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Black women in tech: examining experiences in tech industry workplaces

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Black women in tech: examining experiences in tech industry workplaces

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Content Black Women in Tech: Examining Experiences in Tech Industry Workplaces
Shannon McKinley
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 2023

© Copyright by Shannon McKinley 2023

The Committee for Shannon McKinley certifies the approval of this Dissertation
Anthony Maddox
Maria Ott
Monique Datta, Committee Chair
Rossier School of Education
University of Southern California
2023

iv
Abstract
This study examined Black women’s experiences of perceived discrimination in tech industry
workplaces, how women coped with these incidents, and whether organizations’ policies and
procedures helped facilitate discrimination. The qualitative study was guided by Black feminist
theory, which posits that Black women have different experiences that have similar patterns of
oppression due to racism and sexism in the United States. The study participants included
women who identified as Black, African American, or Biracial, and worked in the tech industry
for at least 1 year on either the product side, including software engineers and coders, or the
business side, in positions that help manage the operations of the organization. Three key themes
emerged in the findings of this study: Black women in tech experience behaviors they perceive
as discriminatory; Black women in tech use multiple strategies to cope with workplace
discrimination; and tech business cultures, processes, and middle managers aid workplace
discrimination. The study created three recommendations to address the patterns indicated by the
findings, including an industry supported tech mentorship nonprofit organization, internal talent
incubator labs, and reinvention of middle management training and pipeline. Recommendations
for future research include studies that explore the organizational structures in tech that
perpetuate the dominance of one gender and racial group in tech’s workforce, and the findings
could inform strategies to dismantle those structures. Future research could also examine the
positive aspects of Black women’s experiences in tech and extrapolate common themes that
inform policies and practices that facilitate positive work environments for underrepresented
employees.
Keywords: Black women, tech industry, Black feminist theory, workplaces discrimination

v
Dedication
To my family, friends, and my OCL classmates, thank you for your encouragement,
support, and grace as navigated this monumental and fulfilling journey to further my education.
To the women who raised me – my mom, nana, grandma, and auntie, may she rest in peace,
thank you for always making me believe that I could do anything I set my mind to and reminding
me of that when I doubted it. To the 11 women who shared their experiences with me, thank you
for your courage and persistence.

vi
Acknowledgements
“Do or do not. There is no try” – Yoda
Thank you to my mom, Celeslie Greer for your unconditional and unwavering love and
support, consistent cheerleading, real talk, and the courage to reach for my dreams, especially
when they scare me.
Thank you to my nana Savannah McKinley, my grandma Odessa Parker, and my auntie,
Brenda McKinley, who passed away last year, for always believing in me and assisting and
encouraging me each time I decided to continue my education.
Thank you to the incredible faculty at USC Rossier School of Education, my dissertation
committee members, Dr. Anthony Maddox and Dr. Maria Ott, and my chair, Dr. Monique Datta,
for your patience and support through this process.
Thank you to my former boss, the late Honorable Mervyn Dymally, who always
encouraged me to continue pursuing my education.
Thank you to my fellow OCL Cohort 19 colleagues in the Saturday squad, for the worldbroadening discussions and the courage-building engagement.
Thank you to my favorite classmate, and the heart of our Cohort 19 Saturday crew, Mary
Crannell, for your friendship and inspiring words that kept me going.

vii
Table of Contents
Abstract.......................................................................................................................................... iv
Dedication....................................................................................................................................... v
Acknowledgments.................................................................................................................…… vi
List of Tables ................................................................................................................................. ix
List of Figures................................................................................................................................. x
Chapter One: Introduction to the Study.......................................................................................... 1
Context and Background..................................................................................................... 2
Purpose of the Project and Research Questions.................................................................. 6
Importance of the Study...................................................................................................... 7
Overview and Theoretical Framework and Methodology.................................................. 9
Definition of Terms........................................................................................................... 10
Organization of the Study ................................................................................................. 11
Chapter Two: Review of the Literature ........................................................................................ 13
Racism in the United States.............................................................................................. 13
Gender Discrimination...................................................................................................... 22
Behaviors that Facilitate Discrimination .......................................................................... 30
Workplace Discriminaiton................................................................................................ 39
Black Women in the Workplace ....................................................................................... 43
Theoretical Frameworkd................................................................................................... 49
Conceptual Framework..................................................................................................... 50
Conclusion ........................................................................................................................ 51
Chapter Three: Methodology........................................................................................................ 53
Research Questions........................................................................................................... 53
Overview of Design .......................................................................................................... 53

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Research Setting................................................................................................................ 54
The Researcher.................................................................................................................. 54
Data Sources ..................................................................................................................... 56
Participants........................................................................................................................ 57
Instrumentation ................................................................................................................. 57
Data Collection Procedures............................................................................................... 57
Data Analysis.................................................................................................................... 59
Interview Method.............................................................................................................. 60
Credibility & Trustworthiness .......................................................................................... 61
Ethics................................................................................................................................. 61
Summary........................................................................................................................... 62
Chapter Four: Results or Findings................................................................................................ 63
Participating Stakeholders ................................................................................................ 63
Findings for Research Question 1..................................................................................... 65
Findings for Research Question 2..................................................................................... 70
Findings for Research Question 3..................................................................................... 75
Summary........................................................................................................................... 81
Chapter Five: Discussion .............................................................................................................. 83
Discussion of Findings and Related Literature................................................................. 83
Recommendations for Practice ......................................................................................... 87
Limitations and Delimitations........................................................................................... 92
Future Research ................................................................................................................ 93
Conclusion ........................................................................................................................ 94
References..................................................................................................................................... 96
Appendix A: Interview Protocol................................................................................................. 122

ix
List of Tables
Table 1: Demographic Information of Participaint Stakeholders................................................. 64
Table 2: Interview Protocol Crosswalk....................................................................................... 123

x
List of Figures
Figure 1: Conceptual Framework ................................................................................................. 51

1
Chapter One: Introduction to the Study
American workplaces are not immune from the racism and sexism that pervade society.
Workers of color face institutional barriers and differential treatment at work that mirrors the
systemic racism they encounter outside of the office (Wingfield & Alston, 2014; Yang, 2021). In
workplaces dominated by one race or gender, underrepresented groups face unequal treatment
and suffer adverse outcomes that can impede their physical and mental health and livelihoods
(Okechukwu et al., 2014; Wingfield & Alston, 2014). Research indicates that non-White
individuals experience more discrimination at work than their White peers (Avery et al., 2008;
Daniels & Thorton, 2020). Among these historically marginalized groups, Black people report
more experiences of discrimination than their non-Black peers (Roscigno et al., 2012; Yang,
2021;). Hall and Hamilton-Mason (2012) noted Black and White women face gender inequality
in the workplace, but unlike their White counterparts, Black women must also contend with
racial discrimination. Black women who face racial and gender discrimination at work are more
likely than Black men and White women to face workplace discrimination in predominately
White or male workplaces (Maddox, 2013; Okechukwu et al., 2014; Yang, 2021).
In the technology industry (tech), Black women, who make up approximately 1.7% of the
tech workforce, sit at the intersection of racial and gender discrimination in the workplace
(Sanchez et al., 2019; Zippia Report, 2022). They encounter several systemic barriers from the
beginning of their interest in tech, including lack of access to science, technology, engineering,
and math (STEM) education, as well as fewer entry-level opportunities in the tech job market
and limited career advancement once in the industry (Sanchez et al., 2019). In the tech industry,
where men make up 75% of the workforce, and White people account for 62% of employees,
workplace systems and practices privilege the majority and discriminate against minorities in

2
subtle ways (Wingfield & Alston, 2014; Zippia Report, 2022). In work environments where
inequality goes unaddressed, race and gender work as oppressive factors that limit access to
opportunities and advancement for women of color (Alegria, 2019; Public Citizen Report, 2022;
United Nations Report, 2020). As a result, Black women face experiences of discrimination that
manifest in everyday workplace encounters that are not overt and may not violate the law, yet
have negative consequences that impact their career and health (Del Carmen Triana et al., 2015;
Okechukwu et al., 2014; Van Laer & Janssens, 2011).
This study will focus on the workplace discrimination Black women face in the tech
industry. Examining the forms of discrimination that manifest in tech workplaces will expose the
nuances of how racism is expressed and permeates the professional environments of Black
women in tech. It may also illuminate how tech workplaces, directly and indirectly, create harm
in minority communities by reproducing systemic bias and prejudice in the online products,
services, and technologies they create (ABO Report, 2020; Goins et al., 2022).
Context and Background
Within STEM fields, the tech industry is broad and has no singular definition or formal
classification in the United States (Bureau of Labor Statistics, n.d.). The federal government
classifies most major industries using data from the Bureau of Labor Statistics (BLS) about
businesses' revenue-generating products and services. The North American Industry
Classification System (NAICS), which operates as the federal government's official industry
classification system, uses a coding system to group business entities with similar characteristics
or processes to determine their respective industries. The NAICS has not yet developed a
classification that encompasses all tech occupations (Bureau of Labor Statistics, n.d.).

3
According to a 2014 BLS Report, the government uses a 2010 definition of "high-tech
industries" developed by the Standard Occupational Classification System (SOC). To compile
this definition, SOC used data from STEM occupations and population survey data to determine
the share of workers in each STEM industry occupation. They included employment that ranged
from information technology (IT) to scientists and postsecondary teachers (BLS Report, 2014).
However, the term "high-tech" does not define one specific industry. The term describes a range
of industries, from those that create manufacturing tools to data-generating and collection
professions, that did not exist 10 years ago (EEOC Report, 2016).
The lack of consensus on the definition of the tech industry dates to the late 1990s when
Baldwin and Gellatly (1998) examined the classification of high-tech versus low tech-firms.
They settled on a classification of high-tech that defines businesses that use and create
technology with skilled, competency-based workforces (Baldwin & Gellatly, 1998; EEOC
Report, 2016). Between 1997 and 2012, the number of occupations considered high-tech grew
and evolved from the creation of technology for efficiency to the innovation of tech that changed
people's lives (EEOC Report, 2016). BLS (n.d.) identifies several "high-tech industries" with a
broad range of occupations, including industrial machinery, wireless telecommunication,
architectural design, engineering, scientific research, data processing and hosting, computer
system design, and forestry.
Within the STEM context, technology is considered "disciplines in computer and
information sciences, including those related to operating systems, artificial intelligence,
programming, cryptography, and mobile computing" (BLS Report, 2014, p. 5). According to a
2018 Bureau of Economic Analysis (BEA) report, computers are necessary for the tech industry
because they enable networks, programs, and applications that facilitate digitization. This

4
digitization fuels the digital economy, including computer hardware and software, computerenabled communication, and the sales of physical and digital goods and services (BEA, n.d.). In
the United States, the digital economy produced approximately $3.31 trillion in 2020, an increase
from $3.17 trillion in 2019.
Computer technology sits at the center of the digital economy's power. According to
Flyverbom et al. (2019), computer devices evolved in approximately 50 years, from gigantic
equipment in university labs to personal devices in individual homes. They assert that
technological advancement made computers capable of turning hard copies of information into
"digital bytes" that could be "copied, stored, and circulated in new ways…" (p. 5). The capability
to digitalize information became valuable once the internet was more accessible to the public
because companies gained the ability to extract data about their consumers' activities while
online (Flyverbom et al., 2019; Turow et al., 2015).
The monetization of digital consumer data began in the 1980s and coincided with the rise
of corporations centralizing computer usage in their business models. According to Turow et al.
(2015), the 1981 launch of the first-ever airline frequent flyer program marked the beginning of
tracking the habits of individual consumers. They assert that the introduction of internet browsers
in the 1990s, and the invention of the tracking cookie, mark additional milestones in an almost
40-year transition into the current era of mining and selling users' online data. The digital
fingerprints people leave behind when they use the internet provide vast amounts of data that
tech companies now use to generate revenue and develop new technologies, products, and
services (Flyverbom et al., 2019).
The value of the digitalization and datafication of tech relies on skilled individuals to
build computers, create the software they run on, and develop the networks and platforms that

5
exist within them (Alegria, 2019). The skilled individuals who perform this work, including
software engineers, developers, and programmers, design technologies capable of shaping
people's worldviews and controlling information. They also operate within their respective sociocultural contexts, directly impacting the technology they produce (Algeria, 2019; Rosales &
Svensson, 2021; Wajcman, 2018). Due to inequitable treatment in STEM education and industry
pipelines, women and people of color have fewer opportunities to secure skilled employment in
tech (Charleston et al., 2014; Robnett, 2016). This disparate treatment of underrepresented
groups gives White males an outsized influence over systems created in tech that impact the
broader society (Alegria, 2019; Cook, 2020; Rosales & Svensson, 2021; Wajcman, 2018).
Tech workplaces dominated by one group can replicate societal inequality and create
structures in the form of policies, procedures, and informal practices that perpetuate racism
(Wiecek & Hamilton, 2014; Wingfield & Alston, 2014). These environments foster workplace
discrimination that impacts tech companies by impeding employee performance and reducing the
retention of workers from underrepresented groups. It also preserves the outsized influence of
gender and racially homogenous groups in the tech industry (Lee, 2022; Maddox, 2013; Rosales
& Svensson, 2021; Wajcman, 2018). As one of the most underrepresented groups in the tech
industry, Black women face sexism and racism in STEM fields and are especially vulnerable to
workplace harassment and discrimination (Maddox, 2013; Okechukwu et al., 2014; Sanchez et
al., 2019).
This study focuses on Black women who work for or with the tech companies that are
based in the United States and produce products that collect, distribute, and manage large sets of
data, and develop and use algorithms, artificial intelligence, software, and other internet-based
applications and features as a core function of their business. It is important to this research that

6
the individuals who participate are current or were recent employees in United States based
technology companies to assess experiences of Black American women who work in the
industry. Focusing on experiences that Black women have had in tech workplaces can allow the
qualitative examination of their individual perceptions and assessment of whether discrimination
occurred, and if it did, whether there are patterns in the discriminatory behaviors experienced.
Purpose of the Project and Research Questions
The purpose of this study is to assess the workplace discrimination Black women face in
the tech industry. Research suggests that the tech industry's struggle with employing diverse
groups, including women and people of color, is perpetual and entrenched (Klinger & Svensson,
2021; Rosales & Svensson, 2021; Sung & Choi, 2021). While White women have made gains in
the tech industry over the past decade, Black women have faced an average decline rate of 15%
in tech industry positions since 2014 (Twine, 2018). Examining how Black women experience
workplace discrimination can identify patterns of oppressive behaviors in the tech industry (Del
Carmen Triana, 2015; Yamaguchi & Burge, 2019). This information may also facilitate an
understanding of how prejudice manifests in these spaces and help eliminate disparate treatment
of underrepresented groups who work in the tech industry.
The following research questions guide this study:
Research Questions
1. What workplace behaviors do Black women experience in the tech industry that
they perceive as discriminatory based on their race and gender?
2. How do Black women cope with workplace experiences that they perceive as
adverse or unfair?

7
3. What workplace policies or practices enable discrimination against Black women
in the tech industry?
Importance of the Study
This study is critical because empirical research focused on Black women's experiences
in tech workplaces is limited (Rankin & Thomas, 2020). Many existing studies examine Black
women's experiences in STEM by assessing what they encounter in the STEM education
pipeline (Charleston et al., 2014; Rankin & Thomas, 2020). While these studies do not explicitly
investigate experiences in tech workplaces, many scrutinize underrepresentation and provide
evidence of systemic racial and gender bias unique to Black women in STEM (Charleston et al.,
2014; Johnson et al., 2019). Existing research also highlights the need to study the intersection of
race and gender to gain deeper insight into how Black women experience discrimination in
STEM fields (Rankin & Thomas, 2020; Solomon et al., 2018).
The manifestations of discriminatory behavior and their impact on Black women in tech
are also significant. Workplace discrimination can be blatant and easily identifiable or exist in
more subtle actions (Offerman et al., 2014; Van Laer & Janssens, 2011). Subtle discrimination
adds additional pressure and stress on Black employees, and Black women have an added layer
of mistreatment related to the intersection of their gender and race (Crenshaw, 1991; Hall &
Hamilton-Mason., 2012; Maddox, 2013; Roscigno et al., 2012). These factors can stifle Black
women's careers in tech in several ways, including disparate health outcomes and decreased job
satisfaction (Avery et al., 2008; Hall & Hamilton-Mason, 2012).
The spotlight on the industry's diversity deficit prompted tech executives to invest
company resources in diversity, equity, and inclusion (DEI) programs. Survey data from 46 tech
businesses gathered as part of a joint project between Fast Company, and The Plug in 2021

8
(FCTP Survey, 2021) noted that tech companies spent approximately $3.8 billion in 2020 and
2021 on DEI initiatives and programs. The survey, however, indicated the efforts produced little
progress for Black workers, with the five largest U.S. tech companies increasing the number of
Black employees by less than 1% over 3 years.
Further, according to 2021 data from a Kapor Center brief, the percentage of Black
representation among tech companies increased by one percentage point between 2014 and 2020.
In 2021, the Aspen Institute and Snap Inc. released a report documenting the tech industry's
unsuccessful DEI initiatives (Catalyze Tech Working Group, 2021). The report concedes that
tech's DEI efforts have been insufficient in bringing about systemic change and advocates for
additional action to address employees' experiences of discrimination.
Examining Black women's experiences of discrimination in tech workplaces may provide
insight into the industry's overall bias problem. The socio-cultural context of the industry’s
workforce informs and limits the technology that it produces by perpetuating negative and
harmful stereotypes (Gavet, 2020; Twine, 2018). The consequences are products and services
imbued with the biases and prejudices of those who design them (Daniels, 2015; United Nations
Report, 2020). As a result, the overrepresentation of homogenous groups in the tech workforce
can, directly and indirectly, reinforce systemic racism that disproportionately impacts people of
color (Alegria, 2019; Kapor Center Brief, 2021; Public Citizen Report, 2022; United Nations
Report, 2020).
Inequitable work environments can perpetuate racial and gender barriers when they fail to
address inequities in employees’ access to opportunities and advancement (Alegria, 2019; United
Nations Report, 2020). Data from a 2021 National Academies of Science, Engineering, and
Medicine Report (NASEM Report, 2021) indicate underrepresentation of Black women in tech

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leads to a myriad of problems in the workplace. This research aims to assess these problems and
their relation to the workplace discrimination Black women face in the tech industry. This
examination will deepen the understanding of workplace discrimination and better inform
solutions that can improve tech workplaces for Black women and other groups who face racial
and gender discrimination in the industry.
Overview of Theoretical Framework and Methodology
Black women are not a monolith. However, due to the systemic racism in the United
States, the intersection of Black women's racial and gender social identities shapes their
experiences (Porter et al., 2020; Sanchez, 2019). Black women in the tech industry do not have
the same experiences or react to disparate treatment in the same manner. Their shared
experiences, however, can provide insight into how discrimination manifests in their workplaces
(Collins, 2000). To examine these experiences, Black feminist theory, also termed Black feminist
thought, will guide this research as its theoretical framework (Collins, 2000). As a critical social
theory, Black feminist thought provides a lens through which to expose issues of oppression
from the subjugated persons' perspectives. This theory can also illuminate similarities in Black
women's experiences of discrimination in tech workplaces and provide evidence of how some
navigate the policies, practices, and ideologies that perpetuate them (Collins, 2000; Rattan &
Dweck, 2018).
This qualitative research study will use interviews with Black women employed in the
tech industry to generate data about the discrimination they face in the workplace. This strategy
of inquiry aligns with the Black feminist theory framework because it can investigate Black
women's experiences related to the intersection of their gender and race. These two social
identities can impact Black women in multiple ways and in a manner that differs from non-Black

10
women, Black men, and other people of color (Meyer, 2014; Yang, 2021). Additionally, using
qualitative inquiry to investigate workplace discrimination provides an opportunity to learn about
the expressions of subtle manifestations of workplace discrimination in the tech industry.
Definition of Terms
The following definitions provide clarity for the use throughout this study.
Black women refer to women born and raised in America who are descendants of
enslaved Africans or are at least second-generation immigrants from the continent of Africa
(NASEM Report, 2021). This distinction recognizes the various levels of representation and
"differing experiences” (p. 15).
Black women's standpoint refers to the knowledge shared by Black women in the United
States that results from their experiences due to systemic racism and oppressive societal
structures (Collins, 2000).
Dialectical relationship is the oppositional relationship that links Black women's
oppression and activism through similar experiences (Collins, 2000). The authors also stated:
Dialectical relationships of this sort mean that two parties are opposed and opposite. As
long as Black women's subordination within intersecting oppressions of race, class,
gender, sexuality, and nation persists, Black feminism as an activist response to that
oppression will remain needed (p. 25).
Implicit bias refers to the unconscious and automatic attitudes or stereotypes that affect
individuals' understanding, actions, and decision-making in daily life (Neitzel, 2018).
McCormick-Huhn et al. (2020) describe it as unconscious bias and note:
Unconscious bias results from people's use of cognitive shortcuts (e.g., heuristics;
stereotypes), which, although efficient, can result in systematic bias that affects

11
judgments and decisions about others. This form of bias is important to address because it
can automatically and imperceptibly influence people's decisions, despite their best
intentions (pp. 27-28).
Intersectionality refers to the innumerable ways race and gender interact to shape the
multiple dimensions of Black women's experiences (Crenshaw, 1991). Brah and Phoenix (2004)
also define it as the following:
[T]he concept of intersectionality as signifying the complex, irreducible, varied, and
variable effects which ensue when multiple axis of differentiation-- economic, political,
cultural, psychic, subjective, and experiential--intersect in historically specific contexts.
The concept emphasizes that different dimensions of social life cannot be separated out
into discrete and pure strands (p. 75).
Microaggressions refer to brief verbal, behavioral, or environmental indignities that are
hostile, derogatory, or harmful racial slights and insults toward people of color (Sue et al., 2007).
Racial Discrimination refers to the denial of equal treatment to individuals because of
their group membership in a social category of racial/ethnic background (Del Carmen Tiana et
al., 2015).
Organization of the Study
The dissertation follows a traditional five-chapter model. Chapter One describes the
problem of practice, explains the study's purpose, uses the theoretical framework to examine the
problem, and briefly describes the methodology used to gather and analyze data. Chapter Two
reviews the literature relevant to Black women and workplace discrimination. This literature
review includes Black feminist theory, which will frame this study, the tech industry and its
history related to gender and racial diversity, and different forms of workplace discrimination.

12
Chapter Three details the research methodology, including the structure of the qualitative study,
details about the participant sample, and the interview protocol used to gather data. Chapter Four
presents the findings of the qualitative study, while Chapter Five provides recommendations
proposed to address the findings discussed in the preceding chapter.

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Chapter Two: Literature Review
To examine the racial discrimination Black women experience in tech industry
workplaces, it is vital to define and understand racism and racial discrimination. It is also
necessary to explore how they manifest in the workplace and distinguish racial discrimination
from other forms of work stress. This literature review aims to present research that will help to
examine Black women's experiences of workplace discrimination in the tech industry. Exploring
discrimination in the United States and the manifestation of discriminatory behaviors in the
workplace will provide insight into how marginalized groups navigate disparate treatment. This
information will also provide context for Black women's experiences because they have
intersecting marginalized identities that create unique forms of inequity (Crenshaw, 1999). This
literature review will also present literature on Black feminist theory, which will serve as the
framework to study Black women's perceptions and responses to racial discrimination in tech
workplaces and to understand how they navigate these environments and as they pursue careers
in the tech industry.
Racism in the United States
Race is a social construct that is used in the United States to justify centuries of injustice
and violence, including the enslavement of Africans and the removal of Indigenous people from
their land (Ray & Mahmoudi, 2022; Smedley & Smedley, 2005;). Through the construction of a
racial hierarchy, the colonial and eventual United States governments allowed racism, the
differential treatment of individuals based on their characteristics, to be used as a tool to maintain
systems of oppression that continue to exist in our society today (Clark et al., 1999; Feagin &
McNair, 2004). Racism is not simply the manifestation of an individual's prejudiced beliefs,
discriminatory behavior, or bias (Ray & Mahmoudi, 2022). It is the multi-level, constant barrage

14
of obstacles sewn into the fabric of our society, and impacts almost every facet of the lives of
people of color, including whether they survive birth, where they live, and where they go to
school and their employment options and opportunities (Abraham et al., 2021).
Racism has multiple levels, including interpersonal, institutional, and structural (AdkinsJackson & Rodriguez, 2022). According to the National Museum of African American History
and Culture (NMAAHC), interpersonal racism includes racial slurs, biases, or actions between
people. The site notes that institutional racism occurs at the organizational level, where
treatment, policies, and practices based on race lead to inequitable outcomes for individuals of
color. Lastly, the NMAAHC notes that structural racism is the broader system that disadvantages
historically marginalized groups across institutions and society and enables White privilege.
Braverman et al. (2022) asserted that some literature uses structural and systemic racism
interchangeably, but they define the two terms separately. Reviewing relevant literature will
foster an understanding of the different levels of racism and how they impact the lives of people
of color in the United States.
Systemic and Structural Racism
The broadest and most entrenched forms of racism operate at a societal level and
encompass laws, policies, and practices that act across institutions. Braverman et al. (2022)
argued that structural and systemic racism work on a macro-level but have critical differences.
The researchers asserted that systemic racism involves whole systems, such as education legal,
economic, or political systems, and include the institutions that maintain them. They stated that
structural racism focuses on the role of these entities, the laws, institutional practices, and
entrenched norms that make up these systems. These authors noted that systemic racism

15
incorporates structural racism; researchers may use them interchangeably or use both terms to
highlight their interdependence.
Systemic racism is foundational to the United States, permeates its most critical
institutions, and privileges White people to the detriment of people of color (Feagin & Elias,
2013; Feagin & McNair, 2004). It is a tool of oppression that maintains racial hierarchy and
marginalizes those not in the majority (Lukachko et al., 2014). In one of the first studies that
tried to measure belief in systemic racism, Silver et al. (2022) examined participants' attitudes
toward Black Lives Matter (BLM) and the police, using data from a national survey of 1,125
American adults who were asked about their "moral intuitions" (p. 344), meaning one's core
moral belief system, and a belief in systemic racism. In addition to their other findings related to
support for BLM, the authors found a relationship between a moral belief in not hurting or
mistreating people and a belief that police brutality was related to systemic racism. In an
examination of Black workers' motivation for seeking self-employment, Bento and Brown
(2021) measured "racial capital" (p. 23) operationalized as a belief in the significance of systemic
racism and whether it predicts their status as entrepreneurs. Data from 2,294 participants in a
nationally representative survey suggest that racial capital is positively associated with Black
self-employment. The authors noted that this belief in systemic racism may influence Black
workers' decisions to work for themselves.
In studying structural racism in the health system, Agénor et al. (2021) used "policy
surveillance" (p. 430), a method to monitor laws and policies over time. Using ten criteria,
including voting rights laws, racial profiling laws, minimum wage, and fair-housing laws, the
authors identified 843 state laws connected to structural racism. The authors noted that these
laws were in all 50 states and either actively discriminated against historically marginalized

16
groups of color or failed to protect these groups from discrimination. In an investigation of media
use in perpetuating structural racism, Rosino and Hughey (2021) conducted a content analysis of
the United States newspaper content from 1983-2014 related to the War on Drugs (WOD). They
asserted that the WOD was an example of structural racism that disproportionally impacted
communities of color and used politics and state and federal laws to create an unjust path in the
criminal justice system. The authors' examination included 394 op-eds, articles, and letters to the
editor and 3,145 comments from 24 online news websites. Their findings indicated that the
media's framing of the WOD helped scaffold the political and societal justification for the laws
and resulting punitive measures that devastated Black and Brown communities throughout the
country.
Structural and systemic racism have also been explored in health research because
evidence has suggested that a relationship exists between racism and disparate health outcomes
in Black Americans (Abraham et al., 2021). Lukachko et al. (2014) examined the relationship
between structural racism and rates of myocardial infarction, another term for a heart attack,
among Black Americans. Using data from the National Epidemiologic Survey on AlcoholRelated Conditions, the study sampled 32,752 non-Hispanic Black and non-Hispanic White
participants and measured structural racism on political participation, employment, job status,
education attainment, and judicial treatment. Their data indicated that structural racism, as
operationalized in their study, is positively associated with myocardial infarction. They
suggested that high levels of structural racism in political participation, employment, and judicial
treatment were generally associated with higher heart attack risk among Black Americans.
Racism that exists at a societal level and within and across institutions can also manifest
in individuals’ actions and behaviors that put specific targets, such as groups that have been

17
categorized as a specific race and have been historically marginalized, at a disadvantage. These
categories are socially constructed, but have practical implications that can shape people’s lives
and limit their opportunities This race-based differential treatment, or racial discrimination, is
discussed in the next section.
Racial Discrimination
Racism and racial discrimination are important to understand because they impact the
daily lives of historically underrepresented groups in different ways. Researchers often use
racism and racial discrimination synonymously in discrimination literature, but the two terms are
distinct because race is a social creation based on differences that have no scientific meaning
(Berger & Sarnyai, 2015; Smedley & Smedley, 2005). As a social construct, race became a tool
to rationalize slavery in the United States and continues to facilitate inequity and perpetuate
oppression for historically marginalized groups (Smedley & Smedley, 2005). Based on the social
construction of race, racism encompasses more than just ingroup preferences; it is a
comprehensive system of "beliefs, attitudes, institutional arrangements, and acts that tend to
denigrate individuals or groups because of phenotypic characteristics or ethnic group affiliation"
(Clark et al., 1999, p. 805). The comprehensiveness of racism dictates that racial discrimination
is a derivative of it rather than its synonym because the latter requires an individual or institution
to withhold, regardless of intention, equal treatment to individuals or groups based on their
phenotypic differences (Brondolo et al., 2005; Clark et al., 1999; Keating et al., 2021).
Racial discrimination is the behavior and action racism facilitates and can be subtle or
overt based on phenotypic or cultural characteristics (Clark et al., 1999; Rucker et al., 2014).
Overt acts of racial discrimination are intentional and targeted, such as racial slurs, physical
violence, or threats, while subtle racial discrimination is indirect and can include exclusion,

18
differential treatment, or harassment (Brandolo et al., 2005; Greenwood et al., 2017; Jones et al.,
2016). Individuals and institutions can facilitate racial discrimination through actions or
organizational policies that treat groups differently based on their physical characteristics or
ethnicity (Lui, 2020). While overt discrimination is more likely to be illegal, subtle
discrimination is difficult to identify or assess, more likely to occur, and can inflict repeated
harm on its targets (Jones et al., 2016).
Subtle discrimination's elusiveness underlies the reasons underrepresented groups
experience it regularly (Harnois, 2022; Operario & Fiske, 2001). Blendon and Casey (2019)
examined the experiences of discrimination among Black people, Latinos, Native Americans,
Asian Americans, and members of the LGBTQ+ community. Using data from a national
telephone survey of 3453 adults in the United States, they calculated the percentage of adults
who reported discrimination in health care and several other areas, including housing, education,
and the workplace. Their findings suggested that racial and ethnic discrimination is prevalent in
the United States, as is discrimination based on gender and sexual orientation.
There have been conflicting research findings about the prevalence of racial
discrimination in the United States. In a study about perceived experiences of racial
discrimination, Boutwell et al. (2017) used data derived from one question on the National
Longitudinal Study of Adolescent to Adult Health to assess self-reports of perceived
discrimination from individuals from underrepresented groups. Their findings suggested that
75% of the 14,793 respondents, across all racial categories, including Black, Latino, and Asian
American, never or rarely experienced discrimination in the United States. However, the authors
noted that using one measure limited their study and suggested that a multi-measure instrument
would be more helpful. In response to this research, Lee et al. (2019) conducted two studies that

19
replicated the Boutwell et al. (2017) study, using data from the Pew Research Center, that asked
a sample of 3,716 respondents about their personal experiences of discrimination. Their findings
indicated that approximately 50%-75% of Black, Latino, and Asian American respondents
reported discriminatory treatment.
In a study that focused on Black adults' experiences of discrimination in the United
States, Bleich et al. (2019) used data from a nationally representative, probability-based
telephone survey to compare reports of discrimination across several domains, including health
care. The sample included 802 non-Hispanic Black respondents and 902 non-Hispanic White
respondents. The authors' data indicated that Black individuals reported experiencing racial
discrimination at significantly higher rates, across gender and socioeconomic status, than their
White counterparts. Earle and Hodson (2020) surveyed 5,922 Black and White adults in the
United States. Their findings suggested that the majority of both groups believe that Black
people experience more racial discrimination than White people. Their data noted that some
White people believe they face discrimination more than other marginalized groups. The authors
argued that these individuals, however, perceived the current oppressive social structure as
legitimate and see any gains in equality for marginalized groups as a threat to their position in
society (Wilkins & Kaiser, 2014).
Black Americans also experience racial discrimination on a personal level and as a group
(Earl & Hodson, 2020). Hagiwara et al. (2016) examined the differences in mental and physical
health impacts of personal-level and group-level racial discrimination. In an analysis of survey
data from a broader study, they evaluated the responses of 120 participants who self-identified as
Black or African American. The authors' data suggested that those who reported more perceived
group-level discrimination had better health outcomes than those who reported more personal-

20
level perceived discrimination. However, they noted that the salience of one's identity acted as a
mitigating factor with experiences of group-level discrimination because those who do not derive
meaning from their racial group are less likely perceive harm from group-level racial
discrimination (Operario & Fiske, 2001).
Individuals who strongly identify with their ethnic or racial identity report more
experiences of discrimination and respond to those experiences more strongly than those in the
majority group (Operario & Fiske, 2001; Rucker et al., 2014). Ruggiero and Taylor (1995)
conducted a mixed-method study with 240 female university students to examine how
disadvantaged groups deal with perceived discrimination. Their data indicated that
underrepresented groups tend to minimize their perception of discrimination and internalize
mistreatment. The authors noted that this can perpetuate discrimination by validating the
majority group' prejudicial beliefs and behaviors. Data from Rucker et al. (2014) suggested that
strong racial or ethnic identity intensifies the response to discrimination and suggests that the
race of the perpetrator of the discriminatory behavior also impacts the intensity of the victim's
response. As part of the reaction to racial discrimination, individuals experience a stress response
that differs from the pressure of other daily life events (Allen et al., 2019; Landrine & Klanoff,
1996). In their examination of racial discrimination, Landrine and Klanoff (1996) conceptualized
the different forms it takes as a "racist event" (p. 145). They asserted, for example, that a racist
event happens to a Black American because that individual is Black. Overtime, these experiences
increase the stress of individuals in underrepresented groups, leading to a multitude of physical,
physiological, and mental health problems, and can interfere with cognitive processes (Allen et
al., 2019; Bleich et al., 2019; Clark et al., 1999; Keating et al., 2021).

21
For most Black Americans, racial discrimination is part of their daily lives (Joseph et al.,
2021; Mouzon et al., 2017). These experiences trigger various interpretations and responses that
require coping strategies that help manage and reduce potential harm to individuals’ mental and
physical health (Allen et al., 2019; Fix et al., 2020; Harnois, 2022; Keating et al., 2021; Operario
& Fiske, 2001). Coping strategies, which are conscious efforts to manage one's emotions,
thoughts, or behaviors, help mediate the impacts of racial discrimination and can focus
individuals' thinking on solution-oriented ways to deal with their responses (Seaton et al., 2014;
Wilson & Gentzler, 2021). Coping strategies can also depend on the salience of individuals'
beliefs about being Black and their membership as part of the broader Black community (Seaton
et al., 2014). This study suggested that a stronger connection to racial identity increased the
participants' ability to use coping avoidance strategies to mitigate the impact of racial
discrimination on their mental health.
Black Americans' use of effective coping strategies to manage the impact of racial
discrimination is critical because the experiences can reduce cognitive functioning over time
(Joseph et al., 2021; Keating et al., 2021; Mouzon et al., 2017). Racial discrimination can also
lead to adverse health outcomes for Black women due to accumulated stress and post-traumatic
stress (Allen et al., 2019; Mekawi et al., 2022). Data from a longitudinal study by Zahodne et al.
(2020) indicated a relationship between daily experiences of racial discrimination and depression
and vascular disease. Their analyses of a subset of 3,304 adult participants over the age of 51
from a more extensive health survey found evidence that racial discrimination can have impacts
2 to 4 years after the initial discriminatory incident.
Research acknowledges that all people of color in the United States face racial
discrimination. However, the data suggests that Black Americans are exposed to it more than any

22
other group. This exposure can lead to several outcomes that can impact their lives, including
disparate economic and health outcomes and struggles with their personal and group identities.
This discrimination, however, is not limited to race. Differential treatment based on gender can
also disadvantage individuals, including those already subject to racial discrimination. There are
a few ways gender based discrimination impact targets. Three forms that exist in the United
States are discussed in the next section.
Gender Discrimination
Discrimination based on one's gender has been an obstacle that limits women across
domains, including education and the workforce. Gender discrimination is rooted in beliefs and
stereotypes about what being born as one sex instead of the other should mean (Bobbitt-Zeher,
2011). In examining stereotypes used to discriminate against women, Burgess and Borgida
(1999) distinguished between two types, labeling beliefs about traits women have as descriptive
stereotypes and stereotypes about beliefs and traits women should have as prescriptive
stereotypes. In the United States, most women, across racial and ethnic identities and
socioeconomic status, experience gender discrimination in multiple areas of their lives, including
health care, higher education, and the workplace (SteelFisher et al., 2019). Such discrimination
can begin in childhood, continue into adulthood, and have several adverse mental and physical
health impacts, limiting employment opportunities and socioeconomic gain through pay inequity
(Rogers et al., 2022; SteelFisher et al., 2019).
Gender discrimination can be expressed in several ways, including differential treatment,
assumptions about how women should behave and institutionalized disadvantages that limit
women’s opportunities. In the United States, the increase in the number of women in the
population has not translated into an increase in societal or institutional power. As a result,

23
women remain vulnerable to gender discrimination. The next section provides research about
sexism, and the actions and behaviors that lead to women being treated differently and put at a
disadvantage.
Sexism
Sexism can come in multiple forms and lead to adverse experiences for its targets. Glick
and Fiske (1996) asserted that gender discrimination stems from different types of sexism. They
noted that sexism is a form of prejudice that can be hostile or benevolent. The former can mean
openly adversarial or derogatory behavior or the belief that women should be subservient to men.
The latter term defined sexism as beliefs stemming from individuals' paternalistic viewpoint that
sees women as meek and in need of men’s protection.
Connelly and Heesacker (2012) examined benevolent sexism to understand why some
men and women find it acceptable despite its perpetuation of structural inequality. They
conducted online survey research of 385 undergraduate students, including 247 women and 111
men, at a public university in the United States. Their data suggested that both women and men
believe that benevolent sexism offers some benefits and that the current state of gender hierarchy
is fair. The researchers noted that their findings reinforce the dangerous nature of benevolent
sexism and emphasize the need for interventions to reduce its prevalence. In research measuring
sexism across age and time, Hammond et al. (2018) used New Zealand's annual panel survey,
Attitudes and Values Study, to collect six waves of data from the country's adults. With a sample
of 10,398, 62.5% of whom were women, the researchers used a 10-item survey to measure
benevolent and hostile sexism. Their data suggested that hostile and benevolent sexism was the
strongest in late adolescence and decreased as the participants aged. Their research also indicated
that women's hostile and benevolent sexism and men's hostile sexism fluctuated over time, with

24
all three higher in early adulthood, lower in middle adulthood, and high in late adulthood.
However, they noted that over time, younger cohorts of participants showed a decline in
women's hostile and benevolent sexism and men's hostile sexism during young adulthood, which
did not increase as they aged. Men's benevolent sexism, in contrast, was stable over time and
increased with age.
Wang and Dovidio (2017) examined how the salience of women's gender identity
impacts how they perceive and confront gender discrimination. They randomly assigned 114
women in the United States to groups that were either primed to focus on their identity or primed
to focus on their gender identity. The participants engaged online with a man who expressed
sexist views and responded to the man in writing. Three different tools measured the women's
responses, including self-reporting, where the participants rated their responses to the sexist
comment, and coded comments, where independent judges who were unaware of the conditions
of the experiment rated the responses. A third measurement asked participants to rate the extent
to which they found the comment sexist. The researcher's data indicated that women with salient
gender identities perceived subtle gender discriminatory cues and were more likely to confront
the perpetrator of said discrimination.
Research by Kuchynka et al. (2018) also explored identity salience and its impact on
perceived sexism. They examined the association between perceived sexism and women's
outcomes in science, technology, engineering, and mathematics (STEM) education courses
among university students. Their research indicated that women who identified more with their
STEM identity than their gender identity did not associate perceived sexism with their STEM
course outcomes. They also noted that women experienced benevolent sexism in their STEM

25
courses, while men supported more benevolent sexism ideology, including the idea that women
needed to be protected.
Understanding how sexism manifests and is perceived is critical because it can impact
women in the workplace. For example, King et al. (2012) examined the potential gender
differences in how managers assign challenging work. The researchers conducted a series of
studies that assessed managers' levels of sexism in different workplaces and its impact on women
employees. They proposed that benevolent sexism, or the idea that women need to be protected,
may cause supervisors to believe they are assisting the women they supervise by assigning more
challenging work to male employees. Their data suggested that male supervisors assessed to
have high benevolent sexism gave men more challenging work assignments than women
employees.
Dray and Sabat (2020) conducted two studies to examine how confrontations of
workplace sexism commonly differ and the workplace implications of those differences. With an
overall sample of 1068 participants across three experiments, the researchers' data indicated that
the sex of the perpetrator and the location of the confrontation, in addition to other factors,
impact confrontations about sexism. Their data also suggested that when bystanders confront
sexism, targets believe the confrontation means others disagree with the perpetrator of sexism.
When workplace sexism goes unaddressed by others, their data indicated that the targets infer
that others agree with the perpetrator's sexism.
The research on sexism suggests that some forms seem to be acceptable to men and
women, despite its negative impact. While one’s sexist attitudes or belief in benevolent, nonhostile forms of sexism can change over time, the strength of a woman’s identification with her
gender is a key component to navigating this gender-based discrimination. Also important are

26
how beliefs about women contribute to the ways in which they are treated. This idea is explored
in the next section that examines gender stereotypes research.
Gender Stereotypes
Gender stereotypes harm those who have been historically marginalized and limit their
employment opportunities. Research defines stereotypes as ''beliefs about the characteristics,
attributes, and behaviors of members of certain groups…and theories about how and why certain
attributes go together" (Hilton & Von Hippel, 1996, p. 240). In addition, how men and women
view their respective identities and the identities of their social group influence gender
stereotypes (Piatek-Jimenez et al., 2018). These internalized beliefs impact the characteristics
that are genderized as male or female in our society, which can impact how individuals view
others' capabilities and how they are treated in various settings, including the workplace
(Bobbitt-Zeher, 2011). Such gender-based beliefs can become social constraints for their targets.
For example, Carli et al. (2016) suggested that genderized stereotypes about women can limit
their opportunities in fields of study and employment, including STEM.
Eaton et al. (2020) examined how the intersection of gender and racial stereotypes
impacted STEM professors' evaluations of post-doctoral employment candidates. The authors
collected survey data from a sample of 251 biology and physics professors from eight public
research universities in the United States, who read one of eight curriculum vitaes (CV) that were
identical except for the name. The names on each CV were changed to manipulate race and
gender, but the other content remained constant. The Eaton et al. (2020) findings suggested that
male candidates were rated higher by both physics and biology faculty. In addition, they noted
that physics faculty rated male candidates as more competent than female candidates.

27
The effects of gender stereotypes, however, are not limited to hiring decisions. In two
studies that sampled 184 undergraduate students in the United Kingdom, Hausmann (2014)
investigated whether gender stereotypes affected cognitive sex differences in STEM and art
students. The data suggested that prompting students' academic disciplines activated gender
stereotypes. Hausmann also noted that this activation negatively impacted women's cognitive test
performance, regardless of the prompting of their academic or gender identity.
The implicit bias that can accompany gender stereotypes may also impact performance.
Smeding (2012) used the Implicit Association Test to study the strength of implicit gender-math
stereotypes among students studying engineering and their peers pursuing an education in the
humanities. With a sample of 256 students across two experiments, the researcher's data
suggested that female engineering students held weaker implicit gender-math and genderreasoning stereotypes than female humanities, male engineering, and male humanities students.
Additionally, the data indicated that implicit stereotyping was more negatively related to math
grades for female humanities students than for the three other groups. A study about implicit bias
among STEM students by Smyth and Nosek (2015) yielded similar results. Their data indicated
that men had more implicit bias related to the idea that men belong in science, while women held
less implicitly biased beliefs. Their research also suggested that women outside of STEM had
stronger implicitly stereotypical beliefs about women's abilities in STEM than women who work
in STEM.
The subtle, unconscious priming of implicit gender stereotyping can also impact the
targets' implicit reactions. Van Breen et al. (2018) conducted two studies to examine how women
resist implicit gender stereotypes. Their data indicated that women who strongly identified with
feminists but not with women as a group resisted the subliminal, or unconscious, stereotypes

28
through implicit in-group bias. They noted that individuals in marginalized groups may develop
unconscious "psychological resistance mechanisms" (p. 1659) that counter stereotypes,
regardless of whether they are consciously aware of them.
Data indicate that gender stereotypes create limiting beliefs about women’s capabilities.
As a result, women can experience unfair treatment in several domains, including education and
STEM fields. Gender stereotypes can also limit women’s economic opportunities. The next
section discusses research related to the way women’s pay can be limited by gendered beliefs
and sexism.
Gender Pay Gap
One of the many tangible manifestations and unjust consequences of gender
discrimination is the gender pay gap. Gender-based disparities in wages disproportionately
depressed the economic well-being of women in the workforce. Research has examined various
factors that may contribute to differences in pay that women and men receive, including but not
limited to differences in productivity, taking leave from the workforce for motherhood, gender
discrimination, and choice of occupation (Williams, 2022). However, data has suggested that pay
differentials cannot be fully explained by factors such as college education and experience
because women have exceeded men in the former and are narrowing the gap with men in the
latter (Rotman & Mandel, 2023; Williams, 2022).
Additionally, research indicates that men receive a higher financial return on their
education, benefit from more cumulative work experience than women, and the returns on
experience and education increase over time for men but not women (Rotman & Mandel, 2023;
Smith & Waite, 2019). There are also gaps between part-time and full-time workers. In studying
the wage gap, Meara et al. (2020) used the monthly United States Current Population Survey

29
(CPS) to investigate the gender wage gap in the United States. They used two cross-section
samples of the CPS, the first for October 2011 to March 2012, with a sample of 77,097
individuals, and the second for October 2017 to March 2018, with a sample of 76,308. In each
sample, 51.6% of the participants were women, and 48.4% were men. Their results suggested a
gender pay gap of about 15% and a 27% gap in hourly wages between part-time and full-time
workers. Their results also showed a gender pay gap for unionized workers that was higher than
for non-unionized workers.
When examining the gender pay gap in STEM fields, research suggests that the disparity
is narrowing but is still in double digits and largely unexplained (Courey & Heywood, 2018). In
studying the pay gap in the chemistry field, Broyles (2009) used data from the American
Chemical Society 2000 census of its membership, for a sample of 22,081 individuals who work
full time as chemists, ages 21-69, with a mean age of 44. Of the sample, 78% were men and 22%
were women, 86% were White, and 14% were people of color. The data analysis indicated that
differences in education and work experience explained 83% of the gender gap in salary and
discrimination, while unexamined factors explained 17%. Broyles also noted that women were
likelier to hold lower-paying positions in chemistry professions which may allude to employers'
gender bias.
In the broader STEM fields, there is evidence that the gender pay gap persists in
industries where women have more representation and levels of experience and education
between men and women are comparable (Michelmore & Sassler, 2016). Sterling et al. (2020)
indicated that the gender pay gap for women and men with degrees begins upon entry into the
workforce. They also noted that women tend to have lower self-efficacy in the STEM field than
men, which impacts women's earning potential during the early stages of their careers. In

30
addition, the authors suggested that the gendered beliefs of the organization also compound these
factors.
Gender-based discrimination can be thoughts, beliefs, feelings, actions, and behaviors
that lead to disparate treatment of a specific group of individuals. In the United States, gender
discrimination has historically undermined the efforts of women to receive equal treatment and
protection under the law. Research suggests that sexism, gender stereotypes and the gender pay
gap work in concert to perpetuate a power dynamic that limits women’s economic and
professional opportunities. However, the gender pay gap, blatant forms of sexism, and expressed
gender stereotypes are not the only ways discrimination exists in the United States. The next
section examines research related to the expression of discrimination and the impacts it has on
women and other historically marginalized groups.
Behaviors that Facilitate Discrimination
When discrimination transfers from thoughts, feelings, and beliefs into action,
individuals' behavior can result in disparate treatment of those in historically marginalized
groups, including people of color and women. The attitudes that inform this behavior can be
implicit, where the individual is unaware of their underlying beliefs (Greenwald & Banaji, 1995).
They can also be explicit, where the person can articulate their feelings (Dovidio et al., 2002).
Individuals' implicit and explicit beliefs can be consistent or inconsistent, where one does not
consciously report underlying discriminatory beliefs, but their actions are unconsciously guided
by them (Greenwald & Banaji, 1995). Such unconscious bias can perpetuate stereotypes, limit
performance expectations, and facilitate biased behaviors that impact others in society and the
workplace (McCormick-Huhn et al., 2020; Melamed et al., 2019).
Incivility

31
Incivility can be a subtle form of discrimination that has a cumulative impact on those in
underrepresented groups. Workplace incivility describes subtle and disrespectful behavior that
demonstrates a disregard for others in the workplace, with no specific intent to harm (Andersson
& Pearson, 1999). The ambiguity of the person's intent to harm is a critical component of
incivility. While incivility is not a characteristic of one group, research suggests that women and
people of color are more likely to be targets of this behavior, and Black women are the most
targeted (Cortina et al., 2013; Ozturk & Berber, 2022). In a study examining cyber and
interpersonal incivility and racial discrimination, Daniels and Thorton (2020) used survey
research to sample 408 adults with full-time employment experiences. Their data suggested that
people of color experience more cyber incivility in email communication than their White peers.
Evidence also indicated that racial discrimination was indirectly expressed through cyber
incivility more than in-person interactions.
Targets of workplace incivility and their organizations bear the consequences of such
behavior. For the targets of workplace incivility, their experiences can result in psychological
distress, reduce their job satisfaction, and lead to employment separation (He et al., 2021; Holm
et al., 2022; Oyet et al., 2020). Experiencing incivility can also lead to several intense emotions,
including anger, fear, and sadness, as targets process individuals' behavior towards them and
determine how to react and the potential consequences of their reaction (Porath & Pearson,
2012). How one reacts to incivility can impact one's well-being. In a study that examined the
relationship between workplace incivility and rumination, defined as "repetitive thinking about
negative feelings and events" (He et al., 2021, p. 298), the researchers investigated the mental
cost targets of incivility must bear. They noted that the more targets of incivility repeatedly
thought about their negative experiences, the more detrimental the outcomes, including job

32
burnout and family conflict. Additionally, the researchers' data indicated that organizational
support for employees who experience incivility reduced the impact of rumination on targets'
well-being.
In addition to impacting employees' well-being, workplace incivility can interfere with
performance. Saleem et al. (2022) examined workplace incivility's impact on performance and
whether an employee's trust in supervisors was a mitigating factor. Their survey data from 252
telecommunication company employees indicated that incivility harms employee performance
by distracting them from work tasks. The data also suggested however, that supervisor
intervention on behalf of the target of incivility can help increase their subordinates' level of
performance.
Khan et al. (2020) provided evidence about how incivility can impact the organization
when employees who experience it react by engaging in "deviant silence" (p. 175), defined as
withholding relevant information at work to harm a colleague, supervisor, or the organization. In
a longitudinal study with a sample of 271, the researchers' survey data indicated a positive
correlation between gender and deviant silence. Specifically, the data suggested that men who
experienced workplace incivility were likelier than women to react with deviant silence. They
also noted that employees tend to reciprocate deviant silence with similar behavior, and their
research suggests that this can hasten the deterioration of workplace communication and
relationships.
Incivility in the workplace can negatively impact the individuals who experience it and
the organization where the behavior occurs. Such incidents can induce coping strategies that
undermine employees’ contributions to the workplace, such as keeping important information
from coworkers or supervisors. It can also cause emotional stress on the targets of uncivil

33
behavior. Incivility, however, is not the only treatment that can lead to disparate outcomes in the
workplace. In the next section, research about exclusion and ostracism, two additional behaviors
that can lead to workplace discrimination, is examined.
Exclusion and Ostracism
Workplace exclusion and ostracism, terms used interchangeably or to define one another
in the research, can undermine workers' performance and isolate targeted employees. Howard et
al. (2020) defined workplace ostracism as a combination of an individual's perception that they
are purposefully being left out or ignored by others at work or when an individual or a group
does not actively engage certain employees in social situations where their colleagues are
participating. They used a meta-analysis of 93 empirical sources that analyzed workplace
ostracism to investigate the antecedents and outcomes of workplace ostracism. Their data
suggested that several antecedents, including gender, education, extraversion, agreeableness,
neuroticism, and conscientiousness, influenced whether an individual experienced ostracism in
the workplace. The researchers' data also indicated a strong relationship between workplace
ostracism, deviant silence, and feelings of belonging. However, Howard et al. noted a correlation
between ostracism at work and other outcomes, including emotional exhaustion and depression
reduced job satisfaction and commitment, and increased employee turnover.
The relationship between workplace exclusion and job performance is critical to
understand because they can occur in employees' daily interpersonal interactions, impact
employees' well-being, and undermine their ability to contribute to the success of their respective
organizations (Kim, 2011). Employees who perceive that they are being ostracized or excluded
at work are less innovative and engage in self-protective strategies that can lead them to avoid
colleagues and engage in defensive silence, where they do not communicate work-related

34
information, raise issues, or share ideas (Ayub et al., 2021; Samma et al., 2020). Research also
indicated that workplace ostracism reduces employees’ physical strength and emotional energy,
which can interfere with their performance on work-related tasks (Xia et al., 2019). However,
employees' self-efficacy, or the confidence in their ability to do their job and how immersed or
attached employees are to their work, can mitigate the impact of workplace ostracism (De Clerq
et al., 2019; Lyu & Zhu, 2019).
Gender can also play a role in workplace exclusion and ostracism. Cyra et al.’s (2021)
research examined how women's levels of social inclusion shape their experiences in
workplaces. Their survey data, from 1,247 employees in STEM roles at nine organizations,
indicated that men with implicit bias against women in STEM reported fewer social interactions
with their women colleagues. The reduced level of interaction can be detrimental for women in
STEM because, as the researchers noted, cross-gender social inclusion at work benefitted women
in STEM roles. Data from Cyra et al. suggested that the women whom male colleagues included
experienced increased workplace engagement, greater sense of self-efficacy, and increased
satisfaction with their career trajectory.
In interactions where employees' perception of workplace ostracism often dictates their
workplace outcomes, understanding the difference between perception, actions, and intent is
valuable. Yang and Treadway (2018) noted that workplace ostracism can be ambiguous. Hence,
their research examined the accuracy of perceived ostracism, the resulting outcome for the
targets, and factors that may mitigate those outcomes. Their data from survey research on a
sample of 156 employees of a manufacturing plant in China, 58% of whom were men, suggested
a weak relationship exists between actual and perceived workplace ostracism. In addition, their
findings indicated that employees' level of a need to belong and their political skill, meaning

35
their ability to adapt confidently to people and environmental stressors, are mitigating factors in
their perception of and reaction to ostracizing behaviors. Yand and Treadway's data suggested
that employees with a strong need to belong and low political skills perceive more ostracizing
behaviors in the workplace than those with a weaker need to belong.
Exclusion or ostracism of certain employees in the workplace can interfere with an
organization’s operations and harm the individual who experiences the behavior. Intentionally
limiting employees’ access to relevant information, resources, or networks can undermine their
job performance and lead to potentially adverse effects, including discipline and termination.
When these actions are concentrated on one group, it can be categorized as unfair treatment,
which is discussed in the next section.
Unfair Treatment
Unfair treatment can impact individuals in their everyday lives and their workplace.
These experiences can include receiving less courtesy or respect than others, having one's
intelligence challenged or questioned, individuals treating one as a threat, or being the target of
threatening or harassing behavior (Holliday et al., 2020). In the workplace, unfair treatment can
come from colleagues or supervisors, and the impact on targeted employees can vary based on
several factors, including the saliency of the targeted person's identity and the context of the
experience (Cojuharenco et al., 2011; Farrell, 2020). Unfair treatment can also harm mental
health and impede the task performances of those targeted (Axt & Oishi, 2016; Ojebuoboh et al.,
2022).
Ong et al. (2017), building on previous research that investigated the toll repeated
discrimination and unfair treatment have on physical health, examined the health risks related to
African Americans' everyday exposure to unfair treatment. They defined this daily unfair

36
treatment as "the range of chronic day-to-day experiences of discrimination such as being
followed around in stores or treated with less courtesy or respect than others" (p. 27). Their study
investigated the relationship between unfair treatment and the allostatic load, which refers to the
cumulative effect of chronic stress on the body. The researchers used surveys to gather data from
233 African American adults 37– 85 years of age, 64% of whom were women. Their data
suggested that everyday mistreatment was associated with higher allostatic load. Ong et al. also
noted that chronic mistreatment, even when race was not a factor, had detrimental impacts on
individuals' stress levels and health.
The cumulative stress from unfair treatment can have physical and mental health
implications. Ojebuoboh et al. (2022) investigated whether a relationship existed between
perceived stress levels and depressive symptoms in African Americans. They also examined the
mediating effect of talking to someone about perceived stress. The researchers used a sample of
376 African American adults from the South, aged 30-55, from the 2010–2013 Minority Health
Genomics and Translational Research Bio-Repository Database. Their survey data indicated that
individuals who spoke to someone about their unfair treatment had less perceived stress than
those who did not. Ojebuoboh et al. noted that talking to other people about the unfair treatment
they experienced also reduced depressive symptoms in their sample.
Experiencing regular incidents of unfair treatment can cause mental and physical health
challenges and economic and professional obstacles. While not always blatant, the subtle
differences in the way people behave towards an individual is detectable and the repercussions
can be cumulative and disrupt one’s normal cognitive processes. When unfair treatment is not
addressed, it can escalate and lead to additional discriminatory behaviors such as
microaggressions.

37
Microaggressions
Microaggressions are subtle forms of verbal, behavioral, and environmental insults that
perpetuate discrimination, systemic oppression and inequity targeting historically marginalized
groups (Banks & Horton, 2022; Sue et al., 2008). Social identities, including race, gender, and
sexuality, can impact individuals' perceptions of microaggressions and their impact (Banks &
Landau, 2019). The frequency of individuals' exposure to microaggressions also varies by social
identity, and research indicates that historically marginalized groups, including African
Americans, Asian Americans, Latinx Americans, and women, are targets of this behavior more
than White men (Liu, 2020; Meyers et al., 2020).
Individuals who believe that race does or should not matter perpetuate societal racism
and can exhibit micro-aggressive behavior because they fail to acknowledge that racialized
experiences shape individuals' backgrounds (Williams, 2021). Such color-blind attitudes were
examined in research by Banks and Horton (2022), who investigated the relationship between
color-blind attitudes and perceptions of microaggressions among students at a Predominately
White Institution (PWI). With a sample of 235 students, the majority of whom were White
women, with an age range of 18 to 59 years, the authors used survey research and manipulated
scenarios to gather data about the perception of microaggressions. Their data indicated a negative
correlation between color blindness and perceptions of microaggressions, where the more potent
the color-blind attitude, the less likely the individual would perceive microaggressions or find the
behavior offensive.
Kim and Meister (2022) used qualitative interviews of women leaders in STEM to
investigate gender-related microaggressions. They used semi-structured interviews with a sample
of 39 women, who were 70% White, 13% Asian, 8% Black, 3% Latina, and 6% Multiracial. The

38
participants had an average age of 39.1 years and 14.6 years of experience. The researchers
divided the participants into three leadership roles: Director or Senior Vice President or higher,
Senior Manager, or Team Leads. The data indicated that the 39 women experienced 224 specific
incidents that the researchers divided into five types of microaggressions. They included
devaluing technical competence, denying one's reality, and pathologizing of women's character
and gender. The data noted that these categories captured several micro-aggressive behaviors,
including questioning a woman's expertise in a group and denying that microaggressions
occurred after women reported the behavior. The data suggested that the experience of
microaggressions led to various emotions, including anger and sadness. It also indicated that
some reactions to these feelings led the women to certain behaviors, including questioning their
abilities or doing more work than their colleagues to prove they belong.
Microaggressions are not always readily identifiable, even to those regularly exposed to
them. However, their impact in the workplace can depend on the racial dynamic between
supervisors and subordinates and the perceived fairness of those in positions of authority
(Offerman, 2013; Wing Sue et al., 2007). However, having a fair-minded supervisor does not
reduce the stress caused by experiencing microaggressions or the potential disparate health
outcomes linked to chronic exposure, no matter how innocuous the behavior may seem (Lui &
Quezada, 2019; Pierce et al., 1977; Sue, 2008). For example, in their research on Black women,
Donnovan et al. (2012) investigated whether a relationship existed between their experiences
with microaggressions and symptoms of depression and anxiety. Using survey instruments, the
researchers gathered data from a sample of 187 women, aged 18 to 63, who were all
undergraduate students at a university in the United States. Their data indicated that 96% of the

39
women experienced microaggressions and suggested that Black women's experiences with
microaggressions negatively impact their mental health by increasing symptoms of depression.
Though subtle, microaggressions can have cumulative negative effects on individuals
who are targeted. Those who experience microaggressions do not always readily identify the
behavior. However, lack of intention does not limit the reality of this form of discrimination
because individuals’ micro-aggressive actions carry stereotypes, bias, and inequity.
Microaggressions, like incivility, exclusion and ostracism, and unfair treatment, are used as tools
of oppression that harm targeted individuals, who are often from historically marginalized
groups. While these behaviors can facilitate harmful daily experiences of discrimination, they
can also sabotage an individual’s performance in the workplace.
Workplace Discrimination
Societal issues such as racism and racial and gender discrimination can manifest in the
workplace. Bias and stereotypes also infiltrate workplaces and facilitate discriminatory behavior
targeting underrepresented groups (Malos, 2015). Research indicates that women and historically
marginalized groups, including Black and Latinx Americans, perceive racial discrimination at
work more than other groups (Del Carmen Triana et al., 2015). Dealing with subtle forms of
discrimination, such as microaggressions and exclusion or ostracism, in the workplace can
reduce cognitive resources and impart performance (Howard et al., 2020; Walker et al., 2022;
Wing Sue et al., 2007). Workplaces are not immune from the racial and gender discrimination.
The next two sections explore how discrimination impacts marginalized groups, and is
perpetuated in organizations’ policies and practices.
Marginalized Groups in the Workplace

40
In organizations that have a workforce dominated by one racial or gender group,
employees who are in the minority must navigate the institutional privilege conferred on their
majority group colleagues (Van Laer & Janssens, 2011; Winfield & Alston, 2014). In these
environments, racial and gender discrimination can manifest in various ways, including in
personal interactions between supervisors and subordinates, among colleagues, in teams, or in
organizational processes, such as work assignments and hiring (Meyer, 2014; Roscigno et al.,
2012). Discrimination can also lead to the majority group othering and marginalizing those they
deem as different (Van Laer & Janssens, 2011). Such discrimination can be mentally and
physically exhausting and erode the productivity of those who experience it by undermining their
abilities to perform their work (Shim, 2021; Walker et al., 2022).
In research about perceived employment discrimination, Nelson et al. (2019) conducted a
mixed-method study to investigate the workplace environment of underrepresented lawyers in
the legal profession. They collected survey data from 5,399 attorneys from a sample of 8,225 in
three waves over ten years. They also conducted a qualitative analysis of comments about
experiences of discrimination from 1,472 attorneys across the three waves. Their data indicated
that women, women of color, men of color, and LGBTQ+ attorneys perceived discrimination
significantly more than their heterosexual White male peers. They noted the evidence that these
groups experienced discrimination in both the public and private sectors and across large and
small law firms. In addition, their data suggested that women and people of color experienced
discrimination from supervisors, clients, and others in the workplace. The researchers also noted
that in their last wave, in 2012-2013, over 50% of African American women reported that they
experienced workplace discrimination. Additionally, 43% of African American men, between
29% and 45% of non-Black women of color, and 30% of LGBTQ+ attorneys reported the same.

41
McCord et al. (2017) also examined employees' experiences with unequal treatment in
the workplace. Using a meta-analysis of existing research, they examined workplace
mistreatment, broadly defined as abusive supervision, bullying, discrimination, harassment,
incivility, interpersonal conflict, ostracism, physical aggression, and verbal aggression. With a
sample of 399 studies, their data suggested that women perceive more workplace mistreatment
than men, while people of color perceive more workplace mistreatment than White employees.
Their data also indicated that Black employees perceived significantly more mistreatment than
Latinos and Asian Americans.
Despite evidence that Black employees' experiences of discrimination are
disproportionate to their White counterparts, data from a study by Ponce de Leon and Rosette
(2022) indicated that Black people are less likely to be believed when they report discriminatory
behavior. Their research focused on Black women and examined how their racial and gender
identities made them "nonprototypical" (p. 785) victims of discrimination relative to White
women and Black men. The research included eight studies with a total sample of 402
participants, 53.4% of whom were women. Their data suggested that Black women's gender and
racial discrimination claims were believed less compared to those made by White women and
Black men. In addition, their evidence suggested that after Black women alleged discrimination,
they received less financial compensation for their experiences than White women but more than
Black men.
Individuals from historically marginalized groups can face the same discrimination at
work as they do in society. In workplaces dominated by one gender or racial group, those who
are underrepresented have to navigate environments that are structured to disproportionately
benefit the majority. However, the majority is not advantaged by simply showing up.

42
Organizations can have policies and practices in place that perpetuate societal discrimination in
the workplace. Research related to this type of organizational discrimination is discussed next.
Workplace Policies and Discrimination
Discrimination can manifest in organizations through policies and practices that
unintentionally and disproportionately harm employees from underrepresented groups. Such
environments can create barriers in the employment process, including recruitment, hiring, work
assignments, performance evaluations, and promotions (Fernandez & Campero, 2017; Raferty,
2020). An employee's membership in an underrepresented group does not mean that the
individual will perceive their workplace to be unfair, and one can believe their workplace is a
meritocracy, even when there is evidence of experiences of discrimination and unfairness within
their self-identified group (Bird & Rhoton, 2021). However, the idea that companies are neutral
meritocracies can create a false sense of fairness within organizations, enabling bias to go
unaddressed and disadvantaging employees who experience discrimination (Castilla & Bernard,
2010).
An organization's recognition of and attempt to mitigate discrimination can also face
barriers. Lennartz et al. (2019) examined the implications of a company highlighting its
successful implementation of an equal opportunities program. Their data suggested that
highlighting the successful equal opportunities policy increased the expression of prejudices and
covert discrimination. In exploring an attempt to mitigate gender bias in hiring, Fernandez and
Campero's (2017) data also provided evidence that policies designed to address bias are
ineffective in reducing the bias. Their data indicated that the work needed to occur before the
hiring stage through recruitment and outreach policies designed to reduce gender disparities in
job applicants.

43
Attempts to provide diversity training to root out bias have also mutedly reduced
workplace discrimination. Sanchez and Medkik (2004) evaluated the effectiveness of cultural
diversity training among managers, and their data indicated that the training did not reduce bias
or differential treatment of historically marginalized groups. King et al. (2012) indicated that
diversity training may be ineffective. However, the researchers noted that it could be helpful as a
tool, among others, to help reduce discrimination in the workplace. Dover et al. (2014) examined
diversity initiatives more broadly and investigated whether employees' belief in the system's
fairness undermined employees' discrimination claims. Their data indicated that the existence of
the diversity initiative reinforced the idea that the workplace was fair and made it more difficult
for employees to report experiences of discrimination. Dover et al. noted that the diversity
initiative was valuable to the organization because it delegitimized claims of discrimination from
employees in underrepresented groups and increased the perception that the company treated
everyone fairly among employees of the majority and historically marginalized groups.
The narrative that American workplaces are unbiased, neutral meritocracies ignores the
research that indicates the opposite. Organizations can perpetuate the discrimination that exists in
society through policies and practices that privilege the majority at the expense of those who are
chronically underrepresented. From recruitment, to hiring, promotion and termination, the ways
in which policies are implemented or enforced, can create barriers for historically marginalized
groups. In the next section, the impact workplace discrimination will be examined through the
lens of Black women in the workplace.
Black Women in the Workplace
As an underrepresented group within Black American communities and among women,
Black women experience gender and racial discrimination in society that is replicated in the

44
workplace. Laws prohibiting discrimination in the workplace have not protected Black women
employees from experiencing such behavior. Research indicated that Black women comprise less
than 4% of middle management positions, and less than 2% of senior management positions in
the private sector, making them vulnerable to disparate treatment that isolates, others, and
penalizes them (Bloch et al., 2021; Williams, 2023). Working in spaces that are dominated by
one race or gender can mentally and physically tax Black women as they take on the extra
burden surviving and coping with incidents that racialize and marginalize them (Shim, 2021).
Black Women Underrepresented at Work
Pollak and Nieman (1998) examined Black women’s experiences of distinctiveness,
operationalized as feelings of racial awareness, and responsibility and accountability to their
identified race, in a predominately White university. Using three studies with samples totaling
296 student participants, their data indicated that Black students felt chronically distinctive,
meaning that they had a hyper awareness of their racial and gender identities. The data suggested
that the feelings where chronic because Black students felt this way in spaces where they were
the only Black person, and when they were not. In contrast, the study noted that their White
peers only felt distinctive in spaces where they were in the minority.
DeCuir-Gunby et al. (2020) also examined Black experiences in predominately White
spaces. Their research explored how Black women navigated experiences of racial
microaggressions at historically Black colleges and universities (HBCU) and predominantly
White institutions (PWI). Their data suggested that the participants experienced similar incidents
of racial microaggressions at both HBCUs and PWIs, but the number of these experiences at
PWIs were more than triple of the incidents at HBCU workplaces. The researchers noted that the
participants used several coping methods to deal with their experiences, including peer support

45
groups, self-care, avoiding conflict and increasing their workload. In addition, Rabelo et al.
(2021) studied the detrimental impact that working in spaces that center the perspective of the
dominant racial group can have on Black women. The researchers analyzed 1169 tweets that had
a hashtag #BlackWomenAtWork to assess how the “white gaze” (p. 1841), defined as the
observing people through the lens of the White majority and creating workplace cultures,
policies and practices that center that gaze. Their data suggested that Black women face more
scrutiny than their non-Black peers in the workplace due to their behavior being monitored,
dissected, and analyzed through the lens of whiteness, or the white gaze.
The additional scrutiny that individuals from historically marginalized groups face in
workplace can negatively impact Black women in all professions. Williams (2023) used
qualitative research to explore how 12 Black women higher education professionals navigated
policing in the workplace, defined as “the physical, metaphorical, and or emotional manipulation
of Black women’s actions to better align with white supremacist notions of professionalism” (p.
69). The data noted that Black women experience workplace policing regularly, in behaviors
that range from comments on their hair, being chastised about their tone of voice, or criticizing
them for showing emotion, while nurturing their White peers who exhibit similar behavior. The
constant awareness of their racial and gender identities can cause some Black women to alter
their behavior. Dickens and Chavez (2017) conducted research that examined Black women’s
use of identity shifting, or presenting themselves in a manner they believe to be more palatable to
others. They noted that Black women do this to cope with the discrimination they experience in
predominately White environments. Their data, collected through semi-structured interviews
with 10 Black women participants, indicated that Black women alternate between identities and
alter their behavior and speech depending on who they encounter and the context in which they

46
are working. Coping strategies such as these, and others employed outside of the workplace,
including familial support, are critical to Black women’s well-being and ability to exist and be
resilient in predominately White workplaces (Dickens & Chavez, 2017; Linnabery et al., 2014;
Ross et al., 2021).
Black Women in STEM Fields
Black women encounter challenges early and often in the STEM pipeline and remain
among the most underrepresented in STEM fields and computer science occupations (Brown et
al., 2016; Yamaguchi & Burge, 2019). The intersection of Black women's racial and gender
identities creates unique obstacles not faced by their Black male or White female counterparts in
STEM fields (Crenshaw, 1991; Solomon et al., 2018). These challenges persist in the tech
industry, which is racially homogeneous and dominated by one gender because it perpetually
fails to increase the overall number of women and people of color in the industry's workforce
(Cook, 2020). However, research indicates that Black women continue to pursue and stay in
STEM professions for several reasons, including opportunities to innovate and grow, a
heightened sense of service driven by a high level of agency and confidence, and the desire for
financial stability (Sendze, 2022).
Research suggests that Black women and girls also face obstacles in the STEM field at
every part of the education-to-career pipeline related to their racial and gender identities. Robnett
(2016) explored the gender bias in STEM that impacts women and girls across racial lines and
impacts their self-perception in STEM-related courses. For example, the researcher conducted a
study that focused on reported experiences of gender bias in STEM courses from women and
girls in high school, undergraduate programs, and graduate school. Survey data from a sample of
334 students, most of whom identified as European American. The data suggested that most

47
participants experienced gender bias in math or math-related subjects, and the bias tended to
come from male peers.
In a study that examined Black experiences in STEM majors and professions, Brown et
al. (2016) conducted survey research with a sample of 611 participants, 52% of whom were
women and 48% men, who were either science majors or professionals in a science field. The
data indicated that Black STEM students and professionals reported experiencing racially biased
treatment at almost equal rates, but the groups navigated the instances differently. They noted
that the professionals believed they could out-work the bias, whereas the students expressed their
feelings about their experiences but did not provide strategies to navigate them.
Ross et al. (2020) examined a different aspect that impacts students' career prospects –
social experiences. Their research investigated similarities and differences between the social
experiences of Black women, Black men, and non-Black women studying computer science in
universities in the United States. The researchers used surveys to collect data from a sample of
3206 participants from 118 institutions. The data suggested that Black women had similar career
aspirations as the Black male and non-Black women peers, but their social experiences differed.
The differences among STEM students and STEM professionals, however, do not capture
the experiences of Black women in STEM. Crenshaw (1999) asserted that Black women must
contend with racial and gender discrimination in ways that differ from non-Black women and
Black men. She noted that, as result, Black women’s experiences with discrimination cannot be
appropriately assessed through the lens of gender alone. Yamaguchi and Burge (2019)
understood the nuance of intersecting salient identities when examining Black women's STEM
experiences. With a sample of 93 Black women in computing, the researchers conducted a
mixed-method qualitative and quantitative study to gather data in surveys and focus groups.

48
Their data indicated several main themes at the intersection of gender and race in computing,
including: influential culture, educational support, and leadership development. They also noted
that the participants believed their respective organizations needed to be held accountable for the
structural deficiencies that impeded support and advancement for Black women employees.
Ross et al. (2021) examined Black women engineers and how the development of their
professional identity helped build their resilience in the field. Using a qualitative study, the
researchers interviewed a sample of nine participants with engineering degrees, who worked in
the field for at least 10 years, self-identified as an engineer, and identified as African American,
or part of the African diaspora. Their findings indicated that the constant centering of their racial
identity and bias they experienced strengthened their identity as engineers. They noted that
participants used several strategies to navigate the discrimination they faced, including creating
their own supportive environments with family and colleagues, self-efficacy and building their
self-confidence
Discrimination in STEM fields extends to the technology industry, which is homogenous
and lacks racial and gender diversity. For Black women, research has noted that feelings of
isolation and subordination and gendered and racial stereotypes that plagued them in STEM
classes extend into the recruitment, retention, and advancement in tech workplaces (Alegria,
2019; Charleston et al., 2012; Rankin & Thomas, 2020). These homogenous environments can
also threaten Black women's intellectual safety, where they feel fear of retribution from
supervisors or colleagues for sharing their thoughts, feelings, or opinions (Call, 2004). While
classroom climates have framed the study of intellectual safety, its tenets, including a respectful
environment where leaders create a supportive climate where individuals feel supported when
expressing their unique ideas and perspectives, even when challenged, can apply to the

49
workplace (Schrader, 2004; Tallapragada et al., 2015). A leader's role in promoting such a
climate is significant for Black women who face discrimination. However, without such
leadership, Black women have demonstrated resilience to racial bias in corporate workplaces
through a myriad of actions, including self-preservation strategies, counter-narratives to combat
stereotypes, and creating opportunities for mentorship and relationship building (Sisco, 2020).
This ability to navigate through discriminatory treatment in tech mirrors Black women's ability
to navigate the challenges they face with gendered racism in society (Spates, 2020).
Black women regularly encounter discrimination that leads to disparate treatment in
college and the workplace. In predominately White environments, including PWIs and STEM
fields, they are especially vulnerable to beliefs and actions that question their capabilities, limit
their opportunities, and undermine their advancement. Despite the obstacles they face, Black
women have demonstrated ways of coping that help them navigate the hostile environments in
which they exist. Not satisfied to just exist, however, research indicates that Black women have
leaned into their identities and found support inside and outside of their families to overcome
adverse workplaces. Data suggest that Black women’s self-efficacy has sharpened their
confidence and made them more resilient and kept them pursing opportunities in workplaces that
were not designed for them.
Theoretical Framework
The theoretical framework guiding this study is Black feminist theory, also termed Black
feminist thought (Collins, 2000). Black feminist thought (BFT) is a critical social theory that
views oppression from the perspective of subjugated individuals. Collins' (2000) theory asserts
that the intersecting oppressions of race, gender, and class inform Black women's experiences.
The theory recognizes that Black women's life experiences vary significantly due to several

50
factors, including age, region, social class, sexual orientation, and religion. However, because of
everyday challenges, due to the intersection of racism and sexism, Black women's experiences
have "recurring patterns" (Collins, 2000, p. 29) that establish their "standpoint" (Collins, 2000, p.
29), or collective group knowledge that develops because of oppression.
Through their unique standpoint, Black women are empowered and inspired to activism and fight
the oppression that is inflicted upon them by those who benefit from their subjugation or have
the power to suppress them (Collins, 2000). Black feminist theory has multiple themes that allow
one to examine the systems through which Black women must navigate. This theory can also
provide insight into how racial and gender oppression manifests in the tech industry and measure
whether and how Black women resist oppressive practices and the ideology behind them
(Collins, 2000).
Conceptual Framework
The conceptual framework for this study will build on BFT to assess how Black women
experience discrimination in the tech industry. According to Grant and Osanloo (2014), a
conceptual framework illuminates the path used to understand the proposed problem of practice
and the variables the study is assessing. Through the lens of BFT, this study will center the
experiences of Black women in the tech industry and assess their Black standpoint, or collective
group knowledge, that is informed by their diverse experiences and shaped by racial and gender
oppression in the United States. Assessing whether race and gender interact in ways that differ
from what is in the literature, Collins' (2000) BFT argues that common challenges due to the
intersection of oppression will create "recurring patterns" (p. 29) that may emerge from this
research.

51
Critical concepts in BFT include empowerment through self-valuation and resisting
negative perceptions of Black women, confronting, and dismantling interconnected structures of
racial, gender, and class oppression, and the fusion of intellectual thought and political activism
(Collins, 2000; Taylor, 1998). Black women's experiences in the tech industry are impacted by a
lack of diversity, and racial and gender discrimination, in the workplace (Maddox, 2013; Yang,
2021). While their experiences may differ, BFT asserts that patterns of oppression will emerge as
Black women's experiences are centered and shared, and their strategies for navigating and
coping with racism and sexism are expressed (Collins, 2000; Joseph et al., 2021; Mekawi, 2021).
However, not all Black women will have the same perceptions, react the same way, or readily
identify discrimination (Collins, 2020). Figure 1 illustrates the conceptual framework with bidirectional arrows to symbolize various reactions and perceptions at each stage.
Figure 1
Conceptual Framework
Conclusion
Black women in tech
industry
Incident of
discrimination (race
and gender)
Perception of
Discrimination
Black women's
coping strategies
Self -valuation and
resisting negative
perceptions
Action that activisim
to dismantle racism
and sexism in tech

52
Racism and discrimination in society tend to manifest in workplaces (Wiecek &
Hamilton, 2014; Wingfield & Alston, 2014). In the tech industry, one of the STEM fields, a lack
of diversity contributes to discrimination targeting historically marginalized groups (Wiecek &
Hamilton, 2014; Wingfield & Alston, 2014). As one of the most underrepresented groups in the
tech industry workforce, Black women are vulnerable to discrimination and may experience such
behaviors in ways that their Black male colleagues and White women colleagues do not
(Maddox, 2013; Okechukwu et al., 2014; Sanchez et al., 2019). Centering Black women in
assessing how discrimination manifests in the tech industry necessitates a lens that understands
that they navigate the intersection of racial and gender oppression daily across settings and their
lived experiences (ABO Report, 2020; Goins et al., 2022).

53
Chapter Three: Methodology
The purpose of this study is to assess the workplace discrimination Black women face in
the tech industry. This study examined how Black women navigate workplace experiences they
perceive as discriminatory, the institutional policies or practices that enable this behavior, and
the mechanisms Black women use to cope with perceived incidents of discrimination. This
chapter provides an overview of the design of the research study and a description of the
individuals who were selected to participate. In addition, the theoretical framework provided
establishes the lens through which this study was conducted. This chapter also provides
information about the data collection procedures and instruments. Finally, the data analysis
structure is detailed, and there is a discussion about the procedures for implementing the highest
ethical standards, safety, and confidentiality protocols that protect participants' anonymity.
Research Questions
To assess the workplace discrimination Black women face in the tech industry, the
following research questions guided this study:
1. What workplace behaviors do Black women experience in the tech industry that they
perceive as discriminatory based on their race and gender?
2. How do Black women cope with workplace experiences that they perceive as adverse
or unfair?
3. What workplace policies or practices enable discrimination against Black women in
the tech industry?
Overview of Design
This field study used a qualitative approach to conduct phenomenological research
examining the lived experiences of Black women in the tech industry (Creswell & Cresswell,
2018). The research questions guided the collection of data through one-on-one interviews to

54
ascertain information about past experiences of discrimination (Merriam & Tisdell, 2016).
Qualitative interviews with 11 women who identify as Black, African American, or Biracial who
currently work in the tech industry provided data for this study. Data collection facilitated
understanding of how the participants perceive and cope with workplace discrimination and
illuminate any institutional structures that enable discriminatory behaviors. Using pseudonyms in
place of real names protected the participants' identities and shielded the names of the companies
for which they currently or previously worked. In addition, the demographical information
collected from participants, including age range, gender expression, and location, were deidentified to protect participants' anonymity.
Research Setting
This qualitative field study aimed to capture Black women's experiences working in the
tech industry on the product side as software engineers, software developers, coders, or on the
business side in positions that help manage the operations of the organization. Black women
account for approximately 1.7% of the tech workforce (Sanchez et al., 2019; Zippia Report,
2022). There is also an obstacle-laden pathway into science, technology, engineering, and math
(STEM) for Black students that often limits opportunities for those who want to work in tech
(Charleston et al., 2014; Robnett, 2016). Interviewing Black women who work in tech provided
insight into how discrimination manifests in their work life. These interviews also highlighted
the strategies Black women use to cope with workplace discrimination and provided information
about how to increase inclusiveness in a racially homogenized industry dominated by one
gender.
The Researcher

55
My positionality is influenced by the intersection of my three salient identities, as a Black
person, a woman, and part of the working class, which fall on the oppression side of the
Intersecting Axes of Privilege, Domination, and Oppression (Axes) (Morgan, 1996). As a
working-class Black woman who is often one of the few, or the only person who looks like me in
many spaces, I have experienced racial and gender discrimination in the workplace. I sometimes
still struggle to name what I am experiencing, and the inability to name it impedes my ability to
communicate and connect the dots for those who have the authority to change things. As a
student researcher, I carried this knowledge with me as I worked to understand what Black
women in tech experience in their work environments. I also acknowledge that my education in
social science and my work experience in government may render me unable to appreciate the
challenges that Black women, who have STEM education backgrounds and work experiences,
must navigate the tech industry.
As I consider my topic of examining Black women's discrimination in the tech industry, I
most closely align with the Transformative philosophical worldview (Creswell & Creswell,
2018). The Transformative paradigm described by Creswell and Creswell (2018) looks at power
structures from the perspective of the marginalized communities that are most impacted and
exposes entrenched and political features that contribute to systemic oppression. This paradigm
informs my lens on my research topic because I view the tech industry as part of the corporate
power structure that marginalizes Black women in a manner that undermines the trajectory of
their professional lives and financial well-being. The Transformative paradigm shapes my lens
on this topic by centering the investigation on the perspective of the Black woman tech employee
and understanding of how corporate power structures contribute to work environments that
perpetuate discrimination against historically marginalized groups.

56
As a Black woman, who continues to navigate marginalized group status, I acknowledge
that powerful systems do not simply exist; they are designed and maintained by influential
stakeholders, institutions, and individuals. As individuals most impacted by discrimination in
these systems, Black women need be at the center of any investigation into the system and any
proposed systemic changes; otherwise, the system will center itself. Centering Black women in
this study also means focusing on equity and exploring workplace inequities as symptoms of
systemic racism. In addition, it also means that I have to be careful not to use my research to
create or exacerbate what Tuck and Yang (2014) noted are "pain narratives" (p. 227) of Black
women who work in tech to justify the wrongs that my positionality and privilege as a student
researcher, allow me to investigate.
Data Sources
The data sources used in this study were semi-structured interviews with 11 women who
identify as Black, African American or Biracial and work in the tech industry. Participants were
selected based on their identity, employment, or previous employment status and their interest in
voluntarily sharing their workplace experiences. This purposeful sampling of Black women who
work in the tech industry ensured that the participants in this study represented the range of
experiences Black women can have when encountering discrimination in tech workplaces
(Maxwell, 2013). During the interviews, participants answered questions about the challenges
they experienced in the workplace, the steps they took to cope with these incidents, and the
institutional policies or practices that enabled or inhibited that behavior. The interviews were
conducted on the computer, using Zoom with the video and audio recorded. Consent to record
the video and audio was requested and obtained before each interview. When consent to record
audio and video was not provided, consent was obtained to take notes during the interview.

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Participants
The target population for this qualitative study were Black women who were at least 22
years old and work in the tech industry or had worked in the tech industry within the previous 12
months. Qualified participants were employed on the product side of their organization as a
software engineer, software developer, or coder, or on the business side in a role that helps
manage the operations of the organization. This population was an appropriate group for this
study because the research focuses on Black women's experiences of discrimination. While other
women and other Black people may experience discrimination based on their gender or race,
Black women are uniquely positioned to speak to their experience with discrimination that
intersects with their racial and gender identities (Crenshaw, 1991).
Instrumentation
One-on-one interviews, conducted after obtaining the consent of each participant, and
Zoom, an online tool that recorded both video and audio, captured the data for this study. The
semi-structured interview protocol had 16 questions and additional probing questions that
requested information about workplace, strategies used to cope with incidents they found
challenging or unfair, and identify institutional policies or practices that may enable certain
behavior. In addition, a demographic information including years worked in tech, previous
employment and educational background was gathered using the professional social media site
LinkedIn. The questions in the interview protocol sought to elicit responses from participants
that described their experiences of perceived discrimination, their coping strategies when such
behavior was encountered, and the institutional factors that they believed enabled this behavior
in their workplaces. The study's interview protocol is included in Appendix A.
Data Collection Procedures

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Interviews with 11 women who identify as Black, African American, or Biracial and
worked in the tech industry on the product side of their organization as a software engineer,
software developer, or coder, or on the business side in a role that helps manage the operations of
the organization, generated the data collected for this study. To ensure that members of the target
population were selected, "purposeful sampling" (Maxwell, 2013, p. 97) was used to create a
sample of Black women working professionals, who have at least 1 year of experience working
in the tech industry. Recruitment materials included an electronic flyer with a quick response
(QR) Code that linked to details about the study, a consent form, and a brief demographic survey
designed to attract participants who meet the study's criteria. Emails containing the electronic
flyer was sent to individuals with whom the researcher has a personal or professional
relationship, requesting that they send them to their respective tech networks. The electronic
flyer was also posted on LinkedIn, a professional social networking site, to reach potential
participants. For individuals who responded to the electronic flyer, each potential participant
received an email from the researcher's student email account that further explained the study,
requested their participation, and obtained consent from those who agreed to participate in the
interviews. Additional recruitment of participants occurred when individuals, including those
who already participated in the study, and professional acquaintances, used email to refer
additional women who met the study’s criteria to the researcher. After the initial introduction
email, each potential participant received an email from the researcher's student email account
that further explained the study, requested confirmation of the individual’s participation, and
requested the person’s consent to participate in an interview.
Participants' consent to be interviewed and recorded was requested before their interview
was scheduled. After consent was acquired, participants were asked to provide two to three dates

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and times that worked for their schedules in a specified window to find a date and time that
worked for all parties. After selecting a date and time, the participant received a confirmation
email with the selected date, time, and Zoom link for the interview and a reminder email two
days before the interview date. If the participant canceled the interview due to a timing conflict,
the individual was offered the opportunity to reschedule.
The time allotted for each participant interview was one hour, conducted via Zoom and
recorded. Participants were given the option to have the interview conducted with the computer
cameras on or off. They also had the option to opt out of having the video and audio recorded. If
a participant chose to opt out of having the interview recorded, notes were taken by hand during
the interview. Once data was collected, an online transcription service was used to transcribe
each interview. To ensure accuracy, reviews of the transcribed interview and interview audio
recording co-occurred. For safe storage, transcripts and recorded interviews were saved on a
laptop that is password protected and kept in a secure location. The transcripts, video, and audio
recordings will be destroyed 2 years after the study ends.
Data Analysis
Data analysis allows a researcher to make sense of the qualitative data collected during a
study by developing meaning and extracting findings that answer the research questions
(Merriam & Tisdell, 2016). The data in this study was analyzed using the data analysis process
developed by Creswell and Creswell (2018). First, an online transcription service transcribed
each recorded interview. Second, reviewing all interview transcripts and typed notes provided an
overall view of what participants stated. Next, the data from the interviews was coded, or
categorized under broad themes, to find similarities in the participants' experiences. When coding
the data, the categories used to sort through the information reflected the nature of the data and

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were "conceptually congruent" (Merriam & Tisdell, 2016, p. 213). The fourth step in this process
included using the coded data to develop themes or significant findings across participants'
experiences. In step five, a summary of the emergent themes found in the coded data provided
findings from the study.
Interview Method
The interview protocol for this study included 16 questions and probes to deepen
responses about participants' experiences with racial and gender discrimination (Merriam &
Tisdell, 2016; Patton, 2002). The interviews were semi-structured, combining a general
interview guide approach and a standardized open interview approach that allowed flexibility
with which questions were on the list and to allowed the conversation to flow more naturally
(Patton, 2002). This type of interview allowed probing questions to be asked, when necessary, in
cases where participants needed to provide in-depth answers to the initial questions and a followup question was needed. Before each interview, an introduction statement was made that
included information about the study, a verbal request to confirm consent to video and audio
record the interview, and a reminder that their participation was voluntary and that they could
stop the interview at any time. Additionally, participants were given the opportunity to ask the
researcher questions before and at the end of the interview. The goal of providing time for
questions was to build a rapport and make each participant feel comfortable.
The open-ended interview questions allowed Black women to describe and provide detail
about their experiences in the workplace that could ascertain whether they deemed them unfair or
adverse, without limiting the possibility of their responses (Patton, 2002). The first two questions
were factual to avoid diving directly into their experiences and how specific incidents make them
feel, to help participants feel comfortable (Krueger & Casey, 2009). The subsequent questions

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asked participants to describe their experiences. These questions generated data about how
participants perceive discrimination, allowing for the collection and analysis of data to determine
whether patterns exist. These questions aligned with the Black feminist theory, which posits that
race, gender, and class shape Black women's experiences and their shared experiences generate
collective knowledge that disrupts oppressive systems that may limit them in the workplace
(Collins, 1990).
The interview protocol had questions that focused on three critical concepts in the
conceptual framework: Black women's experiences with discrimination, how they managed
through these experiences, and whether their coping mechanisms impact self-valuation and the
resistance to negative perceptions. Similar questions also asked about their treatment and
whether they believed it was fair. These similar questions sought to capture the intersection of
racism and sexism that may exist in individuals' experiences. Some questions asked participants
to describe how incidents made them feel to capture how Black women may internalize the
discrimination they experience. Finally, there were questions about workplace practices and
policies designed to learn whether institutional factors enable or contribute to perceptions of
discrimination.
Credibility and Trustworthiness
Strategies used to ensure credibility in qualitative research include triangulation and
member checking (Merriam & Tisdell, 2016). Peer examination is a second strategy used for
credibility purposes (Merriam & Tisdell, 2016). To confirm the credibility, steps were taken
during the study to ensure that others can follow its procedures. These steps included consistent
coding categories and detailed interview protocol information (Merriam & Tisdell, 2016).
Ethics

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This study builds on existing literature that examines racism, racial and gender
discrimination, workplace discrimination, and Black feminist theory, providing a foundation to
examine the participants' experiences. All participants were protected, and their identities were
kept confidential. Additionally, as part of obtaining consent before they began the study,
participants were informed that they could stop the interview at any time (Merriam & Tisdell,
2016). As a part of the informed consent, which participants received before beginning the
interview, a brief statement was included that emphasized that the data generated through their
interview was for student research purposes. In addition to having a robust informed consent
process, the study followed the university's institutional review board (IRB) process to protect
the human participants who choose to participate in this research. Additionally, the semistructured interview protocol began with two questions that elicited fact-based answers to help
participants ease into the interview before getting questions related to their workplace
experiences.
Summary
This chapter overviews the qualitative field study methodology, data collection, and data
analysis used to implement this research. The following chapter will present the study's findings
related to the research questions. The data collection findings and an examination of their
meanings were reviewed for their relationship to the study's purpose.

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Chapter Four: Findings
This study aimed to assess the workplace discrimination Black women face in the tech
industry. The conceptual framework, based upon Black feminist theory (Collins, 2000),
identified the participants’ Black standpoint, or collective group knowledge, that is informed by
their diverse experiences and shaped by racial and gender oppression in the United States. The
data, collected using qualitative interviews, assess whether race and gender interact in ways that
create recurring patterns in the everyday challenges participants face in the workplace. The
conceptual framework and data informed the organization of the research findings and the
development of the recommendations. This chapter outlines the research participants, interview
results, and findings. The following research questions guided this study:
1. What workplace behaviors do Black women experience in the tech industry that they
perceive as discriminatory based on race and gender?
2. How do Black women cope with workplace experiences that they perceive as
adverse or unfair?
3. What workplace policies or practices enable discrimination against Black women in
the tech industry?
Participating Stakeholders
The eleven women purposefully sampled for this study all identified as Black, African
American, or Bi-Racial. Informal and formal professional networks and a general posting on
social media facilitated contact with the participants. All 11 participants agreed to participate in
one-on-one interviews conducted via Zoom, and 10 agreed to have their interviews video and
audio recorded. One participant did not consent to having her interview video or audio recorded
but agreed to allow the taking of typed notes during her interview. A laptop computer was used
to type notes during the interview. To protect their identities, participants received pseudonyms

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after their interviews. Table 1 provides an overview of the participant pseudonyms and indicates
whether participants work on the product side of their company, meaning they are directly
involved in developing their respective companies’ products or writing code, or the business
side, meaning a job related to something other than direct product development or coding. To
protect the participants' identities and the identity of their employers, ages, job titles, and
company sizes were not used. The table also includes the approximate number of years each
participant worked in the tech industry.
Table 1
Demographic Information of Participating Stakeholders
Participant Name
(Pseudonym)
Tech Role Number of Years in Tech
(Approximate)
Aja Product Side 13
Bianca Business Side 9
Charlotte Business Side 20+
Daphne Business Side 10
Elise Business Side 10
Faith Business Side 3
Gladys Business Side 11
Harper Product Side 6
Isabelle Business Side 5
Jordyn Business Side 8
Kenzie Business Side 6

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Findings for Research Question 1
Black women in tech represent less than 2% of the workforce despite accounting for
almost 7% of the United States population. Research Question 1sought to understand the
workplace behaviors that Black women in tech experience and perceive as discriminatory based
on race and gender. This section describes experiences that the participants perceived as
discriminatory. The data analysis revealed three key themes that emerged through the collective
experiences of the participants: (a) experiencing subtle discriminatory behaviors from
supervisors and coworkers, (b) feeling dismissed and undervalued, and (c) perceived lack of
intellectual safety.
Experiencing Subtle Discriminatory Behaviors from Supervisors and Coworkers
All eleven of the participants described incidents that occurred in the workplace that they
perceived as unfair treatment or microaggressions, two subtle discriminatory behaviors. “I feel
like I've gotten a lot more questioning than other leaders," Bianca explained. Isabella noted a
similar experience. “You might be the only woman of color, which happens very often, and you
go through that gaslighting thing in people questioning if you really belong.” Harper also
experienced microaggressions at work. She explained, “Now [that] there are more black women,
as more black people joined, people are just viewing them like, oh, they don't deserve to be
there.” Gladys expressed an instance of behavior that she believed was a microaggression.
“Anytime I'm leading a team,” she explained, “the leader or someone always has an issue. And
I'm nice as pie, but there's always something.” Jordyn explained a similar experience:
[There are] moments where it's singled out and it's a reinforcement that this space still
isn't created for me. And I'm still one of only [a few] and seen as the awkward odd person
out, meaning anything I do is gonna be looked at through a different lens.

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The participants experienced exchanges with peers and behavior from supervisors that conveyed
to them that they did not belong or that their work was subpar without saying those words
directly. They discussed multiple incidents of being questioned about their work or having to
prove their abilities when their non-Black peers did not have to do the same.
Unfair treatment was another discriminatory behavior that participants discussed when
asked about the challenges they face in the workplace. Though subtle, unfair treatment can be
professionally detrimental to targets. As Harper stated:
There isn't a lot of fairness to begin with and so you end up not getting the right projects,
the right visibility, and that sets you back. I also think that mediocrity is allowed for
certain races but not allowed for others. So if a black person is not doing their job or is
lacking in certain areas, you're not given a pass. You have to figure out how to improve
yourself and get back on track, without much grace from anyone.
Gladys took the sentiment further and noted that “[The] Black woman is the lowest on the totem
pole in tech. You have to be willing to play that game, but what does that do for you as an
individual and your mental health? You can't even be yourself.” The perceived unfairness the
participants experienced was not limited to colleagues’ and supervisors’ words and behaviors; it
also impacted compensation.
While eight of the participants either did not mention their pay or expressed that they
believed their compensation packages were fair, three had different experiences. Bianca
explained, “I remember my first six figures, and I was just like, oh, my gosh, I'm so rich. But,
over time, you realize, I just took $7,000 less than someone that had 4 years less experience than
me.” Harper also discussed disappointment with her pay. “They just want me to work, but they're
not trying to pay me what I'm due.” Charlotte had a more direct experience with a leader

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challenging her compensation. “They're just biased,” she stated. "The VP of HR, when she came
on, because I was there before her, and she's like, I see how much you're getting paid. That's way
more than you should be getting paid.” These experiences of perceived unfair treatment and
microaggressions permeated through participants' interviews. The examples indicated that
repeated exposure to patterns of discriminatory behavior.
Feeling Dismissed and Undervalued
Most participants discussed perceived experiences of having their contributions to their
company dismissed or devalued. Daphne explained, "I have to insert myself in conversations. I
am listened to, but there's a lot of noise. You can say one thing, and then the guy says it the same
way, and you're like, I literally just said that.” Glady expressed a similar experience, “The
typical day, if you present an idea, everyone's quiet, they shoot it down, [a man] says, it is great.”
The difference in who is contributing was further defined. “In meetings, I would say something,
and be completely ignored.” Harper explained. “Then a White man says the same thing, and
they're like, that is such a wonderful, brilliant idea. I'll be sitting there thinking, but I literally just
said this.” Bianca stated, "I say it once I get dismissed. I have to go to level 10 and be the angry
black lady before it's like, why aren't you listening to me? The words coming out of my mouth
are not incorrect.” Elise also expressed her feelings of being unheard. She noted, “It sucks in the
environment where you’re not heard. [It] can be really demoralizing. You can get angry and keep
pushing, or you shut down.” Participants indicated that these incidents regularly make them feel
unheard or that their opinions are dismissed or only appreciated when verbalized by a male
colleague. This discriminatory behavior creates an environment in the workplace for Black
women that signals to them that such treatment is allowed and opens the door for their colleagues
to replicate it.

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In addition to participants’ feelings of being dismissed or unheard, four participants noted
they also had perceptions of being undervalued. Aja noted, “I'm not responsible for anyone's
performance… I am very senior because I've been doing this for a while, so that means I'm often
managed by someone who's more junior. I am never managed by an equal subject matter expert.”
Elise explained, “It can be easy for people to feel disposable. The 24 hour grind in tech – no
value placed on work life balance. Your value is based on the number of hours you put in instead
of the work you’re producing.” Their feelings of being disposable also came from being overmanaged. Bianca stated, “there's so much checking of my work. Making sure that their brand
isn't tarnished, or it's the way that we want to say it or you know, the project is correct.” Harper
explained her experience, which had similar undertones. "There have been cases where I'm the
fall person. A project doesn't go well, or if something happens, there's a mistake somewhere,
somehow, I tend to be the one who gets pushed under the bus.” Jordyn expressed her sentiments
about feeling undervalued:
I'm tired and unsupported. But… it's what I expect. In any environment, I don't expect an
outpouring of support, or an outpouring of value being shown. And I expect to have to
work a certain level to get stuff and also expect having to carry the burden to a certain
degree when it comes to certain things. So it's exhausting, but it's a familiar role,
considering that [I’m a] Black woman, so I've never known different.
These feelings of being dismissed and undervalued contributed to these employees’ perceptions
of disparate workplace treatment. They also provide examples of how discriminatory behaviors
of others shape the workplace experiences of Black women in tech.
Perceived Lack of Intellectually Safety

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Ten participants could reasonably define feeling intellectually safe or used the term
interchangeably with psychological safety to comprehend the concept and convey whether they
felt intellectually safe in their workplaces. Aja explained, “I absolutely don't have psychological
safety and also, I actively don't speak up or suggest things because I get immediate dismissal of
that thing.” Gladys responded more directly about her experience in tech, “No, never in any of
my roles.” Daphne had a similar response, “Being able to speak your mind without thinking,
‘Oh, my God, I'm gonna lose my job?’ I’ve never felt that.” Participants expressed a lack of
intellectual safety that aligned with their experiences of feeling dismissed and undervalued at
work.
Four participants had very different responses than the participants who expressed that
they did not feel intellectually safe at work. Elise stated, “We all put on a little bit of a mask at
work. You can’t let your guard down. You can’t bring your full self to work; you can only bring
parts of yourself to work.” Faith also had a view that differed from the other participants. She
explained, "I don't see intellectual safety or being in an intellectually safe space as something
they give me. I see that as something I create and insist upon. And if it is not there, I pivot and
move on.” Isabella could define the term but said she shifted her language away from it. She
explained, "It's almost impossible for you to make a safe space for everybody. You don't know
what they're dealing with…you don't know who's there who may have had an impact on their
career that they're uncomfortable to speak [openly]." Charlotte explained her experience of
feeling intellectually safe with her supervisor. She stated:
I felt it with my manager because I think she was really intentional about asking
questions without pushing. There was an exchange of vulnerabilities that kind of set a
level. I think you can put all your vulnerabilities on the table, but if you're not getting

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anything in exchange, it feels like you're just giving everything up, and then they hold the
power. But when you're both pouring [out] these vulnerabilities, power is not even a
word in the room.
Participants' perceptions of their intellectual safety in the workplace varied, yet there was a
reveling undertone in the responses, even for Charlotte, who felt intellectually safe with her
manager. Their responses suggested that their workplaces are not respectful or supportive
environments where they, as Black women, feel supported when expressing their unique ideas
and perspectives (Schrader, 2004; Tallapragada et al., 2015).
Findings for Research Question 2
Research Question 2 sought to ascertain the behaviors in which Black women in tech
engage to manage their responses to experiencing behaviors they perceive as discriminatory
based on their race and gender. This section describes those behaviors and actions. The data
analysis revealed three key themes that emerged through the collective experiences of the
participants: (a) self-silencing as a defense mechanism, (b)strategies to navigate perceived
obstacles, and (c) seeking support from formal and informal mentors.
Self-Silencing as a Defense Mechanism
Ten participants expressed that they regularly engage in self-silencing behavior by
actively limiting their verbal contributions in meetings and other instances at work as a form of
protection. Aja explained, “I [spoke] up several months ago and was retaliated against. So I
currently do not speak up. I actively don't speak up, and I just sit there. I don't contribute. It's not
fair, the power dynamics are way off.” Gladys stated a similar response to her experiences of
being repeatedly shut down by her boss. “I know my craft, and I know that my boss doesn't, so I
hold back on what I know. I just don't say anything in most instances.” Harper expressed fatigue

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with getting pushback for her contributions in the workplace. “I do hold back because I don't feel
like some battles are worth fighting. I have tried to say what I need to say in a watered-down
version, and even then, it hasn't necessarily been taken so well.” Charlotte shared her hesitancy
to speak up. “I withhold even when I'm almost certain the thing that they're talking about is not
right. Sometimes,” she continued, “my mental health isn't worth more than to push through…I'm
gonna try to be as agreeable as I can because it's my survival.” Kenzie expressed that she thinks
about when and whether to speak up at work. She stated:
I have to think… is this the right place to make this statement? Is this the right time… Do
I feel like they want to hear what I have to say? So yes, I have held it back because I
think sometimes it might not be received well.
Participants indicated that their self-silencing behavior was a self-protection strategy necessary
to get through their daily experiences at work.
Other participants used different strategies when deciding whether to stay silent at work.
Daphne explained how she limits what she says in her male-dominated environment. “Men tend
to talk more, especially when there's senior leaders in the room. If I don't have anything to say, I
don't talk. I hold back because I don't know how I would reflect on my boss.” Faith expressed
hesitancy, and being careful about what to say and when to say it, but does not embrace fully
self-silencing. She stated, “There should always be some level of trepidation…so yes, I've had
those moments. They are less now because I have a better understanding of the company and
recognizing that I have to always speak with some level of authority.” Isabella acknowledged
that she does not always speak up, but when she does, she speaks up for more than just herself
and from a place of authority. She explained, “I think there's an expectation of me to speak on
behalf [of] people of color, or people who may have disabilities or people in the LGBT plus

72
community. Normally, after I speak, there's an action that comes from it.” Bianca, however,
expressed the opposite experience and focused on how she amplifies her voice instead of
silencing it. She stated, “I felt that for the last couple of years, I always have to yell, I have to
shout the loudest on something that's reasonable. And then we may end up doing, I just had to
shout about it first.” While these experiences vary, there is an undercurrent of differential
treatment to which the participants react. To navigate in their tech workplaces as Black women,
participants employed self-silencing, shouting to be heard, hesitating to speak up, or carrying the
voices of others, suggesting that these experiences are unique to them.
Strategies to Navigate Perceived Obstacles
Participants acknowledged using different strategies to navigate perceived obstacles in
their respective workplaces. Elise explained the importance of having trusted allies in the
company while avoiding gossips who will “weaponize information against you.” She also noted
that documentation was vital. “Start documenting things…wins, conversations, losses, and
everything you tried to do to be successful so you can defend yourself. Have those receipts.”
Harper had a different approach to navigating a workplace she described as toxic for Black
women. She explained, “The way to win is to somehow develop tough skin, and just ignore
everything and be aggressive like they say you are, and do your job and push through. And you
might get rewarded for that.” When facing difficulties at work, Faith described a more internal
tactic. “From a personal perspective, my default is always prayer. And of course, when you are
pressurized, and in times of crisis, you default to what you know, so my faith takes center stage
when I am pressurized.” Isabella expressed how she handles pushback from colleagues in her
company who resist changes related to increasing diversity in the workplace. She explained
having to “go back and forth and deal with the people that are intentionally trying to make your

73
job more difficult” because she is working to increase diversity in her workplace. Isabella noted
that “you have to be prepared for that because it's centered from a place of insecurity and fear...”
These strategies used by participants suggested that they have no other option but to fortify and
protect themselves from work environments where they have experiences that taught them to be
prepared and push through. As the women indicated, these means can include several strategies,
such as praying, actively managing other people's emotions, and documenting everything to
ensure they remain prepared for anything.
Daphne explained her strategy for navigating perceived obstacles by focusing on her
team and making an exit plan. She stated, “I tried to stay positive for the team. But that's not
where I want to be, so in the meantime, I am looking at other options. I'm looking at making my
plan B. That's what keeps me going.” Aja discussed a different approach to navigating her
workplace. “As a Black woman in tech, I don't have the option to not show up the same every
time. I have perfected showing up the same because I have to for my survival.” Charlotte had the
opposite approach and explained how she is motivated by showing up differently and speaking
up about not being pigeonholed. “Tech, it's about newness, and I'm intentional [in] telling
people, I'm not kidding, [I’m] not going to shut up. So it's motivating me to be like, don't put me
in this box, because I'm bigger than this box.” These experiences suggest that these strategies
help Black women survive in their respective tech workplaces.
Seeking Support from Formal and Informal Mentors
All participants discussed experiences with mentors that helped them deal with perceived
discriminatory behavior in the workplace and other issues they were facing over their careers,
both before and in the tech industry. Daphne described how mentorship helped her. “You have to
have the relationships, you have to have someone in the room who mentions your name, you

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have to have one on ones, so that networks within work bring you in. That is how I was guided.”
Elise indicated that she currently has a White male mentor who took an interest in her, which she
did not expect, but he advocates for her when she is not in the room. She noted that her first
mentor in tech was a Black woman who invited her to different events and exposed her to new
networks that helped her make connections. Aja described a different experience leaning on
mentors in her career. She noted that her mentors gave her "advice on how to navigate
relationships, solve conflicts and when to escalate [or] ignore something.”
Harper described her experience finding mentors through tech company-sponsored
employee mentor programs. She explained that her mentors helped her navigate “any challenges"
she had. Harper also stated that she could talk to her mentor about improving her performance. “I
think that really helped me improve certain areas. And then I got put up for promotion, and I
ended up getting [it].” Isabella noted that having a Black woman as a mentor helped her navigate
dealing with discriminatory behavior in the workplace. “My mentor was key," she explained, "I
needed to make sure I leaned on somebody who could hear me and validate what was going on,
and be part of the discussion throughout so that we can navigate how to make the best outcome
we could.”
Bianca, who has never had a formal mentor in her workplace, had the opposite
experience of the other participants. She described the impact on her career of needing a mentor
at work. “I would have risen higher, had I known the etiquette of organizations. I've never had
that experience… It's always kind of figuring it out on your own.” Faith also acknowledged that
she does not have a mentor in her current role, but remarked on the importance of the mentorship
she has had in her career leading up to her job in tech. She explained, “The ability to have
mentors literally helped with the trajectory of my professional career. They helped me navigate

75
landmines. To avoid pitfalls, to avoid a career suicide moves. So they've been very helpful.”
Charlotte explained her experience with a mentor who found her in her tech workplace and
helped guide her:
He immediately saw me and was like, ‘You are doing so much they have no idea.' There
were times when he would call stuff out, and it was so jarring and uncomfortable, but I
needed someone to say, 'Listen, she knows what she's talking about. Just listen to her.’ It
empowered me to advocate for myself. And I was like, oh, this is mentorship.
Ten out of eleven participants indicated that mentorship was a critical factor in helping them
navigate experiences with discriminatory behavior directly or getting them to a place in their
careers where they had the tools to deal with adverse workplace experiences. While not all of the
participants had mentors who were Black women, their experiences indicated that mentorship
helped them survive.
Findings for Research Question 3
Research Question 3 captured workplace policies and practices that facilitate
discrimination against Black women in tech. This section describes the practices and policies the
participants described as impacting them in the workplace. The data analysis revealed three key
themes that emerged through the collective experiences of the participants: (a) unsupportive
middle managers, (b) unclear performance review and promotion processes, and (c) workplace
cultures that enable toxic behavior.
Unsupportive Middle Managers
Seven of the eleven participants discussed workplace experiences with their managers
that negatively impacted them. Aja acknowledged the importance of employees' relationships
with their managers. “A good manager makes everything better; a bad manager is terrible. The

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upper-level management leaves it to middle management to decide how to recognize people…so
if they mess it up, there is no recognition.” Elise expressed a blunter sentiment about managers
in tech. “If you and your manager don’t click, you should start looking.” She indicated that her
experience taught her that middle managers are the gatekeepers in the industry, so the nature of
an employee’s relationship with them is critical. Bianca described an experience that implied her
manager’s lack of trust. “I think the level of micromanaging with the supervisor is very
challenging. I firmly know what I'm doing in my career, and my expertise background, and
relationships should be taken into consideration. And I don't think it is.” Gladys discussed an
experience with her manager, who was also a person of color, that she described as “abusive”
and taxing on her mental health. She said that he “shut me down” in meetings and on several
occasions “he would pull me to the side and say, ‘why did you speak? You are not allowed to
speak.’” These experiences suggest that the participants encountered discriminatory behaviors,
including microaggressions, and were treated differently than their peers.
Another aspect of having unsupportive middle managers that participants described was
managing up. Aja explained, “I'm not managed by people who understand what I do.” Charlotte
also expressed the challenge of having a manager with little experience, “My department
manager, who is also a White woman, I’m managing up with her. She has not had a lot of
experience managing people.” Faith expressed dislike of the overall culture of navigating
internal company politics, including managing her manager. “I hate it so much. It's exhausting. It
is not my favorite thing. Absolutely necessary and I'm trying to learn to do it better. That kind of
managing up, that managing up and out.” These various experiences with managers highlight the
participants’ vulnerabilities as Black women in tech have when unsupportive managers supervise
them.

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Unclear Performance Review and Promotion Processes
Eleven participants described very different performance measurement processes within
their tech workplaces. Some perceived the processes to be vague, nonexistent, or not rigorously
followed. Others thought their respective organization’s performance review and promotion
processes were fair, while a couple were described as fair if one had the right manager. Aja
explained, “I hate to say it, but in tech, it is all about the performance review.” Daphne stated
about the performance assessment process, "[I]t's a pretty fair process in my opinion, it just takes
a lot of time." Elise explained her more nuanced experience with performance reviews. “The
process has been fair because I have a good manager. However, it is also not fair because the
review process is too dependent on managers.” Harper, however, expressed a different
experience. She said, "I don't know how my performance at work is judged. [I]t has left me
confused because I don't really know how my work has been evaluated, even though I'm being
told that I'm doing a good job.” Bianca also shared her experience with an unclear performance
review process and unhelpful feedback. “There's no real process,” she stated. She explained that
the feedback she received was not “instant” or “implementable.” She continued, “Even when I
get feedback, it's like, what am I supposed to do with that? Thanks for sharing.” While these
unclear processes may be detrimental to other employees, they leave Black women especially
vulnerable to the bias of their managers with whom, as several participants discussed, they do
not always share a positive relationship. The system of promotion in tech also emerged as an
obstacle for participants. Jordyn explained how doing the work was not enough to get a
promotion:
I remember having a hard conversation of saying you told me to go out and deliver this
purple pony. Here are three examples of me delivering this purple pony. How are you

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justifying that I'm still not able to move up a level?
Faith explained the process for getting noticed for promotion in tech. “In this industry, you have
to promote your own good work. It is all about political theater. And you have to do that well.
Which means you need to identify even the smallest win and blow that W up.” Bianca explained
a similar challenge with self-promotion in tech. “Selling myself is a challenging activity. It was
draining every day. I think that's one of the things that disadvantages people of color…
particularly women. I wish there would be some magic wand to get rid of that.” Charlotte
indicated that the process of promotion at her company is “evolving.” She alluded to the
potential uselessness of self-promotion that Bianca and Faith acknowledged was necessary in
tech. “I can campaign and put myself out there, but if someone doesn't like you, they don't like
you, and employees still can't get a leg up.” Aja discussed the downside of tech relying on selfpromotion as the formula for employee advancement. “It's not fair because it relies on someone
being savvy and experienced to rise to the top. If you don't know all the resources and levers, and
you're not super politically driven, you're gonna get completely ignored and overlooked.” Harper
shared a similar experience but provided more context into how managers play a role in
perpetuating unfairness in promotion processes. She said:
There isn't a lot of clarity when it comes to your career path. People can do whatever they
want. We don't have enough HR processes in place to prevent bad behavior. People just
join teams and then decide to build empires, so then they just go and bring their friends,
and the other people already on the team don't get promoted. It's almost like people get
promoted based on being friends with the manager [instead of] actual work.
In concert with Harper’s experiences, Gladys explained that self-promotion only sometimes
equates to completed work. She stated, "It's all about promotion… that's why they steal stuff."

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She continued, "Somebody can fluff a whole document and say, ‘I did all of these astronomical
things,’” and no one would know as long as the employee had their “managers buy-in.” Kenzie
expressed a need to focus more on those actually doing the work instead of those talking about
the work. She said, “I don't think that the recognition is necessarily fair. I think that people who
are the doers, and are working in the background, I think… there needs to be a light shined on
them a little bit more.”
The participants described experiences that suggest that most of their companies lacked
clear and effective performance review and promotion processes. These deficient business
practices disadvantage Black women in the tech industry. Participants’ experiences suggest that
such lackadaisical processes enable unfair treatment and allow bias and discriminatory behaviors
to limit Black women’s opportunities and advancement in tech. In addition, participants’
experiences indicated that the current processes allow managers and colleagues to obfuscate
Black women’s contributions and work products. If Black women are not skilled at selfpromotion, their colleagues steal or dismiss their ideas, or managers ignore their efforts.
Work Cultures that Enable Toxic Behavior
Having a toxic culture in the workplace exacerbates the challenges that Black women
face. Isabella explained that the entire tech industry needs more diversity. She said, "One of the
things [that] fuels me is something that makes it challenging for a lot of people and women of
color…is that the technology industry is working towards becoming more diverse, but the
diversity is a challenge.” With most tech companies led by cisgender White men, it can be
difficult for individuals from historically marginalized groups to improve the company culture.
Aja alluded to this when describing her experience. “I don't like that the senior leadership seems
to be so far removed.” She continued, “It feels like the senior leadership team, the people who

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make the broad decisions, really aren't taking any opinions from people who are on the lower
level or who are on the front lines.” Understanding this disconnect is essential in assessing how
tech industry workplace cultures impact Black women. Harper discussed how bias permeates
throughout her company. She explained that the distribution of meaningful projects is unfair and
impacts who management recognizes. "Managers end up deciding [who gets work] based on
who they like and who they want to work with.” Charlotte detailed a similar dynamic in her
company. “There is a lot of nepotism," she explained, “in the sense of, this is my friend, and I'm
loyal, even if they're not great.” This description of an unclear and unsystematic process is
another example of how managers' relationships can impede Black women in tech. Several
participants describe work environments where managers assign work based on whether they
like an employee or consider the employee a friend rather than who has the skill set to do the
work. Their experiences suggest this disadvantages Black women in tech because they are part of
a historically marginalized group that traditionally does not have access to the same networks as
managers who are disproportionately White or male.
Faith described positive aspects of her workplace culture, noting, "I would describe it as a
space in which you have a collection of some of the brightest minds I've ever experienced.”
However, she also acknowledged that the workplace culture is “cutthroat and aggressive.”
Daphne, who also described her company’s culture as “cutthroat, backstabbing, [and there is] no
team work,” provided insight into how colleagues in these environments behave. She said, “They
hear you talk and if it's a good idea, people will just steal it and regurgitate it, especially if it's a
senior level [manager] in the room. So it's a little frustrating.” Gladys expressed a similar
experience that further described the toxicity of her tech workplace culture. She explained,
“There's a lot of backstabbing, you're always watching your back. At any given moment, it’s

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like, you get past everyone that has a gun and you forget the person in the tree with the bazooka.
You're always on guard.” The experiences described by participants suggest that many work in
toxic cultures that impede their opportunities and growth in tech.
Summary
The participants' experiences indicated that they perceived behaviors in the workplace as
discriminatory. This discrimination impacted their interactions with colleagues and managers
and was perceived as embedded in their tech companies' practices and policies. Black feminist
theory provides a framework that recognizes that Black women have different experiences that
are shaped by race, gender, and class. This creates similarities in experiences that generate
collective knowledge that disrupts oppressive systems that may limit them (Collins, 1990). Each
participant described challenges that they faced in the workplace that they perceived as subtle
forms of discrimination related to their race and gender. As a result of their experiences, they
developed strategies to navigate their environments and survive, or in some cases, changed
employers. The findings indicated that their membership in a historically marginalized group in
tech has limited their opportunities for recognition and promotion. It also suggested that others'
subtle discriminatory behaviors stunt their ability to make meaningful and impactful
contributions to tech. Participants were not asked directly about discrimination or race. However,
they all discussed experiences where they perceived that their race or gender was centered. Their
experiences indicated they could not escape their historically marginalized status in their
workplace because it impacted everything, from pay to whether they spoke up in a meeting. It
was also reflected in the relationship some participants had with their managers and how the
systems of recognition and promotion impacted others.

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Subtle discrimination is exigent because it lingers just under the surface, and permeates
environments, while silently choking the enthusiasm, creativity, contributions, and feelings of
value and worth out of those who encounter it on a regular basis. Despite being subjected to
microaggressions, unfair treatment, and other subtle discriminatory behaviors in several aspects
of their job, daily and multiple times a day, the participants' experiences indicated that they
persist by continuing to work in the tech industry. They used strategies such as self-silencing and
leaning on their mentors to navigate perceived hostility in their workplaces or push through when
obstacles seemed unsurmountable. Participants also described how they used their existence in
tech to help others through actions such as mentoring other Black women, being a good manager
for their team, or pursuing leadership positions to help change their companies from the inside.
While not all of the participants were undertaking these actions, their reluctance to do more is
warranted. The added stress participants described that results from working in tech are
cumulative and can take an incalculable toll on Black women's physical and mental health. In
addition, subtle discriminatory behaviors, such as unfair treatment and macroaggressions, are not
always easy to identify or document and do not benefit the same statutory prohibitions as blatant
discrimination. The participants' perceptions in this study provide a critical window into tech
workplaces and the experiences of those who are among the most marginalized and have the
least access. They also create an opportunity to provide insights into solutions that can help
improve work conditions for Black women and all other tech employees who may be suffering
under the weight of subtle discriminatory behaviors in the workplace.

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Chapter Five: Discussion
This study examined the workplace discrimination Black women face in the tech
industry. After a thematic analysis of participants’ interviews about their workplace experiences,
this chapter unveils and synthesizes the significance of the study’s findings and bridges the gap
between theory and practical application. This chapter begins with a discussion of the study’s key
findings and provides recommendations for practice. Additionally, in recognition of the growing
body of research related to Black women in STEM professions, this chapter concludes by
offering recommendations for further research.
Discussion of Findings and Related Literature
The study’s findings address three research questions that examine Black women in
tech’s perceptions of workplace discrimination, how they cope with unfair or adverse treatment,
and the policies and practices that enable workplace discrimination. The findings also support the
tenets of Black feminist theory, which asserts that racism and sexism create recurring patterns of
experiences and group knowledge of Black women with diverse life experiences (Collins, 2000).
They also purport the BFT concept that Black women empower themselves by resisting negative
perceptions and confronting and dismantling structures of racial and gender oppression (Collins,
2000; Taylor, 1998). The data generated three findings highlighting how participants perceive
discriminatory behaviors in the workplace and employ coping strategies to navigate them. They
also illuminate how tech companies’ policies and practices enable perceived discrimination to
pervade their workplace cultures. By discussing these findings, this study expands the body of
research on Black women’s experiences in the tech industry, and the impact perceived racial
discrimination has on the workplace.
Black Women in Tech Experience Behaviors They Perceive as Discriminatory

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Existing literature about subtle racial discrimination asserts that it can constitute
behaviors that are difficult to identify and harmful to its targets, who tend to be those with
different observable or cultural characteristics than the offender (Clark et al., 1999; Jones et al.,
2016; Rucker et al., 2014). Research also indicates that most women of color, approximately
50%-75%, report experiencing discriminatory treatment (Lee et al., 2019). The findings of this
study indicated that the 11 participants, who identified as Black, African American, or Biracial,
all experienced behavior in their tech workplaces that they perceived as discriminatory.
Specifically, participants experienced behaviors from colleagues and supervisors that align with
the literature's definitions of incivility, unfair treatment, and microaggressions (Banks & Horton,
2022; Holliday et al.; Porath & Pearson, 2012; Sue et al., 2008). These behaviors included
questioning their intelligence, abilities, and whether they belonged in the workplace, and
devaluing their technical competence (Holliday et al., 2020; Kim & Meister, 2022).
The findings also suggested that their perceived experiences of microaggressions and
unfair treatment triggered strong emotions. Participants described feeling undervalued or
dismissed after incidents they perceived as discriminatory based on their race and gender, and
behavior they did not observe being directed towards their non-Black or male peers. Most
participants did not report these discriminatory incidents to their employers. The choice to not go
to human resources supports research by Ruggiero and Taylor (1995), whose study data
suggested that historically marginalized groups tend to internalize mistreatment and minimize its
impact. Responding to regular exposure to discrimination, participants said they lacked
intellectual safety. As a result, they did not believe they worked in respectful and supportive
environments when they expressed their unique ideas and perspectives (Schrader, 2004;
Tallapragada et al., 2015).

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Black Women in Tech Use Multiple Strategies to Cope with Workplace Discrimination
Data from this study indicated that Black women in tech employ several strategies to
protect themselves after they experience behaviors that they believe are adverse or unfair.
Participants suggested that these responses include self-silencing, developing their own ways to
navigate obstacles, and seeking support from mentors. Discrimination is part of Black
Americans' daily lives, and repeated racist incidents increase their stress levels (Joseph et al.,
2021; Landrine & Klanoff, 1996). These experiences trigger interpretations and feelings that
require coping strategies to help mitigate mental and physical health harms (Allen et al., 2019;
Fix et al., 2020; Harnois, 2022; Keating et al., 2021; Operario & Fiske, 2001). As conscious
actions, the coping strategies participants employed, such as connecting with a mentor, or selfsilencing in a meeting to avoid being shut down or dismissed by a manager, helped them deal
with racial discrimination (DeCuir-Gunby et al., 2020; Shim, 2021).
The participants all discussed the number of ways they engaged in self-silencing or
holding back thoughts, opinions, or other contributions in the workplace as a form of protecting
themselves from adverse or unfair treatment. The literature, however, suggested that participants’
behavior is a form of "devious silence" (Khan et al., 2020, p. 175), defined as individuals
withholding relevant information at work to harm their organizations, peers, or managers. In
their study, Howard et al. (2020) acknowledged that deviant silence was a reaction to
experiencing discrimination in the workplace. The notion that the participants’ self-silencing to
protect themselves at work is deviant and harms the workplace ignores how the workplace or a
person’s colleagues or supervisors enables the discrimination that precedes employees’ silence.
The literature also suggested that women with salient gender identities were more likely
to confront perpetrators when they perceived subtle gender discrimination (Wang & Dovidio,

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2017). However, most of this study's participants did not employ that coping strategy. While
some participants leaned on mentors and sought advice on responding to incidents, they
indicated that their experiences steered them away from direct confrontation, which may be
related to the intersection of their racial and gender identities. This response aligns with data
from Sisco (2020) that suggested that Black women have exhibited resilience to racial bias
through several means, including self-preservation strategies and seeking out mentorship and
relationship building. The study's data did not indicate that participants planned to flee the tech
industry to cope with racial and gender bias. Participants' decision to continue working in tech
aligns with research data from Sendze (2020), which suggested that Black women remain in
STEM professions for multiple reasons, including their high level of agency and confidence and
drive to pursue opportunities to innovate and grow their careers.
Tech Business Cultures, Processes, and Middle Managers Aid Workplace Discrimination
This study's findings suggested that tech companies have work cultures that enable toxic
behaviors and allow unsupportive middle managers to act as gatekeepers to their employees.
They also indicated that tech relies on vague performance review and promotion processes to
make critical personnel decisions. These findings align with data from Lui (2020), which
indicated that organizational policies and actions can facilitate racial discrimination. The
participants, all members of a historically marginalized group, described experiences that they
believe put them at a disadvantage. Research by McCord et al. (2017), whose study data
indicated that Black employees perceived more mistreatment than other workers of color,
supports this finding.
The findings also specified that performance reviews and promotion processes did not
provide meaningful, actionable, timely feedback and provided no clear path for advancement.

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Participants expressed that these vague processes allowed managers who controlled work
assignments too much discretion while requiring little, if any, justification for their decisions at
most tech organizations. This data was in concert with existing research that suggested
workplace policies and actions can include racial and gender disparities in the assignment of
work and how employees are rated by management (Eaton et al., 2020; King et al., 2012).
Additionally, participants described tech workplace cultures that were cutthroat, competitive
environments, where colleagues steal ideas, where promoting one's work appeared to be more
important than completing said work, and where everyone was chasing advancement. These
findings aligned with existing research that indicated that in environments where people of color
face barriers to impactful work assignments, promotions, endure toxic work cultures, and inept
organizational processes can be detrimental to their careers (Fernandez & Campero, 2017;
Raferty, 2020).
Recommendations for Practice
In the tech industry, Black women comprise less than 2% of the workforce and face
several obstacles that impact their work environments and professional experiences. The findings
of this study aligned with existing research that suggested Black women in the tech industry
experience a disproportionate amount of racial and gender discrimination (Avery et al., 2008;
Daniels & Thorton, 2020; Hall et al., 2012; Maddox, 2013, Okechukwu et al., 2014; Yang,
2021). This data indicated that Black women in tech experience behaviors that they perceive as
discriminatory and align with what the literature defines as subtle and thus difficult to assess, yet
still harmful (Harnois, 2022; Jones et al., 2016; Liu, 2020; Operario & Fiske, 2001).
Additionally, this data suggested that Black women employ several self-protective strategies to
cope with the discrimination they encounter at work, including seeking out and leaning on

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mentors outside of their workplace. The data also alluded that tech companies’ toxic cultures,
unsupportive managers, and ineffective processes aid behaviors that participants perceive as
discriminatory. The next sections includes proposed recommendations that the literature suggests
address the findings of this study.
Recommendation 1: Industry-Supported Tech Mentorship Nonprofit Organization
The study’s findings suggest that Black women in tech workplaces experience
microaggressions and unfair treatment and rely on several self-protective coping strategies to
navigate discriminatory behavior. Among their identified coping mechanisms, seeking and
leaning on mentors to navigate incidents they perceive as discriminatory appeared to yield
multiple professional and personal benefits. Workplace discrimination drains the targets’ energy
and impedes their performances, and having access to culturally responsive mentors can help
mitigate these barriers (Corneille et al., 2019; Kim, 2011; Xia et al., 2019). While individual
mentoring programs in their workplaces may be ideal, there is no guarantee that each company
will have a quality program. A quality mentorship program can provide meaningful and
enriching learning experiences that effectively use the mentors' and mentees' time (Billet, 2003).
However, Black women face challenges securing quality mentorship experiences in their
workplace, even where mentor programs exist (Horton, 2023).
One recommendation to increase access to formal mentorship opportunities is creating a
3-year pilot mentorship program that Black women can easily access in the tech industry. Using
an existing nonprofit organization based in Silicon Valley, with funding from tech companies, the
program would be open to all women in tech seeking mentors. However, the pilot would
specifically focus on Black women in tech. The pilot program would include training for the

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mentors, assistance from the sponsoring organization to facilitate the program and provide space
for training, and in-person and virtual options for connecting mentors and mentees.
Creating a quality mentorship pilot outside of individual tech companies will ensure that
the program is high-quality, intentionally targets Black women, and avoids various organizations'
internal politics that may undermine or underfund the program. Additionally, an evaluation of the
pilot would provide data about the need for improvements and the benefit of scaling up the
program to create a separate mentorship organization that includes other historically
marginalized groups in the tech workforce. Finally, companies can support the organization by
donating money to the program. Creating a meaningful way to support mentorship for women in
tech allows tech companies to check a box on supporting diverse tech workforces without
creating an internal program. However, a successful pilot mentor program can also serve as a
model for tech companies that want to establish new or improve an existing mentor programs.
Recommendation 2: Internal Talent Incubator Lab
Despite Black women's challenges while working in the tech industry, they still want to
work there. Data from this study suggested that most participants liked their work, even when
they did not like their company, its processes, or their direct supervisor. A pattern in the findings
indicated the participants had unsupportive middle managers whom participants believed
undervalued them and dismissed their thoughts and opinions. The managers' behaviors
undermine the participants' contributions to their companies and constrain their ability to
advance. While the internet offers opportunities, it contains the same bias that limits offline
entrepreneurial opportunities for women (Dy et al., 2017). Additionally, recognizing that bias
exists in business accelerator programs, which are competitive and rely on the judgment of
investors, an internal company incubator program designed to provide entrepreneurial

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opportunities to employees from historically marginalized groups can provide valuable
resources, training, and other tangible things needed to grow talent (Kapinga et al., 2018; Lange
& Johnston, 2020).
To implement this recommendation, existing research about past business incubator
programs can support implementation by working with at least two tech companies to develop a
model internal talent incubator program for women in tech with an intentional recruitment effort
that targets Black women. With a design informed by the research, the program would meet the
real-world needs of the business owners, while providing the program participants with
opportunities, outside of their regular company hierarchy, to work on impactful projects and tap
into their creativity. The pilot would also help the tech industry retain talent and, possibly, scale
up new products or improve processes based on what their employees develop. This
recommendation could be implemented by working with two or three tech companies. The
program would have a specific time limit, such as 6 or 12 months, and increase opportunities for
the participants to engage with each other and their respective networks regularly.
Recommendation 3: Reinvent Middle Management Training and Pipeline
This study’s data indicated that most of the participants did not feel supported by their
managers. Lack of support ranged from ignoring or shutting them down in meetings, engaging in
behaviors participants perceived as discriminatory, or treating them differently than their male
and non-Black colleagues. As the gatekeepers responsible for their employees’ work
assignments, performance reviews, and paths to promotion, middle managers are a critical part of
the tech industry work environment. Additionally, research has suggested that individuals’
management styles differ based on their characteristics but are not fixed and can be improved
(Jungert et al., 2022; Hardré & Reeve, 2009). The pliability of how managers do their jobs is

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essential because it impacts employees’ motivation, work product, well-being, and commitment
to the organization (Hardré & Reeve, 2009; Malek et al.,2018). Improving individuals’
management capabilities also benefits their employers by ensuring their employees, who are
valuable resources, are in environments where they feel valued and give their best work in
service of their companies’ goals and bottom lines (Barba Aragon & Valle, 2013).
Data from this study suggested that tech industry workplaces could benefit from
managers with more training that would improve their abilities to create more supportive
environments for their employees. Participants reported behaviors from managers that led them
to self-silence and strained their cognitive capacity by forcing them to navigate obstacles they as
supervisors created or permitted. To ensure that managers have the tools to create supportive
environments where employees feel intellectually safe and employ fewer protective coping
mechanisms, this recommendation would create a 3-year initiative to study and then work to
reinvent the tech middle management pipeline. The project would begin by getting buy-in from
at least three tech companies of different sizes to agree to participate in the pilot and commit to a
level of funding for the duration of the initiative. The project's first phase would include
academic research and a systematic assessment of the participating companies’ current middle
management recruitment, selection, training, oversight, and promotion policies and practices.
The second phase would include commissioning a working group of relevant stakeholders and
tasking them with a mandate to use the data to make recommendations on how to dismantle and
rebuild the pilot companies’ management pipelines. Phase three would operationalize the
working group's recommendations, study the impact on the companies, and issue a report at the
end of year three. If the initiative produces measurable positive changes to the companies, phase

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four would include using media to highlight the program's success and pitching it as a model for
other tech companies.
Limitations and Delimitations
While this study employed necessary measures to ensure credibility and trustworthiness,
some factors were out of the researcher's control, which resulted in limitations and delimitations
on this research (Creswell & Creswell, 2018). First, the data gathered was self-reported and
limited to the participant's perception of others’ behaviors and the thoughts and feelings triggered
by that behavior. Additionally, the study was intended to assess the participants' individual
experiences, so their bias and their singular view of their respective workplaces were inherent in
their description of events. Although the study illuminated aspects of these participants'
workplace experiences, it cannot control variables such as trust and motivation or the accuracy of
the participants' recall of interactions. The study also focused on Black women who work in the
tech industry and thus is limited to this one sector and may not be immediately generalizable to
other industries or tech industry employees of other gender expressions, races, cultures, and
ethnicities.
The study’s delimitations included choices related to the study population, scope, and
conceptual framework. Women in the United States who identify as Black, African American or
Biracial and work in the tech industry comprised the study's population. This study limited the
definition of the tech industry to companies based in the United States that produce products that
collect, distribute, and manage large data sets and develop and use algorithms, artificial
intelligence, software, and other internet-based applications and features as part of their business.
This definition may not encompass all companies in such a broadly based sector. Additionally,
positionality and philosophical worldview affected this study's research design and theory

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selection. Further, the study's conceptual framework confines the assessment to the individual
perception of employees’ experiences. It thus does not examine the perspective of managers,
company leadership, or existing organizational policies or procedures.
Future Research
As the tech industry continues to make efforts to increase the diversity in their workforce,
understanding the challenges Black women in tech face can provide insight into workplace
obstacles that impact individuals from underrepresented groups. This study adds to the body of
literature examining the experiences of Black women in STEM fields and in corporate America.
Despite existing research that illuminates the difficulty women face while pursuing STEM
education and working in STEM fields, there is a dearth of research that focuses specifically on
the tech industry or Black women who work in tech. Additional research focusing on tech
workplaces and their distinctness from other corporate environments may provide additional
awareness of how organizational structures affect their ability to recruit, hire, advance, and retain
employees from underrepresented groups.
Tech is a broad and trillion-dollar industry producing advanced products upon which our
society is becoming more dependent. Despite all of the industry’s innovation, it continues to be
dominated by one racial group and gender. Further studies can explore the organizational
structures that perpetuate this cycle in tech’s workforce, and the findings could inform strategies
to dismantle those structures. Finally, this study indicated that participants enjoyed their work
and could recall positive aspects of their companies. Future research could examine these aspects
of Black women’s experiences in tech and extrapolate common themes that inform
recommendations for practice. Such studies could provide a roadmap of policies and practices

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that facilitate positive work environments for underrepresented employees, increase the diversity
of their workforce, and improve their overall productivity levels.
Conclusion
This study contributes to the literature on Black women’s experiences in STEM fields
within the framework of Black feminist theory. Exploring how Black women exist in and
navigate through the technology industry can illuminate potential paths forward to ensure that its
workforce is as diverse as the communities from which it obtains its profits. Tech, a trillion
dollar economic engine that purports to be on the cutting edge of innovation and promises and
sells convenience, connection, and tools that facilitate evolution and progress, should be raceneutral. The reality, however, is that companies within the industry have created homogenous
work environments that are not race-neutral, bias-free or objective. As a result, they have
manufactured an inequitable industry that hobbles the ability of their organizations to foster
innovation and connection amongst their respective employees. Despite spending billions on
diversity, equity and inclusion initiatives over the past 3 years, the industry’s workforce is still
dominated by one gender and one racial group. In addition, the findings in this study indicated
that companies’ policies and practices aid the behaviors Black women perceive as discriminatory
in their workplaces. This should raise questions about whether the tech industry’s existing
organizational structures and leadership are capable of attracting, retaining, and elevating the
racially and gender diverse talent needed to level the uneven playing field they built.
The participants in this study chose the tech industry for several reasons, and most
embraced their challenging and innovative work with enthusiasm and determination. However,
the obstacles they faced, including dealing with microaggressions, repressive managers,
inefficient workplace policies and practices, undermined their work products, taxed their

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cognitive resources, and exhausted their spirits. Though these findings are gleaned from the
perceptions of 11 Black women who work in different organizations in tech, their experiences
may be the red flags needed to alert the industry to broader problems related to deficient
organizational structures, toxic workplace cultures and obstructive middle management
personnel.
Understanding how the tech industry’s workplaces are falling short by examining the
experiences of its most underrepresented employees is critical because of the products the
industry is developing and unleashing on the world. The tech mantra of “move fast and break
things” has a different meaning when the things that are being broken are communities,
democracies, and society. The mantra is chilling when it leads to self-driving cars on public
streets that cannot recognize people of color, facial recognition software used by law
enforcement that misidentifies Black people, or artificial intelligence that recreates systemic
racism being thrust on everyone. The findings of this study support the existing literature that
suggests that the tech industry has systemic racial bias and gender bias problems. Black women
sit at the intersection of both, and experience consequences unique from their Black male and
White women colleagues (Brown et al., 2016; Charleston et al., 2014; Crenshaw, 1999; Johnson
et al., 2019). The study's findings support further examination into how racial and gender
discrimination in tech companies impact their existing employees, influence efforts to increase
diversity in their workforce, and affect the products and services the industry produces. It may
also force broader conversations and spur additional research about who is breaking what, the
societal costs of that destruction, the inequity in who gets devastated, and who bears the
responsibility for restoring what has been lost.

96
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Appendix A: Interview Protocol
The following research questions guide this study and attempt to assess workplace experiences
Black women have in the tech industry. The following research questions will guide this study:
1. What workplace behaviors do Black women experience in the tech industry that they
perceive as discriminatory based on their race and gender?
2. How do Black women cope with workplace experiences that they perceive as adverse
or unfair?
3. What workplace policies or practices enable discrimination against Black women in
the tech industry?
Participants: 11 women who identify as Black, African American, or Biracial and are currently
employed in the tech industry or have been employed by in the tech industry withing the past 12
months.
Introduction to the Interview:
Hello, and thank you for agreeing to participate in this study about the Black women’s
experiences in tech workplaces. The purpose of this study is to assess the workplace experiences
of Black women in the tech industry, highlight any patterns that impact Black women in tech,
and propose solutions based on what is found in the data. Before we get started, I would like to
remind you that your participation in this study is voluntary, and you can leave at any time, or
stop if you feel uncomfortable. Additionally, all identifying information, including your name,
your employer, or former employer, and any other identifying information, will be kept
confidential, and not made public.

123
I have 16 main questions, but I may ask a few additional follow-up questions to seek clarity, or
dig deeper into your experiences. To ensure that I collect accurate data, I like to record my
interviews with the camera on. Do you consent to conducting this interview with the camera on?
If no, do you consent to conducting this interview with the camera off? Do you consent to having
your video and audio recorded during this interview?
Again, thank you for agreeing to participate in my study. Do you have any questions for me
before we begin?
Great, let’s get started!
Table 2
Interview Protocol Crosswalk
Interview Questions Potential Probes RQ Addressed
Key Concept
Addressed
1. How would you
describe your current
position and your
general daily activities
at work?
1 Black women in tech
2. What led you to work in
the tech industry?
Did you seek out an
opportunity in tech or
were you recruited?
1 Black women in tech
3.What aspects of your job
do you enjoy?
Can you describe
things about your
company that you like?
1 Black women in tech
4. Can you describe aspects
of your job that you do not
like?
Can you describe
things about your
company that you do
not like? 1 Black women in tech
5. How do employees in
your workplace access
professional mentors?
Have you had an
experience with a
workplace mentor?
1 Experiences at work

124
Can you describe how
it impacted your
career?
6. How would you describe
the system of recognition
and the system of
promotion in your
workplace?
Do you think these
processes are fair?
Can you describe why
you feel that way? 3 Sexism/Discrimination
7. How do you feel at work
when you express your
thoughts, feelings, or
opinions?
Have you ever held
back your thoughts,
feelings or opinions
out of without fear of
retribution from coworkers or
supervisors? 3 Experiences at work
8. Can you provide me with
examples of how your
performance at work is
judged?
Who monitors your
work performance?
How was this
information relayed to
you? 3 Experiences at work
9. What challenges, if any,
have you had in the
workplace?
How did these
experiences make you
feel?
How were you able to
navigate the(se)
situation(s)?
1 Experiences at work
10. When you hear the term
intellectually safe, what
does that term mean to you?
Do you feel
intellectually safe at
work?
Can you explain why
you feel this way? 3
Self-evaluation and
resisting negative
perceptions
11. Can you describe any
interactions, at work,
positive and or negative,
that have made you feel
singled-out?
Can you describe the
emotions that you felt
during these
interactions?
Was there an impact
on you work? 1 Experiences at work
12. Can you describe a time
that you were excited about
a project or assignment at
work?
How often do you get
excited about your
work? 2
Self-evaluation and
resisting negative
perceptions

125
13. Can you describe a time
when you empowered at
work?
How often do you feel
empowered at work?
2
Self-valuation and
resisting negative
perceptions
14. How would you
describe your company’s
workplace culture?
How are people’s
differences (race,
culture, religion,
gender identity, etc.)
acknowledged?
2 Experiences at work
15. What opportunities
exist inside or outside of
your workplace that allow
you to interact with other
Black women who work in
tech?
What barriers exist that
support (or limit) (or
prevent) your
engagement in these
opportunities? 3
Activism to dismantle
discrimination.
16. How would you change
your workplace to increase
the number of Black
women who work there? 3
Activism to dismantle
discrimination
Conclusion of the Interview:
Thank you for agreeing to participate in this study, and for helping me gather important data by
sharing your workplace experiences. Your willingness to share your experience will help inform
my study, and may also inform specific solutions that may improve tech industry workplaces for
all employees. As I stated, your name and all identifying information will be kept confidential.
Again, thank you for your time, and your willingness to be open. I understand that doing so is
not always easy, and I appreciate your participation in my research. Please let me know if you
have any questions.
Thank you.

Abstract (if available)

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Asset Metadata

Creator McKinley, Shannon L. (author)

Core Title Black women in tech: examining experiences in tech industry workplaces

School Rossier School of Education

Degree Doctor of Education

Degree Program Organizational Change and Leadership (On Line)

Degree Conferral Date 2023-12

Publication Date 11/17/2023

Defense Date 11/02/2023

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

Tag Black feminist theory,black women,Black women in tech,OAI-PMH Harvest,tech industry,technology industry workplaces,workplaces discrimination

Format theses (aat)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Datta, Monique (committee member), Maddox, Anthony (committee member), Ott, Maria (committee member)

Creator Email shanmckinley@gmail.com,smckinle@usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-oUC113774576

Unique identifier UC113774576

Identifier etd-McKinleySh-12478.pdf (filename)

Legacy Identifier etd-McKinleySh-12478

Document Type Dissertation

Format theses (aat)

Rights McKinley, Shannon L.

Internet Media Type application/pdf

Type texts

Source 20231120-usctheses-batch-1107 (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.

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