black, which now looking back I’m sure I messed up some numbers
somewhere along the lines. But if they wouldn’t let me [identify as two races], I switched
each time.
For Journey, choosing one race was the equivalent of denying or ignoring one of her
parents and their culture. She identified and loved both and being made to choose was wrenching
and maddening. She described it as a wrenching choice to have to make.
Those are my parents, you know. My father is White [Hungarian]. I’m Hungarian. I’m
proud of being, you know, a first-generation Hungarian from immigrant parents. My
mom was Black … and I just always grew up knowing where my family came from and
not being apologetic in any way about it. … That’s what makes me, me. So, if you’re
going to ask me to define me, like, that’s who I am and I would get mad when people
didn't like that answer. … No, you have to pick one. I’m like, ‘Well, why do I have to
pick one if they’re both my parents?’… I never understood it. … It just, it just didn’t
make sense to me.
Miriam developed a response to the race question on surveys that asserted her authentic
identity and was a consequence of and shaped by her experience of identity denial. Miriam
described her approach to answering the “pick one” race question: “And it would say, ‘please
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check one,’ and I’d be like, ‘x, x, x.’ I don’t care. You pick one, because I’m not picking one,
right?” Miriam’s strategy for answering race questions on surveys was thus borne out of her
experience of being denied the ability to choose her authentic identity. Miriam not only was not
allowed to choose her true racial identity, but as a result she suffered the loss of opportunity in a
key identity denial experience.
As a result of Ella’s experiences, her response to the race question has changed over time.
Ella spent most of her life identifying as Black because of her identity denial experiences and her
acceptance in and deep connection to the Black community. Later in life, she began to check
Black and Japanese or multiracial in response to the race question. When those options are not
available, she refuses to answer the question.
So, I have found myself really recently, you know, skipping [it]. And the reason why I’ve
skipped it is because I’ve been mad that I couldn’t check both boxes or they didn’t have a
box for multicultural, when previously, I think I would always just check Black. But I
think recently, and what I mean by recent is probably the last six months, you know, I
just feel like, why should I have to deny one part of who I am, or my heritage, you know?
Theme 2: Talking Back and Standing Up
Responses to race questions on a survey may be viewed as a type of discourse with an
unseen other. Respondents recalled answering race questions on a survey as if they were in
discourse with an unseen other. In this dialogue, the respondent used their responses to correct or
direct the person on the other end of the survey. This is illustrated by Miriam’s declaration, “You
pick one. I’m not picking one.” Or Journey’s decision to move between Black and White each
time, as if to say to the person on the other end of the survey, “if you won’t give me the option to
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choose more than one race, I will create the option.” Journey’s move is essentially showing the
survey creators how choice should be offered.
In engaging with the survey as if they were in dialogue with a person, respondents
exhibited an awareness of the race question as a creation of unseen others. When Journey, in
describing the lack of options said, “This isn’t right,” she was suggesting that someone had made
a decision that was unfair or unjust. Further, that decision had harmed her. Similarly, Miriam’s
proclamation of, “You pick,” was directed at the person at the other end of the survey as a
challenge to an impossible choice. The respondents did not approach the questions in an
impersonal, formulaic manner. Instead, they challenged the creator of the question and the
instructions, with the certainty that people had created the question, had erred, and could correct
their errors.
Ella’s decision to skip the question altogether is the conversational equivalent of giving
someone the cold shoulder. There is a purpose wrapped in Ella skipping the question. It is not
happenstance or laziness. Her purpose is to say that absent more information and absent the
opportunity to share her full identity, she will not participate in this conversation.
Results Research Question 5
Two themes emerged from interview questions designed to answer research question 5
and from the discussion in general. These related themes were (a) a lack of awareness of race
reporting strategies and (b) questions about the potential implications of race data usage.
Theme 1: “When Did That Happen?”
Respondents were unaware of race reporting practices. None of those interviewed for this
study was aware of the way data is reported in higher education race surveys or of their
exclusion from the Black tally. Every respondent expressed surprise that they would not be
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tabulated in the data in the specific races they reported. Their disapproval of the reporting
practice was not a statement against being offered the option of selecting two or more races, but
specifically of not being counted in the race categories they selected. For the respondents, being
recognized as Black and another race held great significance. They did not expect that selecting
the Black box and the box for their other racial identity meant they would not be reported as
Black.
Again, looking at our history—like when did that happen? Because it wasn’t that long
ago, that it really didn’t matter what you looked like, if you had any Black in you at all
like, even just the tiniest bit that you might not even know about, that made you Black
and therefore made you subject to that violence that I talked about earlier, that violence,
that was the number one, just the go-to, it wasn’t the last resort, it was the very first line
of defense against anything we don’t like about Black people violence.
Journey, like other respondents, appreciated the ability to include more than one race on a survey
but did not know the manner in which the responses are tabulated and reported.
Honestly, I don’t think I thought that much about it. And realizing that, yeah, you put
[two or more races] they’re not going to know what that is. I knew it subconsciously, but
I don’t think I really recognized when you have that how limiting it becomes, and what
that further implication could be.
Theme 2: Questioning the Question
Respondents raised questions about the potential implications of race data usage as
reported. The universal lack of awareness of the manner in which race data is reported led to a
questioning of the method. None of the respondents reported learning about how race is reported
in higher education or elsewhere. There seemed to be an underlying assumption that the
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collection and reporting methods would be consistent. The fact they are not suggests to the
participants a hidden process or a bait and switch that Miriam explained:
What then happens behind the scenes? Now that I know more about how it all works,
boxes are not arbitrary. Somebody then goes and takes that information and does
something with it. So, what is happening with that multiracial box?
Ella questioned the need for and intended use for the data. She is skeptical when the
question is asked, as it often is, without an explanation for how the data will be used. She said
this is particularly true with some online surveys and questionnaires from nonprofit
organizations.
Why do they want this information, and what are they going to use it for? So, I think
when … there’s not a clear explanation. I wonder why the question is there. You know?
Like what it has to do with their organization and their mission.
Ella also questioned the impact the federal methodology might have on funding for underserved
communities. She reported seeing value in knowing the composition of the nation and the needs
of populations.
Being made aware of the federal methodology left Journey wondering why the reporting
of race was limited, given the many experiences housed in the category of “two or more races.”
Having the ability to say that you are more than one race is important. I think … the
documentation needs to be clear that if you put two or more [races] they’re not going …
any deeper than that. I wish that there was the option to do two or more and here’s what
they are. … I wish there was a way that you could get counted in both groups. [It’s] only
fair. Both need representation.
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Prospective students need accurate and specific information in Harriet’s view. She
proposed that students’ races and ethnicities should be reported as specifically as possible. For
even greater clarity of campus demographics, she proposed specificity for reporting the race and
ethnicity of faculty members as well.
Or maybe they need to [report] both [races], you know, just to be more accurate. And
people will know exactly what type of campus they’re going to, what type of classes they
have available, they can relate to. I mean, even more so … the faculty members. Yeah, I
think that would really help if they were more specific as opposed to just grouping them.
… Be more specific so that people would understand who’s on campus. Yeah, and the
faculty members are the most important. I would think [students would] become
comfortable talking to faculty members about this stuff, in general, I probably would, if I
knew they were more like me.
Unanticipated Theme: Purpose-Driven Self-Identity
Self-identity expressed on a survey or form can be purpose driven beyond the realms of
identity, ancestry, and culture. The approach to answering the race question found on surveys
and demographic forms often reflected a decision years in the making and with a defined
purpose. This purpose often extends beyond the discussion of the self, but the self in relationship
to community. Miriam chose to identify as Black and White and sometimes as Black out of a
desire to assist the most maligned group of her two racial groups. By doing so, she is following a
tradition set by her mother of choosing to identify in a way that assists a community. In the case
of Miriam’s mother, the chosen identity was Protestantism and membership in the congregation
of an African Methodist Episcopal (AME) Zion church.
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All the Black folks from miles around came to this one church, a very small
congregation. It is the only Black church for miles. And when I got older, I found out that
my mother … actually had converted to Catholicism in her youth and in her heart she was
Catholic. And that was like what? Like, you’re Catholic? What’s happening? … How is
this even possible? You know? And I was like, ‘why didn’t we go to the Catholic
Church? Why did we go to the AME Zion Church, all those years? And she said, “Well,
I mean the Catholic Church in the community … had a full congregation. There were
several Catholic churches where we lived. But there was only one Black church, and it
had a very small congregation and … I just felt that I was needed more there than at the
Catholic Church. And I was like, ‘O.K., so you say you attended this Black church and
took your kids to this Black church, instead of the church that you converted to, because
you felt like the Black people there needed you. And, you know, so basically that was it.
But you know, that concept has kind of stuck in my head and I think that the older I get,
the more I realize that by self-identifying as biracial or multiracial which is truly what I
am … it’s not really helping anybody … what I have to offer is not really being offered to
anyone, by being biracial or multiracial, but it can be more useful by identifying as
African American. I can kind of offer what I have to offer to this cause and these people
who need it, you know? So, I think that as I get older I swing more and more toward just
saying, ‘Look, I’m just Black, it doesn’t really matter what I look like or what my
background is, let’s just call it Black because that’s where I’m needed.’ In the same way
that my mom felt that’s where she was needed in that church, this is where I’m needed.
Miriam’s self-identity evolved, but so did her intent to use her identity as Black for the purpose
of contributing to the community.
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Similarly, Journey is comfortable with being identified as multiracial, but may choose to
identify as Black because of a desire to represent Black identity and to have a positive influence
on issues impacting Black people in the workplace and in her industry.
And I think it’s important to open up opportunities like I recognize there are not a lot of
Black women in my side of my job and if me filling out a survey means that the company
will show more Black people than not, I want to be a part of that. But honestly, for most
of our documentation, mixed is an option that I circled because I want to find the other
mixed people and I think that’s important to learn their backgrounds and what it’s about
and stuff. So even now, like, when I have the option to do it, I still pick [multicultural],
but if it doesn’t exist, I probably would put it as Black just to ensure that people saw that
there is some representation at our company.
Harriet’s decision to select multiracial as an identifying term, when possible, extends the
act of selecting race categories into the realm of self-preservation. She described her selection of
a multiracial identity as a means of lessening bias in high stakes circumstances. Harriet reasoned
that selecting a multiracial designation would lead to fairer treatment than she might receive if
she identified herself as Black and Chinese. “And I’d be very conscientious because I want it to
be an even playing field … Then I would just put multiracial.” This response illustrated a reality
of being multiracial: an individual can receive and suffer from the biases levied against each
group with which they identify. For Harriet, choosing to identify at times as multiracial is a way
to shield herself from the biases and discrimination against people who are Black and/or Chinese
in high-stakes situations.
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Unanticipated Theme: Self-Identity Changing Late in Life
Collectively, the respondents made a clear statement about the evolutionary nature of
identity over the life cycle. The self-identity of the four respondents continued to evolve and be
refined over time. Well past adolescence and the college years, and deep into their professional
lives, they were refining their self-identities.
Two experiences converged and began the stage of identity that Ella is now in. She
accompanied her mother on a trip to Japan. In her youth, her mother lived in Nagasaki, Japan,
and was there when an atomic bomb was dropped by the United States during World War II. The
Japanese government was paying reparations to the victims and Ella’s mother needed to return to
Japan to prove her identity as a victim. That experience was transformative for Ella that allowed
her to feel closer to her Japanese heritage. Ella has also reached a different stage of life that has
enabled her to disregard the reaction of some in the Japanese community to her Black identity.
This stage came when she was in her 50s: “And then now I’m just a little bit more unapologetic.
I don’t really care what anybody thinks or if they want to accept me or not. It is a part of my
culture and my heritage and my upbringing.”
Miriam’s understanding of history expanded through a Black book club, but mostly
through her own personal reading. She became hungry, she said, for her own tale. She read
authors like Danzy Senna, whose work explores issues of race, colorism, and elitism and
includes characters who are biracial. She also read and learned about the history of Black people
in this country.
I never took any Black history. I never took anything like that. So, I’ve had to pick up my
knowledge in bits and pieces just through life, and through my own curiosity. So, really
[it] hasn’t been until I have been probably in my early 40s that I began to really truly
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understand the full history of Blacks in America, and, like, the ramifications of what that
means, on the infrastructure of our society, how that impacts us as a people, and yes, even
me, you know, in ways that I never understood because I was I was like, ‘Oh, well, you
know, I don’t talk Ebonics. My skin is pretty light, like, when does any of this affect
me?’ Yes, it does. It does. All of this history affects me. But I did not know that until
probably my early 40s, you know, maybe like 6 or 7 years ago. It all started to come
together.
Summary
This chapter detailed the findings of quantitative and qualitative analyses that were aimed
at answering the research questions through a QuantCrit lens. The quantitative analysis revealed
different trend trajectories for the percentage of students who identified themselves as Black and
students who identified themselves as Black and multiracial or multiethnic. The analysis further
demonstrated that applying an all-inclusive whole assignment methodology created a Black
identified population that was greater, by as much as 45%, than the population of students who
identified themselves as Black and no other race. An analysis of the disaggregated data also
revealed that, of the students who identified themselves as Black and multiracial or multiethnic,
Black and Latino is the most frequent combination. The qualitative analysis added depth to the
quantitative findings by including the voices of individuals who are Black and multiracial. A
thematic analysis of the qualitative data revealed the participants’ shared experiences of identity
denial and the development of a strategic approach to answering survey questions on race. The
qualitative analysis further revealed a lack of awareness of the federal race methodology and a
conflicting expectation that their identities would be reported in the data as they had reported
them on the survey. The participants’ newfound awareness of the federal reporting methodology
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led to each raising questions about the data, its accuracy, its usefulness, and its purpose. The
qualitative analysis illuminated the quantitative findings through the lived experiences of people
who are Black and multiracial and the emergent themes.
The next chapter offers a discussion of the quantitative and qualitative findings. In
Chapter Five, the outcomes of the study will be explored and related to previous research. The
discussion will further examine the quantitative and qualitative findings in relation to the
problem of practice. Recommendations for practice are included, as well as suggestions for
further research.

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Chapter Five: Discussion
More than a decade after its implementation in 2009, the federally mandated race
methodology for data collection and reporting has produced a wealth of data in higher education
that can be analyzed to answer questions related to race. Like other universities and colleges in
the United States, Public University has gathered this data. The quantitative phase of this study
analyzed data through a QuantCrit lens of interrogation. The qualitative phase of the study aimed
to provide deep, rich data that would provide a narrative that expands knowledge surrounding the
data. The conceptual framework for this study proposes that lived experiences, sometimes over
decades, influence how individuals self-identify on race surveys, yet a federal methodology that
mandates how race is measured on U.S. campuses (Office of Management and Budget, 2001)
imposes race categories that usurp self-identity.
The research was guided by five questions:
1. What are the key 10-year demographic trends for the Black student subpopulation
and the Black multiracial/multiethnic subpopulation at Public University?
2. How does the demographic profile (number and proportion) of Black students at
Public University change when an all-inclusive whole assignment bridging
methodology is applied to the student population?
3. What are the most frequent race combinations found at Public University when
the “two races or more category” is disaggregated?
4. How do Black multiracial or multiethnic people who have experienced identity
denial view and interact with race and ethnicity survey questions?
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5. How does the reporting of Black identity, as mandated by the federal government,
align with expectations and assumptions for reporting held by Black multiracial or
multiethnic people?
Findings
The following quantitative and qualitative summary of the findings answer the research
questions.
Finding 1
Use of the federally mandated methodology underreports Black identity, including those
who intend to be counted as Black.
This finding answers Research Questions 1 and 5. My analysis found that the population
of students who identified solely as Black declined steadily at Public University, while those
who identified as Black and multiracial increased over a 10-year period beginning in 2009. Such
declines were predicted by and are consistent with the findings of Lee and Orfield (2006). More
recently Bates et al. (2019) noted that the federal race data methodology could produce analyses
that failed to capture Black students of Hispanic descent and students who identify as Black in
combination with another race the data. The U.S. Department of Education (2007) anticipated
the kinds of declines in student populations that my analysis found. The guidance associated with
the policy asserted that the new reporting method would produce more accurate data, and “in
most instances, the Department anticipates that the size of the two or more races category will
not be large enough to cause significant shifts in student demographics,” (U.S. Department of
Education, 2007, p. 59270). On a national scale, with large populations this may be true, but on
the campuses of colleges and universities where subpopulations are sometimes counted in the
tens and hundreds rather than the millions, it is more difficult to dismiss the declines as
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insignificant. When the margins are slim, declining populations may carry more significance and
cause more concern.
The qualitative interviews provided evidence that some individuals who are included in
the “two or more category” intend to be included as Black. All of the participants in the
qualitative interviews held the expectation that the data reporting would reflect their identity as
the two specific races that they reported. Although no one expressed an awareness of the
methodology that would allow for such a count, there was an underlying assumption. Learning
that the data is reported differently left the respondents with the idea that some unknown factor
was taking place behind the scenes. The interviews confirmed a gap between how data is
reported and people’s awareness of how data is reported. Further there is a gulf between how
data is reported and how respondents want it to be reported as a representation of their authentic
identity. Given the research community’s tragic history with Black America (Washington, 2006;
White House, Office of the Press Secretary, 1997), fully explaining practices should be
prioritized.
In key ways, the data is collected in a manner that avoids some of the causes of identity
denial (Cheryan & Monin, 2005) and microaggressions (Harris, 2017; Johnston-Guerrero et al.,
2020). This reverses a long history in the United States of racial data collection that was based on
hypodescent and that, according to what is known today, promoted identity denial. The failure to
provide options that recognized the full spectrum of a person’s identity was the most evident
cause of identity denial on surveys. While significant changes were made in how data is
collected that avoid perpetuated identity denial, those changes did not extend to data reporting.
The U.S. Department of Education’s (2007) guidance to respect the self-identity of the
respondent is reflected in data collecting but is absent in the data reported. The Department of
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Education also admonished against creating a multiracial box on the survey. The survey that
students take does not include a singular “multiracial option.” Again, the reporting is a different
animal. Multiracial students are all reported in the “two or more races” category. This category
functions in the same way that a multiracial box would. The very thing that the U.S. Department
of Education advised against in its guidance, exists in the reporting of multiracial students.
Limitations
A limitation of this study is the fact that all the participants were women over the age of
30 who lived in Southern California. This limitation presents a threat to external validity. Studies
show that race identity is fluid and can be situational (Renn, 2000) and is influenced by factors
such as age, gender, and location (Campbell, 2007). Respondents in different geographies (urban
versus rural), different ages (born before 1965 and after 1965), and different genders may report
different experiences and views.
Finding 2
Applying an all-inclusive whole assignment methodology results in a measure of Black
identity that is larger than the population reported using the federal methodology and respects
and acknowledges the self-identity as shared by participants.
This finding answers Research Question 2. Applying an all-inclusive whole assignment
methodology produced a Black identified category that was consistently larger than the Black
category created using the federal race methodology. Identifying a different population size is
consistent with the findings of several studies that suggest that the methodology used to measure
race can produce vastly different data (Allen & Turner, 2001; Gullickson & Morning, 2011;
Mays et al., 2003; Perez & Hirschman, 2009) for the same population. The all-inclusive whole
assignment methodology reflects identity as reported by the respondents. If the goal is to count
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race as reported by students, this methodology accomplishes that because respondents are
included in every race category they select.
This finding is confirmed by data from qualitative interviews related to identity denial
and the development of a strategy for answering survey questions about race. The conceptual
framework for this research proposed that the lived experiences of individuals influence how
they respond to survey questions about identity. The study found that the participants all reported
having experienced identity denial and three respondents referred to specific instances that
shaped the manner in which they refer to survey questions now. This relationship is detailed in
the following concept map (Figure 3).

Figure 3
From Identity Denial to Identity Strategy

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Individuals experienced identity denial when they were presented with survey questions
about race that did not provide sufficient options for self-identity. The “choose one” surveys that
were common prior to 2009 and still exist today caused an identity denial experience (Cheryan &
Monin, 2005). Answering the questions would force them to select one race over the other or
others that make up their identity. As a result of this experience, individuals may experience
anger, confusion, self-reflection, and a lack of self-autonomy. This in turn can lead to a
development of self-identity autonomy, evidenced in a rejection of the imposed (monoracial
identity) and/or an embrace of the denied (multiracial) identity. This embrace and denial can
further lead to the creation of a strategy for answering race survey questions and a personal
narrative about the race question expressed on surveys. This concept builds on and expands
knowledge of the identity denial experience and its role in the formation of self-identity and its
expression in surveys and demographic forms.
Though the federal race methodology provides expanded options that allow respondents
to more fully express self-identity, it does not allow for this full expression to be reported. The
federal race methodology expanded options for identity expression in surveys but kept denial
present in data reporting. This may seem to be a harmless act because data reporting does not and
should not connect back to a specific individual; thus, no individual is harmed. However, this
practice of aggregating data in reporting serves to negate self-identity choices and to do so in a
way that is generally unknown and not explained.
An all-inclusive whole assignment methodology avoids practices that cause identity
denial and avoids the challenges that may arise from assigning fractions to an individual’s life.
The work of several researchers such as Campbell (2007) and Allen and Turner (2001) suggest
how Black multiracial individuals would identify themselves if forced to choose one race, yet
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identity denial studies also demonstrate the harm caused by forcing a choice. Allen and Turner
(2001) suggested fractional assignment as a fair way to bridge to earlier race data. For some, the
idea of fractional assignment may harken back to a time when enslaved Black people were
counted as three-fifths of a person. It may further a monoracial paradigm as the standard and the
trope of race as rooted in biology.
Limitations
This study only analyzed the data for Black identified students at Public University.
Assuming that the same methodology would be applied to all student populations, the percentage
for all student groups would change. Although my analysis focused on the change in the
population of Black identified students as shown in Figure 1, this type of methodology, if applied
across the board, would likely increase the populations of other racial groups as well. Further,
this methodology results in percentages that exceed 100%.
Finding 3
The disaggregation of the “two or more races” category allows for a fuller view of the
student population.
Disaggregating the data in the two or more races category allowed for a view of the
student population that is not evident in the minimal reporting required by the methodology. The
disaggregation revealed that Black and Hispanic students are the most frequent combination or
mix. This finding is significant given the reporting mandated by the policy. Under the reporting
methodology, these students would appear in the data as Hispanic only. Public University is a
Hispanic Serving Institution, with a majority Latino population. Because the majority of students
are Hispanic, including students who identify as Black in the Latino population effectively erases
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these students, yet their experiences may be inconsistent with the experiences of others in this
category.
The numbers of students who identified themselves as Black and American Indian
indicates the importance of American Indian roots to respondents. In 2009, Black and American
Indian was the third largest Black multiracial group at Public University (Table 4). Black and
American Indian marriage was not unusual in certain parts of the nation during certain historical
periods (Campbell, 2007). Campbell (2007) suggested that those who self-identified as Black
and American Indian in contemporary times did so based on knowledge of an intermarriage more
distant in their family tree. Campbell (2007) found that if forced to identify themselves with just
one racial group, 95% would select Black. For this multiracial combination in particular, there is
strong evidence that supports including them as Black identified. The revelation of this identity
has implications for programming and support on college and university campuses. This
combination may go unacknowledged if not for the disaggregation of data.
Researchers have confirmed the value of disaggregating data for understanding the
outcomes and the needs of subpopulations that may be hidden in a larger population. A push to
disaggregate data of AAPI university students demonstrated the value of this data (Teranishi et
al., 2013). Other scholars have encouraged the disaggregation of multiracial data as a means of
identifying needs of multiracial subpopulations (Tracy et al., 2010; Mays et al., 2003) and have
found that multiracial subpopulations may experience different outcomes than others. The
multiracial category is broad and encompasses a vast range of experiences. Further analysis may
glean additional data from the disaggregated “two or more races” data.

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Limitation
The qualitative phase of this study is limited by the absence of an Afro Latino in the
study. The terms Latino and Afro Latino cover a vast expanse of people and experiences. There
are those who identify as Afro Latino because one parent is Black and the other is Latino, while
others may identify because they were born in a Latin American country. Still others may
identify as Afro Latino because a parent or grandparent was born in a Latin American nation.
Though two generations removed, they also embrace this identity. Such variation suggests the
need for a focused study on this population.
Finding 4
Respondents who have experienced identity denial use the surveys to assert their identity
and to talk back to the survey creators.
Data from the interviews illustrate the meaningful ways that individuals who are Black
and multiracial engage with the question of race on surveys and demographic forms. The
interviews revealed that selection of more than one race on a survey can be an assertion of the
individual’s authentic identity and represents a talk back to unseen others. Identity denial is a
common experience for people who are multiracial. All of the respondents described identity
denial experiences in previous surveys and in encounters with other individuals. These
experiences happened in their younger years. As a result, each spoke of having developed an
approach for addressing the race question.
This approach represents a strategy that enabled the individuals to assume self-agency in
their identification. A decision to check all the boxes that apply, in defiance of “check one box,”
as explained by Miriam, is an example of identity assertion as is her declaration in the interview:
“You pick one,” as if she was speaking to the survey creator. Similarly, the decision to check the
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White category on one survey, but to check the Black on the next survey as Journey did is to
assert self-agency by self-identifying in a manner that is authentic to her life experiences. This
represents a strategy, and a talk back to the unseen others: survey creators, researchers, and
anyone who would or has denied Black multiracial identity. The assertion is simple: This is all of
who I am.
The data show that sharing one’s full identity carries significance, which is consistent
with previous research (Cheryan & Monin, 2005; Root, 2003). It means that individuals are not
forced to select and therefore value one part of their identity over another. Sharing one’s full
identity also means that no aspect of one’s being is rejected in order to fit a so-called monoracial
norm. To recognize the intersectional identities of an individual is to acknowledge the lived
experiences of the individuals and not sanitize them for easier accounting.
Unanticipated Findings
Although this study looked at student population numbers, the same methodology for
collecting and reporting race data exists for faculty and staff of colleges and universities. This
was raised by Harriet, a participant in the qualitative interviews, who noted that she would want
to know about the specific identities of faculty on a potential campus to determine if she would
feel as if there was someone to whom she could relate. Each of the respondents spoke to specific
experiences within their college years in which they felt nurtured by a community or learned in
class a history that helped shape their identities. For Harriet and Journey, the experiences took
place in either a classroom or a formal setting. Ella and Miriam described nurturing experiences
in the form of a caring professor, staff, or peer. This underscores the value of diversity and of
identifying diversity, including multiracial and multiethnic diversity, across the university
community: students, faculty, and staff.
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My analysis also revealed responses that research suggests may indicate that respondents
are making a statement about their views on race data collection. For example, 24 students
selected Black and every other racial category. It is wholly possible that students have each of
these races somewhere in their heritage. However, studies such as Dowling (2014) show that
survey respondents choose “some other race” because other survey options do not meet their
self-identity needs. Respondents may also decline to answer. Similarly, those students who
selected each available race may be signaling a view of race or an identity that merits further
study.
Implications for Practice
The implications of this study for practice are practical and pragmatic. Because race is an
invention, the things that flow from it are equally invented and should be viewed in the same
light as race itself. Further, as long as race is used to count humanity and measure experiences,
safeguards need to be in place to ensure that the data is an accurate reflection of a population,
and that it is understood to be a construct. This is especially true in higher education, a relatively
brief time period in the lives of individuals.
1. Researchers and survey takers should explicitly educate respondents about how
their data will be used. Knowing the purposes of the data may help students
understand the need to collect it and lessen the growing number of students who
select “some other race” or decline to answer the question.
2. Researchers and survey takers should educate respondents about the reporting
methodology before asking them to select a race or ethnicity category or
categories on surveys. It is important for respondents to understand how their
identity will be reported based on their selection. This is especially significant
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given the dichotomy between how race is collected and how race is reported and
the fact that some people do not know that such a divide exists.
3. Colleges and universities should develop staff expertise that allows for the use of
bridging methodologies and a more expansive reporting in some circumstances.
The OMB recognized the challenges of bridging, including a lack of knowledge
and the funding associated with it. Yet 10 years after the implementation of the
policy, time, cost, and expertise are not sturdy. The section of the application that
requires a selection should state in clear terms how the data will be reported.
People should be aware of the dichotomy between how race is collected and how
it is reported.
4. Researchers and data personnel should acknowledge that data represents a count
of Black students or Black and multiracial students, rather than the count of these
student groups. The difference in article represents a very significant change in
the way one views the data. It is not an egg, it is a quiche, and one of a number
cooked in different ways.
5. Researchers and data personnel should share disaggregated data for use by
students and their families and others to anticipate the student population and
subgroups.
6. Researchers and data personnel should use bridging methodologies and report
more than one set of data so that students will be able to select and better
understand the data.
7. Researchers should be clear about the need for race data and select a methodology
that is best suited for that need.
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Conclusion
Whether we see it or not, race data is present and influences the everyday lives of
Americans. It is the invisible hand that helps shape everything from marketing campaigns for
menthol cigarettes (Gardiner, 2004), to algorithms that determine protocols for medical treatment
(Smith & Spodak, 2021), to the creation of outreach and support programs on college and
university campuses. In 2021, race data was used to calculate and justify a lower payout for
Black former NFL players suffering from dementia than for their White counterparts (Belson,
2021). The result was an injustice that seemed outrageous when reported but was baked into the
negotiation and had been accepted even by the attorney representing the players. Only when
players sued, collected signatures, and went to the media, was the presence of race
acknowledged and ultimately discarded (Belson, 2021). While the NFL’s use of race was the
headline, the lack of scrutiny of the algorithm that included race data is the flashing red light that
serves as a warning far beyond the world of football.
If race is a construct, and in the 21st century social science agrees that it is, then certain
questions must be asked of the byproducts of race, specifically race-based data. What is the
purpose of the data? How is the data created: what are the methodologies used? Who has made
key decisions about methodology? Such questions are the minimal due diligence that social
science owes those individuals and communities who are reflected in the data. Race categories
and tabulating form the building blocks of race data that forms views, perspectives, protocols,
and practices. Data built on race is, by extension, as man-made as race itself. Given that we
know Johann Blumenbach and Samuel Morton, a founder of race and a perpetuator of its myths
(Wilkerson, 2020) were wrong, shouldn’t race-based data be required to give an account of
itself? By continuing to measure humanity by race, we continue the need for scrutiny that is as
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commonplace as the use of race itself. This study was not an attempt to layer logic on top of the
illogical and thus shaky foundation that race is, but to ask the questions that expose the whole
house as crumbling (Wilkerson, 2020).
QuantCrit exists as a branch of Critical Race Theory because, its creators argue, data is
often treated with a certain sanctimony and absolutism instead of scrutinized (Garcia et al., 2017;
Gillborn, et al., 2017). While there are immutable rules of mathematics, race data do not belong
in that category. To treat race data in the same way as these rules is to equate an average egg
with a quiche. Too often data that is a quiche is treated like an egg: the salt, the spices, other
ingredients, the baking are ignored. The argument that QuantCrit makes in the three tenets that
frame this study is basic good science and good journalism. The who, what, why, when, and how
questions are the starting point for the interrogation of data, rooted in the realization that data
does not speak for itself with the clarity that is needed on an issue as complicated as race. The
voices of individuals and communities speaking of their experiences, views, expectations, and
values, can help social science understand the data.
In America, race is a messy undertaking and the drive to smooth it over and make it
manageable pushes against a tide of complexity that offers no promise of ebbing. Wilkerson
(2020) describes race as the enabler of America’s caste system. For Omi and Winant (2015, p.
viii) it is a master category, “a kind of template for patterns of inequality, marginalization and
difference throughout U.S. history.” In the 21st century, race is being held up to the light and
recognized for its relationship to caste and other such harmful inventions. This makes for a
Sisyphean task for the Office of Management and Budget and the Department of Education.
Because race is illogical, often political, and its implications immense, anyone who endeavors to
use it faces challenge and peril. Their task is to make the biologically meaningless meaningful, to
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layer the illogical with a layer of logic. And as the nation becomes more diverse, race will only
become a flimsier foundation. Perez and Hirschman (2009) observed that if trends continue, by
2050, a quarter of Black people will be multiracial.
College and university campuses are microcosms of society and reflect its race
dynamics—particularly its implications for funding and resources. In various settings, money
follows numbers. This is true in congressional redistricting, NFL payouts, and in numerous
examples. Grants to serve populations may require that the population exists on the campus, or at
the very least, the argument may be stronger when populations are greater in larger numbers. The
population of students who identify themselves as a particular race, and thus may benefit from a
particular program, may be higher than the numbers reported using the federal methodology.
This may result in missed opportunities for individual students and for institutions.
In the aftermath of the murder of George Floyd, there was much discourse in the media
about America’s racial reckoning (Burch et al., 2021). In the world of data, this reckoning should
be called good science. But race data still has escaped scrutiny because, QuantCrit argues, of the
legitimacy accorded quantitative data. What QuantCrit calls for is what social science and
journalism should do as standard practices. To release invented data into the world without a
clear, explicit disclaimer, is to call the quiche an egg.
Suggestions for Further Research
The following are suggestions for further research.
1. Explore the Black and Latino racial group. Students who identify as Black and
Latino may do so stemming from different backgrounds. Some students may
identify as Black and Hispanic because one parent may be Latino and the other
Black. The term may also be used for those whose heritage stretches back to a
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Latin American nation. The students, their parents or grandparents may have been
born in a Latin American nation.
2. Delve into the inciting identity denial experience. These experiences are crucial in
the lives of individuals who are multiracial. While my research confirms the
significance of identity denial experiences, the mechanisms that lead to the
development of a strategy for responding to strategy are not fully evident.
3. Apply the approaches to measuring race to wider student populations, as well as
faculty. Campuses and universities are unique populations. While studies have
examined national population samples, similar measurement studies should be
done on student populations as well as faculty.
4. Examine the meaning of race to those individuals who select every race category
available. What message are they sending to the survey takers by making the
selection? How do they see their personal heritage encompassing all groups?

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Appendix A: Timeline of Race Categories in Education

Note. The data is from The history and origins of survey items for the integrated postsecondary education data system (2016-2017
Update), by Aliyeva, A., Cody, C. A., & Low, K. (2018). U.S. Department of Education. National Postsecondary Education
Cooperative. http://nces.ed.gov/pubsearch. In the public domain.
111

112
Appendix B: Interview Questions
Interview questions Alignment with research questions
1. I’d like to start with a few biographical questions for
background information:
a) Where were you raised?
b) Where did you attend college (undergrad)?
c) What years were you in college (undergrad)?
d) What degrees do you hold?
e) If you hold a graduate degree, what years were
you in graduate school?
f) What is your occupation?
g) Do you have siblings? If so, how many?
h) What is your age?
i) What was your parents’ occupation?

Background
2. How do you typically identify yourself in survey
questions about race?

RQ 4
3. I’m curious about the development of racial and
ethnic identity over time. I’m wondering if the way
you identify yourself racially and ethnically has
changed over the years.

RQ 5
4. I’m curious about the development of racial and
ethnic identity over time. I’m wondering if the way
you identify yourself racial and ethnically has
changed over the years.
a) How did you did you identify yourself as an
elementary age student?
b) How old were you when you entered college?
RQ 5, background

RQ 5, background, RQ 4 (a-g)
113

Interview questions Alignment with research questions
c) How did you identify racially as a college
freshman?
d) How did you identify as a 25-year-old?
e) If your identity changed in college, can you
describe the change?
f) If your identity changed in college, can you
describe what prompted the change?
g) If the way you identified yourself changed after
college, at what age did it change?
h) If your identity changed after college, please
describe the change.
i) If your identity changed after college, please
describe what prompted the change.

5. When you think back on your experiences in
college, what kinds of clubs, organizations, and
events did you participate in that were designed for
members of your racial groups. Can you give
examples?
a) When you were a student, were you involved in
activities, events, organizations for each of the
racial groups with which you identify, or
primarily with one racial group?
b) If so, what led you to participate in that racial
group rather than others?
c) How did those activities influence your feeling of
belonging on campus?
RQ 5, behaviors and experiences
114

Interview questions Alignment with research questions
d) How, if at all, did those activities, events and
organizations influence your academic
performance in school?
e) How, if at all, did those activities, events and
organizations influence your academic
performance in school?

6. When you were a student, were you aware of
expectations others had of you based on your race?
a) As a student were you sometimes viewed and
perhaps treated as a member of one race that
makes up your identity and not the other race, and
if so which race?

RQ 5, identity denial experiences
7. Did you ever experience a conflict between how you
view yourself and how people in the university saw
you?

RQ 4, identity denial experiences
8. How, if it all, have you seen the myth of the model
minority in others’ expectations of you
academically?

RQ 5, background
9. During your time in college, if a particular class that
you took or a book that you read influenced your
racial identity, can you describe the class or book?

RQ 5
10. An underlying theme of this research is the
effectiveness of federal surveys in collecting and
reporting the way multiracial and multiethnic people

115

Interview questions Alignment with research questions
actually identify themselves. Federal surveys used in
higher education only allow people to be reported in
one category, although survey respondents are given
the option to select as many race categories that
apply. If a student selects more than one race, they
are not included in any of the race categories they
selected. That means that you and other multiracial
individuals are not included in the Black category
and any other category you select on a federal
survey. Instead, you are placed in the “two or more
races” category. The races that make up that
category are often not reported.
a) Some people would say this practice takes from
students their ability to express their self-identity
and allows the government to determine who is
Black. What are your thoughts of this practice?
b) How would you describe your level of awareness
of the practice?
c) In your view and your experience, what are the
implications of this practice?

RQ 4, identity denial

RQ 5
RQ 5
11. What are your thoughts on the importance of
identifying the components of your racial heritage?

RQ 4, authentic self-identity
12. If you were given the option to write in your racial
and ethnic identity on a survey, rather than check a
box, what would you write?

RQ 4, authentic self-identity
116

Interview questions Alignment with research questions
13. Have you ever felt forced to choose just one identity
on a survey and if so, how did you respond to the
survey question?

RQ 4, identity denial
14. Are there any scenarios in which you wouldn’t
respond to a question about race on a survey? If so,
could you describe them?

RQ 4, identity denial
15. In your family, what kinds of conversations did you
have about race identity?

RQ 5, background
16. What do you think is the most important reason to
collect and report data about race and ethnicity in a
higher education setting?

RQ 5
17. Is there anything that I haven’t asked about this topic
that you think is important to share?

117

Appendix C: Information Sheet for Exempt Research
STUDY TITLE: Enumerating Black Identity in Higher Education
PRINCIPAL INVESTIGATOR: Jocelyn Stewart
FACULTY ADVISOR: Patricia Tobey, Ph.D.
You are invited to participate in a research study. Your participation is voluntary. This document
explains information about this study. You should ask questions about anything that is unclear to
you.
PURPOSE
The purpose of this study is to examine the influence of federally mandated race categories and
methodology on Black identified multiracial and multiethnic students at a public university in the
western United States. Using a mixed methods approach, and a QuantCrit framework, the aim of
the research is to show that the mandated narrow definition of Blackness can lead to an
undercount of Black identified students. We hope to learn how individuals who are excluded
under the federal definition of Blackness (those who are multiracial and multiethnic) make
meaning of race categories and identity in a higher education setting.
You are invited as a possible participant because as a person who is multiracial, you may have
insight on the topic.
PARTICIPANT INVOLVEMENT
If you decide to take part, you will be asked to answer interview questions. The interviews will
be audio/video recorded.
PAYMENT/COMPENSATION FOR PARTICIPATION
You will receive a $25 gift card for your time. You do not have to answer all of the questions in
order to receive the card. The card will be mailed to you after the interview.
118

CONFIDENTIALITY
The members of the research team, and the University of Southern California Institutional
Review Board (IRB) may access the data. The IRB reviews and monitors research studies to
protect the rights and welfare of research subjects.
When the results of the research are published or discussed in conferences, no identifiable
information will be used.
Data will not be labeled with any personal identifying information. The data will be saved
electronically on a local computer and on a cloud-based server.
The researcher will have access to the audio/video recordings and transcript. You may
review/edit the transcript if you choose to do so. The data will be retained for study record
keeping purposes per institutional policy. The data will be retained by the investigator for future
use.
INVESTIGATOR CONTACT INFORMATION
If you have any questions about this study, please contact Jocelyn Stewart, js60330@usc.edu, or
(323) 219-7637 or Patricia Tobey, Ph.D., tobey@usc.edu.
IRB CONTACT INFORMATION
If you have any questions about your rights as a research participant, please contact the
University of Southern California Institutional Review Board at (323) 442-0114 or email
irb@usc.edu.

119

Appendix D: Informed Consent for Research
Study Title: Enumerating Black Students in Higher Education
Principal Investigator: Jocelyn Stewart
Department: Rossier School of Education

INTRODUCTION
We invite you to take part in a research study. Please take as much time as you need to read the
consent form. You may want to discuss it with your family, friends, or your personal doctor. If
you find any of the language difficult to understand, please ask questions. If you decide to
participate, you will be asked to sign this form. A copy of the signed form will be provided to
you for your records.

KEY INFORMATION
The following is a short summary of this study to help you decide whether you should
participate. More detailed information is listed later in this form.

Being in this research study is voluntary–it is your choice.

You are being asked to take part in this study because you identify as Black and multiracial or
multiethnic and are a university or college graduate, and thus belong to the study’s target
population. The purpose of this study is to understand how people who are Black and multiracial
or multiethnic make meaning of federal race and ethnicity categories that undercount Black
identity. Your participation in this study will last for one week. Procedures will include
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answering study questions during a one-on-one interview conducted on Zoom or by phone. After
the interview, you may be contacted again in a few days to clarify a point from the interview or
to answer a follow-up question.

There are risks from participating in this study. The most common risks are discomfort caused by
interview questions. More detailed information about the risks of this study can be found under
the “Risk and Discomfort” section.

You may not receive any direct benefit from taking part in this study. However, your
participation in this study may help us learn more about race and ethnicity categories and how
people make meaning of self-identifying on surveys.

If you decide not to participate in this research, your other choices may include declining and not
participating in this study.

DETAILED INFORMATION
PURPOSE
The purpose of this study is to examine federal race and ethnicity categories and how they may
contribute to an undercount of Black identified students at colleges and universities in the U.S.
We hope to learn how people who are Black and multiracial make meaning of federal race and
ethnicity categories that narrowly define Black identity and exclude multiracial and multiethnic
people. You are invited as a possible participant because you are Black identified and multiracial
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and multiethnic, and as a university or college graduate have had experience with racial and
ethnic categories. About five participants will take part in the study.

PROCEDURES
If you decide to take part, you will answer study questions in a one-on-one interview with the
principal investigator for about two hours. After the interview, you may be contacted again and
asked to answer follow-up questions or clarify a previous question. This follow-up is not
expected to last more than an hour.

RISKS AND DISCOMFORTS
Possible risks and discomforts you could experience during this study include:

Surveys/Questionnaires/Interviews: Some of the questions may make you feel uneasy or
embarrassed. You can choose to skip or stop answering any questions you don’t want to.

Breach of Confidentiality: There is a small risk that people who are not connected with this study
will learn your identity or your personal information.

BENEFITS
There are no direct benefits to you from taking part in this study. However, your participation in
this study may help us learn more about race and ethnicity categories and how people who
multiracial and multiethnic make sense of them.

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PRIVACY/CONFIDENTIALITY
We will keep your records for this study confidential as far as permitted by law. However, if we
are required to do so by law, we will disclose confidential information about you. Efforts will be
made to limit the use and disclosure of your personal information, including research study and
medical records, to people who are required to review this information. We may publish the
information from this study in journals or present it at meetings. If we do, we will not use your
name.

The University of Southern California’s Institutional Review Board (IRB) may review your
records. Your data or specimens will be stored electronically on an external hard drive for two
years. The principal investigator for this study will have access to the data.

Your information or samples that is/are collected as part of this research will not be used or
distributed for future research studies, even if all your identifiers are removed.

ALTERNATIVES
An alternative would be to not participate in this study.

PAYMENTS
A $25 gift card will be provided to subjects who participate in the study’s qualitative interviews
as a thank you gift. The card will be provided at the end of the interview.

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VOLUNTARY PARTICIPATION
It is your choice whether to participate. If you choose to participate, you may change your mind
and leave the study at any time. Refusal to participate or stopping your participation will involve
no penalty or loss of benefits to which you are otherwise entitled. If withdrawal must be gradual
for safety reasons, the study investigator will tell you.

If you stop being in the research, already collected data may not be removed from the study
database. You will be asked whether the investigator can continue to collect data from your
records. If you agree, this data will be handled the same as the research data. No new information
or samples will be collected about you or from you by the study team without your permission.
The study site may still, after your withdrawal, need to report any safety event that you may have
experienced due to your participation to all entities involved in the study. Your personal
information, including any identifiable information, that has already been collected up to the
time of your withdrawal will be kept and used to guarantee the integrity of the study, to
determine the safety effects, and to satisfy any legal or regulatory requirements.

CONTACT INFORMATION
If you have questions, concerns, complaints, or think the research has hurt you, talk to the study
investigator Jocelyn Stewart at (323) 219-7637. This research has been reviewed by the USC
Institutional Review Board (IRB). The IRB is a research review board that reviews and monitors
research studies to protect the rights and welfare of research participants. Contact the IRB if you
have questions about your rights as a research participant or you have complaints about the
research. You may contact the IRB at (323) 442-0114 or by email at irb@usc.edu.

Abstract (if available)

Abstract This study examines the impact of federally mandated race categories and methodology on the enumeration of Black identified students at a public university in the western United States. The purpose of this work is to explore how Black identified individuals who are multiracial or multiethnic make meaning of race categories and to examine the effectiveness of current enumeration practices in reflecting the self-reported identity of individuals in this population. Interviews with Black identified multiracial students provided qualitative data. An analysis of institutional records (secondary data) collected by the university yielded quantitative data. The research led to several key findings: (a) the use of the federally mandated definition of Blackness led to an undercount of Black identified students, (b) applying an all-inclusive whole assignment methodology resulted in a measure of Black identity that was larger than the population reported using the federal methodology and provided an approach that respects and acknowledges the self-identity expressed by participants, (c) the disaggregation of the “two or more races” category allows for a fuller view of the student population, and (d) individuals who have experienced identity denial use race surveys to assert their identity and as a vehicle to talk back to the survey creators. These findings have implications for creating nuanced and useful enumeration methodologies in higher education, methodological approaches that more accurately reflect the way multiracial individuals report and experience identity in the 21st century.

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Asset Metadata

Creator Stewart, Jocelyn Y. (author)

Core Title Enumerating Black identity in higher education

School Rossier School of Education

Degree Doctor of Education

Degree Program Education (Leadership)

Degree Conferral Date 2021-12

Publication Date 12/15/2021

Defense Date 07/13/2021

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag Black identity,black students,census,disaggregated data,enumeration,Ethnicity,identity assertion,identity denial,microaggressions,multiethnic,multiracial,multiracial identity,OAI-PMH Harvest,Race,race categories,race data,surveys

Format application/pdf (imt)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Tobey, Patricia (committee chair), Gomez, Jose (committee member), Maccalla, Nicole (committee member), Patall, Erika (committee member)

Creator Email jocelyny.stewart@gmail.com,js60330@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC18652762

Unique identifier UC18652762

Legacy Identifier etd-StewartJoc-10303

Document Type Dissertation

Format application/pdf (imt)

Rights Stewart, Jocelyn Y.

Type texts

Source 20211221-wayne-usctheses-batch-905-nissen (batch), University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Access Conditions The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the author, as the original true and official version of the work, but does not grant the reader permission to use the work if the desired use is covered by copyright. It is the author, as rights holder, who must provide use permission if such use is covered by copyright. The original signature page accompanying the original submission of the work to the USC Libraries is retained by the USC Libraries and a copy of it may be obtained by authorized requesters contacting the repository e-mail address given.

Repository Name University of Southern California Digital Library

Repository Location USC Digital Library, University of Southern California, University Park Campus MC 2810, 3434 South Grand Avenue, 2nd Floor, Los Angeles, California 90089-2810, USA

Repository Email cisadmin@lib.usc.edu