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Content may be subject to copyright.
Gender Bias Against
Women of Color in Science
Double
Jeopardy?
Joan C. Williams
Distinguished Professor
Hastings Foundation Chair
University of California,
Hastings College of the Law
Katherine W. Phillips
Paul Calello Professor of Leadership & Ethics
Senior Vice Dean
Columbia Business School,
Columbia University
Erika V. Hall
Assistant Professor of
Organization & Management
Emory University
Goizueta Business School
Published online at www.worklifelaw.org.
© 2014 Joan C. Williams, Katherine W. Phillips & Erika V. Hall
1
Gender Bias Against Women of Color in Science
Table of Contents
Executive Summary ..........................3
Introduction ...................................9
Prove-It-Again ................................ 11
Tightrope .....................................18
Maternal Wall................................ 28
Tug of War................................... 35
Bias that Does Not Fit the
Four Patterns Template .................... 45
Conclusion .................................. 48
Bias Interrupters ............................ 49
Appendix .................................... 53
Bibliography................................. 54
Table of Contents
This material is based upon work supported by the National
Science Foundation under Grant Number (1106411).
Any opinions, ndings, and conclusions or recommendations
expressed in this material are those of the author(s) and do not
necessarily reect the views of the National Science Foundation.
Gender Bias Against Women of Color in Science
Executive Summary2
I found growing up in India…there
seemed to be less discrimination….
I found that it was far more here
than back home, which may come
as a surprise to you.
– Asian, Immunology
Gender Bias Against Women of Color in Science
Executive Summary 3
THE PAUCITY OF WOMEN IN SCIENCE HAS BEEN
documented over and over again. A 2012 Report
from the President’s Council of Advisors on Science
and Technology reported that a decit of one million
engineers and scientists will result in the United States
if current rates of training in science, technology, math,
and engineering (STEM) persist (President’s Council
of Advisors on Science and Technology, 2012). It’s not
hard to see how this hurts the United States’ competitive
position—particularly if women in STEM meet more
gender bias in the U.S. than do women elsewhere,
notably in India and China.
The conventional wisdom is that women haven’t
progressed in careers in STEM due to the pull of children
and early choices not to pursue math and science careers
(Moss-Racusin, Dovidio, Brescoll, Graham, & Handelsman,
2012). Some studies conclude that the relatively low
percentage of women stems from these factors and “is
not caused by discrimination” in STEM (Ceci, Williams, &
Banett, 2009; Ceci & Williams, 2011; Ceci et al., 2011).
Yet three recent studies found that gender bias also
plays a role. One found that, even when math skills were
identical, both men and women were twice as likely
to hire a man for a job that required math (Reuben,
Sapienza, & Zingales, 2014). “In some situations up to
90% of the time when a mistake was made, it was made
in favor of the man,” commented Dr. Ernesto Reuben,
one of the study’s co-authors (University of Cincinnati,
2014). A second study found that, in academic
laboratories in elite universities, male (but not female)
scientists employed fewer female than male graduate
students and post docs (Sheltzer & Smith, 2014). A
third double-blind randomized study gave science
faculty at research-intensive universities application
materials of a ctitious student randomly assigned a
male or female name, and found that both male and
female faculty rated the male applicant as signicantly
more competent and hirable than the female with
identical application materials (Moss-Racusin, Dovidio,
Brescoll, Graham & Handelsman, 2012).
These studies are part of a much larger literature on
gender bias: experimental social psychologists have
documented bias over and over again since the 1980s.
The present study begins from an extensive review of
this literature, which documents four distinct patterns:
1. Prove-It-Again. Women often have to provide
more evidence of competence than men in order
to be seen as equally competent (Eagly & Mladinic,
1994; Foschi, 1996; Foschi, 2000). This descriptive
stereotyping (Heilman, 2001) reects the perceived
lack of t (Heilman, 1983) between being a woman
and being a scientist (Nosek, Banaji, & Greenwald,
2002; Moss-Racusin, Dovidio, Brescoll, Graham &
Handelsman, 2012).
2. The Tightrope. Women often nd themselves
walking a tightrope between being seen as too
feminine to be competent—or too masculine to
be likable (Cuddy, Fiske, & Glick, 2004; Fiske,
Xu, & Cuddy, 1999). The Tightrope reects
prescriptive stereotyping (Heilman, 2001), and
stems from the fact that science is seen as requiring
masculine qualities—but women are expected to
be feminine. Thus women often nd themselves
pressured to take on dead-end roles, from acting
as administrative assistants to being expected to
mentor everyone else’s students in addition to their
own (Allen, 2006). Women also often face backlash
for behaving in stereotypically masculine ways, such
as being assertive (Prentice, & Carranza, 2002),
angry (Brescoll & Uhlmann, 2008), or self-promoting
(Rudman, 1998).
3. The Maternal Wall. By far the most damaging form
of gender bias is triggered by motherhood. Maternal
wall bias includes descriptive stereotyping that
results in strong assumptions that women lose their
work commitment and competence after they have
children (Correll, Benard & Paik, 2007; Cuddy, Fiske,
& Glick, 2004), as well as prescriptive stereotyping
that penalizes mothers who remain indisputably
committed (Benard & Correll, 2010).
4. Tug of War. Sometimes gender bias against women
fuels conict among women. This stems from the
fact that women as well as men are biased against
women in traditionally masculine domains (e.g. Moss-
Racusin, Dovidio, Brescoll, Graham & Handelsman,
2012). In addition, studies show that women who
experience discrimination early in their careers tend
to distance themselves from other women (Derks,
Ellemers, van Laar, & de Groot, 2011; Derks, van Laar
de Groot, 2011). Commonly this is called the “queen
Executive Summary
Gender Bias Against Women of Color in Science
Executive Summary4
This research is unusual in that it bridges the gap between
experimental social psychologists’ labs and actual
workplaces—and because it examines gender bias among
women of color as well as White women. The current body
of social psychological work on gender bias has focused
almost exclusively on the experiences of White women,
leaving the major question of whether these four distinct
patterns of bias extend to women of color unanswered.
This report adds to a small existing literature on women
of color in STEM. The classic report, The Double Bind:
The Price of Being a Minority Woman in Science, was
written in 1976; it reports many of the same patterns of
bias documented by this report (Malcolm, Hall, & Brown,
1976). Much of the subsequent research has focused
on undergraduates or graduate students rather than
science professors, who are the focus of this report.
(For recent examples, see Ong, Wright, Espinosa, &
Oreld, 2010; Espinosa, 2011; Reyes, 2011; Ong, Wright,
Espinosa, & Oreld, 2011; O’Brien, Blodorn, Adams,
Garcia, & Hammer, 2014.) One of the rare studies that
compares White women scientists with women scientists
of color found an important dierence, namely that
the White women reported higher levels of inuence in
their departments than did the women of color (Settles,
Cortina, Malley, & Stewart, 2006). Another study of a
major research university found that 43% of women of
color academics felt under close scrutiny, as compared
with 33% of White women and 18% of White men, and
that women of color were also more likely (77%) to report
that they felt they had to work harder to be perceived as
legitimate than White women (58%) or White men (46%)
(Hollenshead & Thomas, 2001).
We interviewed sixty scientists who were all women
of color. Women of color face “double jeopardy”
because they encounter race as well as gender bias
(Epstein, 1973; Almquist, 1975). This study explores
how the experience of gender bias diers by race. We
bee” syndrome and attributed to the personality
problem of an individual woman, but this problem
often signals gender bias in the environment.
Each of these patterns has been documented repeatedly.
STEM elds provide fertile ground for bias for at least
two reasons. First, studies of tokenism document that
bias tends to occur more often when women make up
less than 15% – 20% of a given eld, which is common
in many elds of science (although no longer in biology)
(Kanter, 1977a, 1977b). Second, an inuential study by
Emilio Castilla and Stephen Benard found that bias is
more common in elds, like science, that see themselves
as highly meritocratic (Castilla & Benard, 2010).
This report asks a long-standing question: do
the patterns documented in experimental social
psychologists’ labs reect what is actually occurring
at work for women in the STEM elds? (Mitchell &
Tetlock, 2006). The answer is yes. Gender bias exists,
and it exists for women of color: 100% of the sixty
scientists interviewed for this study reported
encountering one or more of these patterns of
gender bias, based on interviews in which we simply
described experimental ndings and asked women
scientists, “Does any of that sound familiar?” (An earlier
study found that 97% of the Black women interviewed
were aware of negative stereotypes of Black women,
and 80 percent had been personally aected by them
(Jones & Shorter-Gooden, 2003).
100% of the sixty scientists
interviewed for this study reported
encountering one or more of these
patterns of gender bias.
Gender Bias Against Women of Color in Science
Executive Summary 5
4. Tug of War. Over one-half (55.3%) of scientists
interviewed reported Tug of War patterns. Although
three-quarters (75.5%) of those surveyed reported
that their female colleagues supported each other,
several Tug of War patterns emerged. About one-
half (51.4%) of the scientists surveyed felt that
“some women [scientists] have ‘just turned into
men,’” while 41.7% agreed with the statement that
“some women just don’t understand the level of
commitment it takes to be a scientist.”
5. Sexual harassment. Over one-third (34.5%) of those
surveyed reported sexual harassment.
In addition to these ndings, our studies began to
document how the experience of gender bias diers for
women of dierent racial groups. Some major ndings:
1. Prove-It-Again is more common for Black women
than for the other three groups of women:
Black women (76.9%) were more likely than other
women to report having to provide more evidence
of competence than others to prove themselves
to colleagues (Latinas: 64.5%; Asian-Americans:
63.6%; White women: 62.7%).
2. The stereotype that Asians are good at science
appears to help Asian-American women with
students—but not colleagues. The stereotype
of Asian-Americans as “good at science” did not
appear to help the scientists surveyed establish their
competence with colleagues: they reported more
“Prove-It-Again” bias (63.6%) than White women
did (62.7%) when it came to establishing their
competence with colleagues. Interviews conrmed
that Asian-American women’s experiences were
shaped far more by the negative stereotype that
women are not good at science than the positive
stereotype that Asians are. This nding raises the
empirical question of whether the stereotype of
Asians as technically competent (Fiske, Cuddy,
Glick, & Xu, 2002) benets Asian-American men
more than Asian-American women. On the other
hand, Asian-American women scientists reported
less Prove-It-Again bias from students (31.7%), as
compared with the other three groups of women
(Black women: 56.5%; Latinas: 50.0%; White
women: 43.3%).
3. Asian-American scientists were more likely than
other women to report workplace pressures to
use the interviews of women of color in science and a
survey that quanties the experiences of White, Black,
Asian-Americans, and Latina women in STEM elds to
document the little-explored dierences between the
experiences of White women and women of color, and
between dierent groups of women of color.
Respondents for both studies were recruited through
the Association for Women in Science (AWIS) by
sending emails to AWIS members. Sixty women
participated in the interview study: twenty each of
Latinas, Asian-Americans, and Black women. Erika Hall,
then a graduate student at Northwestern University’s
Kellogg School of Business and now an Assistant
Professor of Organization & Management at Emory
University’s Goizueta Business School, conducted the
interviews. Five-hundred and fty-seven scientists
responded to the online survey.
Our data suggest that gender bias is commonplace in
science:
1. Prove-It-Again. Roughly two-thirds of both the
women interviewed (66.7%) and those surveyed
(63.9%) reported Prove-It-Again bias.
2. Tightrope. About three-fourths (76.3%) of the
scientists interviewed reported Tightrope bias. The
survey measured dierent types of Tightrope bias
and found that:
a. About one-third (34.1%) of the scientists
reported pressures to take on dead-end
traditionally feminine roles.
b. About one-half reported backlash for
stereotypically masculine behaviors such as
assertiveness (53.0%) and expressing anger
(52.3%). Over one-third (38.2%) reported
backlash for self-promotion.
3. Maternal wall. In interviews, nearly two-thirds
(64.0%) of scientists with children reported
maternal wall bias, including the exibility stigma
(Williams, Blair-Loy, & Berdahl, 2013) when women
took parental leave or stopped the tenure clock.
Women scientists without children also report being
disadvantaged in various ways, notably when they
are expected to work longer hours to make up for
the schedules of colleagues who do have children.
Motherhood appears to be a no-win proposition for
many women in STEM.
Gender Bias Against Women of Color in Science
Executive Summary6
57.1% of Black women). Among those surveyed,
Asian-Americans (26.7%) and White women (26.0%)
were far more likely than Latinas (9.1%) or Black
women (7.7%) to report that their colleagues had
communicated that they should work fewer hours
because they had children.
7. Tug of War. When asked whether women support
each other, most respondents (75.5%) said yes,
but Black women were far less likely to agree: only
56.0% did so. Latinas (35.5%) were far more likely
to report nding it dicult to get administrative
support personnel to support them. In interviews,
Black women also reported many instances of
conict with administrative sta. About one-third of
both Black women and Asian-Americans reported
tokenism—that women in their environments were
forced to compete with each other for the one
“woman’s spot”—as compared with roughly one-
fth of Latinas and White women. Asian-Americans
were far more likely (70.5%) than other groups to
agree that “some women had just ‘turned into men.’”
Finally, roughly 40% of all groups of women agreed
that “some women just don’t understand the level of
commitment it takes to be a scientist.”
8. Attributions dier. Black women tended to attribute
Prove-It-Again bias to race rather than gender. All
groups of women tended to attribute Tightrope
and Maternal Wall bias to gender, although race
remained more salient for Black women.
9. Sexual harassment. White women (37.2%) are far
more likely to report having been sexually harassed
as compared with Asian-Americans (25.0%), Latinas
(21.9%), and Black women (12.5%). Because the
interviews did not ask about sexual harassment, this
is the only data point available. A prior study that
lumped social scientists with natural scientists found
no dierence between sexual harassment reported
fulll traditionally feminine roles—and pushback
if they didn’t. Asian-American scientists surveyed
were far more likely than other women to report
backlash for stereotypically masculine behaviors
such as being assertive (61.4%) and self-promoting
(48.4%). They also were more likely than other
women (40.9%) to report pressures to play
traditionally feminine roles, such as oce mother
or dutiful daughter. Black women rarely reported
pressures to play traditionally feminine roles
(8.0%) and had the lowest levels of backlash for
self-promotion (30.4%). White women and Latinas
fell in between.
4. Latinas who behave assertively risk being seen as
“angry” or “emotional”—and they shoulder large
loads of oce housework for both colleagues
and students. Interviews found that Latinas who
behaved assertively risked criticism for being angry
or “too emotional,” even when the women themselves
reported that they weren’t angry—they just weren’t
deferential. Nearly 60% of Latinas surveyed noted
backlash for expressing anger, as compared with
54.4% of Asian-Americans, 49.7% of Whites, and
47.8% of Blacks. In addition, in interviews, Latina
scientists were far more likely than the other
groups of women to report being expected—both
by colleagues and by students—to do large loads of
oce housework, including literal housework (making
coee), administrative work typically performed
by support personnel, and emotion work in helping
students with their emotional problems.
5. Black women are allowed more leeway than
other groups of women to behave in dominant
ways—so long as they aren’t seen as “angry
Black women.” The interviews conrm the nding
of two experimental studies (Livingston, Rosette, &
Washington, 2012; Richardson, Phillips, Rudman, &
Glick, 2011) that found that Black women are allowed
to behave in more dominant ways than White
women—although interviews also noted pushback if
one is seen as an “angry Black woman.”
6. The Maternal Wall aects mothers of all races.
In interviews, 64.0% of the scientists who were
mothers reported maternal wall bias. In the survey,
69.0% of both Latinas and Asian-Americans
described pressure from their families to have
children (as compared with 60.6% of Whites and
Nearly 60% of Latinas
surveyed noted backlash
for expressing anger.
60%
Gender Bias Against Women of Color in Science
Executive Summary 7
janitors—something Williams has never heard in her
interviews with White women (Williams & Dempsey,
2014). But men of color describe similar experiences
(Bonilla, 2006).
An important point, sometimes overlooked, is that
while bias is rampant, glimpses of hope also emerge
from these interviews – situations where women of
color experienced support and success despite the
diculties faced. Specically, some of the scientists felt
that their cultural and racial traditions armed them well
to encounter the challenges they faced.
This report concludes by introducing a new approach
to organizational change to interrupt gender bias,
called Metrics-Based Bias Interrupters (Williams,
2014). In contrast to traditional one-o bias trainings,
and traditional sensitivity based organizational change
initiatives, Bias Interrupters uses a four-step iterative
process: 1) identify how gender bias is playing out, if at
all, in basic business systems (recruiting, assignments,
evaluations, etc.), 2) develop objective metrics to
measure bias, 3) implement a bias interrupter to
interrupt the bias, 4) see whether the relevant metric
improves and, if it doesn’t, strengthen or modify the
intervention. A compilation of Bias Interrupters is
provided at the end of this report.
among Whites and women of color (Settles, Cortina,
Malley, & Stewart, 2006).
It has long been known that the experience of women
of color diers from both that of men of color and
from that of White women, a phenomenon known as
“intersectionality” (Crenshaw, 1989). But this insight
has rarely been explored empirically. (For a literature
review of the exceptions, and a proposed theoretical
framework, see Ridgeway & Kricheli-Katz, 2013.)
In addition to experiencing the forms of gender bias
that fall into the Four Patterns rubric, women of color
also reported racial bias. All three groups of women of
color reported that they had to confront negative racial
stereotypes. Black women were more likely than other
women to report a sense of bleak isolation. Latinas and
Black women also often reported being mistaken for
Black women were more likely
than other women to report a sense
of bleak isolation.
Gender Bias Against Women of Color in Science
Executive Summary8
[Y]ou can try to ignore it just to keep
your sanity and move on, but the
biases that are there are prevalent.
And closing your eyes to them will
not make them disappear.
– Asian-American, Geology
9
Gender Bias Against Women of Color in Science
Introduction
AN ASIAN WOMAN IN BIOPHYSICS RECALLED THAT,
when she began her career in the late 1970s, gender
bias was very open: “Research grants were very dicult
to get. I got a grant, and my colleague said something
about, ‘Well, why don’t you go back to the kitchen so
that we have a chance to get the grant?’”
Gender bias today is typically more subtle. But it’s
pervasive.
Of the 60 women of color in STEM interviewed for
this report, 100% reported having encountered one
or more of the four basic patterns of gender bias.
Some had been warned by male mentors: “He told me
directly, ‘Look, I know you want to go in to do research.
And I think that if you are willing to ght, this will be a
productive career for you. But this is a male-dominated
area. So you’re going to have to saddle up here,’”
recalled a Latina professor of environmental biology.
Several women from India commented that gender bias
for women in STEM was worse in the U.S. than at home.
Women from Japan and Africa disagreed. Said a biologist
originally from Japan, “There…women are supposed
to be making tea for the guests [in addition to]…your
regular work, [making it] three times harder than the male
coworker to prove half as much.” A biochemist originally
from Africa agreed: “I’m comparing it to where I’m from,
and I’m like pt, this is nothing.
This report’s focus on women of color is designed to
address an oft-noted problem: that women’s initiatives
are seen as “White women’s initiatives.” Thus an Asian-
American science professor said her colleague of
color “felt that the committee on faculty women really
should have been renamed the committee on White
faculty women.”
A common, and indisputable, point is that women of
color often are aected by racial as well as gender
bias. Much less discussed is that women of color often
experience gender bias in ways that dier signicantly
by race. That is a major focus of this report.
The women we interviewed were divided on whether
they had been more aected by gender, race, or another
characteristic. Some women felt what mattered diered
depending on the situation. Said a Black lesbian in
biostatistics, “There’s some times where I feel like being
a woman is more problematic than being a person
of color, and there are denitely times where it’s the
reverse. Then there are times where the combination is
worse than being—it feels worse than being… a sexual
minority…. [I]t’s sort of situation dependent…. [I]n
various situations, one is at play more than the other
and vice versa.
Other Black women felt that race was more of an issue.
Said another scientist, “I obviously stood out and I
felt like I stood out rst because of my race and then
because I was a woman…. I’m the only African-American
[in my department], but then in terms of my gender,
there’s a ton of women here. Maybe that’s why.” This
was a common sentiment among Black women.
Asian-Americans and Latinas were more likely to
attribute bias to gender than race: “I think it depends on
the context. I sometimes have felt the ethnic bias versus
the gender bias, but I think overall it’s mostly…gender
bias,” said a Latina whose specialty is anatomy.
No matter what a woman’s race, bias is draining and
demoralizing. An Asian-American in astrophysics
found the bias she encountered “tiring and exhausting
because it’s a constant.” A Black woman in biostatistics
described “this under-the-surface feeling of uneasiness
that you can never quite identify as being overtly…
racially discriminatory, but, man, it certainly feels that
way.” What’s most draining, she noted, were “those little
micro kinds of situations, I think that, in some ways,
they’re probably a little bit worse in that they linger the
longest.” These micro-aggressions (Sue, Capodilupo,
Torino, Bucceri, Holder, Nadal, & Esquilin, 2007) are
often hard to identify by those not aected. This report
attempts to make them visible.
No matter what a woman’s race,
bias is draining and demoralizing.
Introduction
Gender Bias Against Women of Color in Science
Executive Summary10
The vision of the scientist that is the
White guy with the glasses and that
vision that if you ask a kid to draw
me a scientist, they would denitely
draw a guy with glasses and White.
– Hispanic female, biomedical research
11
Gender Bias Against Women of Color in Science
Prove-It-Again
BECAUSE WOMEN OF COLOR DON’T SEEM TO FIT
quite as well with “the vision of a scientist,” often
they have to provide more evidence of competence
than do White male scientists in order to be seen as
equally competent. Prove-It-Again bias stems from the
perceived mismatch between the typical woman and
the brilliant scientist. This perceived mismatch drives
several dierent tendencies:
• Womenarepresumedincompetent(Gutiérrezy
Muhs, Flores Neimann, González, & Harris, 2012);
men are presumed competent (double standards)
(Foschi, 2000).
• Women’smistakestendtobenoticedmore,
and remembered longer, than men’s (recall bias)
(Heilman, 1995).
• Women’ssuccessesoftenareattributedtoluck
or other outside causes: he’s skilled; she’s lucky
(attribution bias) (Swim & Sanna, 1996).
• Objectiverulestendtobeappliedrigorously
to women, leniently to men (leniency bias)
(Brewer, 1996).
• Superstarwomentendtoreceiveevenhigher
evaluations than superstar men, but women who
are merely excellent tend to get much lower
evaluations (shifting standards; polarized evaluations)
(Biernet & Manis, 1994; Linville & Jones, 1980).
• Ifajobrequiresbothexperienceandeducation,
people tend to choose a man with more education
and cite the importance of education to the position;
but if the woman has more education, they tend to
choose the man with more experience and cite the
importance of experience (Uhlmann, Cohen, 2005).
Nearly two-thirds of the women surveyed (63.9%) and
those interviewed (66.7%) reported that they needed
to provide more evidence of competence than others
in order to prove themselves to their colleagues. Yet
women’s experiences varied substantially by race. Black
women (76.9%) were more likely than the other three
groups of women to report having to prove themselves
over and over again (Latinas: 64.5%; Asian-Americans:
63.6%; Whites: 62.7%). Interestingly, in the interviews,
Latinas discussed colleagues’ negative competence
assumptions about as much as did Black women, and
far more than did Asian-Americans. This nding was not
reected in the surveys.
That Black women felt more Prove-It-Again bias makes
sense, given that they trigger two distinct sets of negative
competence assumptions, one based on gender, and the
other on race (Fiske, 2010; Go et al, 2008). Less easy
to understand is that slightly more Asian-Americans
reported Prove-It-Again bias from colleagues than
White women reported: perhaps the “model minority”
stereotype of Asians as equally competent as Whites
(Fiske, Cuddy, Glick, & Xu, 2002), particularly in technical
matters, chiey benets Asian-American men.
The scientists surveyed also reported having to provide
additional evidence of competence to prove themselves
to their students, although at lower rates. Black women
Prove-It-Again
76.9% of Black women
reported having to
prove themselves over
and over again.
76.9%
12
Gender Bias Against Women of Color in Science
Prove-It-Again
(56.5%) and Latinas (50.0%) reported this problem more
frequently than did White women (43.3%) and Asian-
Americans (31.7%). Interestingly, the “model minority”
stereotype appears to help Asian-American women in
STEM more with students than colleagues: while Asian-
Americans were more likely than White women to report
Prove-It-Again problems with their colleagues, they were
less likely to report similar problems with their students.
Latinas
Colleagues’ negative competence assumptions.
A Latina in environmental engineering recalled Prove-
It-Again bias from her earliest days in her eld when,
on her qualifying exams, one of her professors “told
me that he was going to ask a question that I was not
going to be able to answer and he was going to have me
take an extra course.” This woman’s qualifying exams
did indeed contain a question that was impossible
to answer without making assumptions. So she
made some assumptions, and reached the correct
conclusion. Her professor was unimpressed: “even
though [her] assumptions were correct and the answer
of the question was correct” he still made her take the
additional class. “[H]e went as far as knocking on my
head and saying, ‘Is there anybody there?’” Years later,
her hands were shaking as she told the interviewer the
story. “I was about 22 years old, so I went back to my
oce in tears.” It took her years, she said, “just to be
able to see myself again as somebody who actually did
know what I was doing back then.”
A Latina in geography thought that some people have
“these kneejerk reactions that people of color or women
of color aren’t as competent.” A Latina in biochemistry
recounted being excluded when her (male) colleagues
discussed her own project. When she suggested that it
would have been appropriate to include her, they looked
at her with surprise; “from that day on, I had to really
ght and be very proactive about these things.”
Sometimes negative competence assumptions play
out as hyper-scrutiny. Said a biochemist, “they’ll nitpick
at the protocol, if that makes sense. Well, did you do
something dierent? Did you change something on the
protocol? Did you do it at a dierent time of day? Was
the temperature exactly the same? You just have to
address every one of their nitpicking questions, until
you’ve answered them all. It’s like, ‘Okay, you’re out of
arguments.’ Then they have to accept the fact that okay,
yes, you were successful in that, not because you’re a
woman, but because you can do the experiment, or you
can do that project well.”
As a result, many Latinas felt intense performance
pressure. For these women, working hard is a way to
overcome the “Mexicans are lazy” stereotype. Some
Latinas felt constantly under pressure to make sure
everything they did was perfect, a pattern that has been
documented in the lab for Black women (Rosette &
Livingston, 2012).
Students’ negative competence assumptions.
Women also mentioned challenges in getting students
to take them seriously. A Latina engineer noted,
“Students’…mental image of what their . . . respected
engineering professor should look like is a White,
balding male. I enter the classroom and I don’t t that
image, so I start out with this, okay, I have to prove
myself to them.” A Latina chemical engineer noted that
“students tend to basically just have a certain level of
respect for a male faculty from day one that they don’t
necessarily have for a female faculty, or for me at least.”
Prior studies have made similar observations (Turner,
Gonzáles, & Wong, 2011; Stanley, 2006 (citing studies)).
Successes discounted. Part of the problem was that
Latinas’ accomplishments were discounted or attributed
to luck. “Even when I went up for promotion,“ said a
Latina biologist, questions were raised about “whether
or not I would continue to be doing the things that I
was doing, once I got full professor….I had never heard
that kind of a comment ever expressed in previous
deliberations though. It was a double standard.
Mistakes magnied. Several women noted that
women were penalized far more than men for mistakes.
A Latina statistician recalled a female colleague whose
mistake “many years back” was brought up again and
again, noting that a male colleague “hasn’t been able
“[S]tudents tend to basically just have a
certain level of respect for a male faculty
from day one that they don’t necessarily
have for a female faculty, or for me at least.
13
Gender Bias Against Women of Color in Science
Prove-It-Again
mostly males, you are kind of wired into thinking that
you have to try harder…. And you probably will have to
work twice as much as your male colleagues,” remarked
one woman. Another Latina, a statistician, noted “You
are young and you are male, you can do it. You are older
and you are female, they don’t want to waste time on
you, until you prove the contrary.
Prove-It-Again problems were perceived to have
concrete consequences. A Latina engineer commented,
“I have seen some of my [female] colleagues get higher
funding rates, higher number of publications, higher
service achievements, have their promotions delayed
because it was considered that they didn’t have enough
achievements.
A Latina in microbiology and biochemistry commented
that the Prove-It-Again problems she encountered in
the early years of her career stopped when she entered
an environment that was gender balanced: “[D]uring
my postdoctoral fellowship where I was the only female
in a postdoctoral lab of six men, and the PI was also a
man… I always felt like I had to do more to prove myself
in that lab. Even in just simple lab meetings, we would
each have to kind of say what we did that week and go
to let go of that and continues to pound this woman
on every possible occasion.” This same colleague, she
noted “was extraordinarily lenient with a male colleague
of ours who has done worse than this female colleague
of ours and seems to enjoy—‘Oh, he didn’t mean that.’”
The stolen idea. Several women also reported
situations where women suggest an idea only to have
it overlooked, only to have the idea taken up when
it is repeated by a man. Said a Latina environmental
engineer, “I would say something in a meeting and it
would go on deaf ears. And then somebody else would
say the exact same thing and there would be the, ‘Wow,
that’s such a great idea.’” A Latina statistician recalled,
“[Y]ou say something in a meeting, you throw an idea
out on the table, nobody picks up on it. Then, a little
while [later] one of your male colleagues throws the
exact same idea on the table and everybody goes, ‘Oh,
that’s a fantastic idea.’”
The Latinas interviewed typically attributed their Prove-
It-Again! challenges to gender rather than race. “[A]s a
woman in engineering, very, very, very few women, right,
14
Gender Bias Against Women of Color in Science
Prove-It-Again
she’s a go-getter. My great-grandma grew up during the
Mexican Revolution, and she was one of those ones that
picked up guns and went ghting for the cause. It comes
from generations of very assertive women.
A strong sense of right and wrong helped others: many
Latinas in science adopted a “what does not kill you makes
you stronger” attitude, viewing those who exhibited
prejudice as weak and themselves strong because they
worked hard and took pride in the results of their work.
Black Women
Colleagues’ negative competence assumptions.
The experimental nding that Black women have to
provide more evidence of competence (Rosette &
Livingston, 2012) denitely resonated with the women
interviewed. Said a Black microbiologist, “[I]t’s a huge
barrier, how you’re perceived as a capable scientist.”
over our data. And I always felt like I was getting drilled…
[W]hereas the other guys, they would just kind of say,
‘Oh, yeah, and we sat around and did X,’ and they were
just believed immediately.” Now that this woman is in a
department that is half male and half female, she notes
that this does not happen anymore.
Some Latinas felt that unfair treatment just rolled o
their backs. A biology professor noted, “I was raised in
a culture where women are sort of stronger in a lot of
ways. Women have learned to take over responsibility
for their families and be the ones in charge. Whether
you have a man or not, you have to make things
happen…. I feel that that has given me strength in
science where I don’t believe paying much attention
about what other people might think or not think and
just go for what I think I want to do and that I need to do.
I just don’t give up. I’m from Puerto Rico.” A woman of
Mexican descent agreed. “My mother is an extremely—
15
that’s not Statistics, and if you’re going to challenge me
on this—well, I won’t be challenged on this.’”
Blackwomenare“presumedincompetent”(Gutiérrez
y Muhs, Flores Neimann, González, & Harris, 2012) not
only in research but also in teaching. A Black statistician
recalled when an administrator asked her how her
teaching was going. “‘You’re not having any problems?
Everything’s going okay?’” She said everything was ne;
later she found out that “a student had called the oce
and complained about a professor. For some reason,
naturally it was assumed that it was me, okay?” The
student complained about another professor.
Successes discounted. A Black biochemist reported
that an evaluation said, “she’s bright, she’s big, but she
needs a lot of supervision.” Note how her success was
discounted.
Objective rules applied rigorously to women,
leniently to men. A Black biologist noted an example of
leniency bias—when objective requirements are applied
rigidly to some but leniently to others. She prepared a
document and “I didn’t put it in an envelope. That was it.
I just gave it to the sta member and didn’t put it in an
envelope. The faculty member came back to my oce
screaming and raging about anybody could have seen
this paperwork, it’s private and condential. It was just a
hiring form.”
Some women were philosophical about their Prove-It-
Again challenges. Many of these women grew up with
the knowledge of an “uneven playing eld.” Said a Black
statistician, “I turn it around as a motivator. Because
I turn it around into a positive. It helps motivate me to
push harder.”
Asian-Americans
One woman used the model minority stereotype
strategically. Asian-American women in STEM, at
least in theory, are in a dierent situation than Latinas
and Black women. First, Asian-Americans are not an
underrepresented minority in STEM. Second, Asian-
Americans are seen as equal in competence to Whites
(Fiske, Cuddy, Glick, & Xu, 2002), particularly in
technical matters. An Asian-American physicist very
self-consciously played o the stereotype that “Asians
are naturally talented in STEM elds” to counter the
Gender Bias Against Women of Color in Science
Prove-It-Again
A Black biochemist noted, “You always have to prove
yourself…, to show skill. I’ve never, ever had anything
easy.” She attributed the problem chiey to gender,
recalling a time when she and her advisor, a White
woman, stood virtually alone watching the trac go to
the poster of a White male colleague, whose was on a
closely related topic.
More commonly Black women attribute their Prove-
It-Again problems to race. Said a Black woman in
medical imaging, “that initial expectation of not being
professional or whatever and—or not being taken
seriously until they hear me, I think that’s more because
I’m Black than because I’m a woman.” A statistician
agreed, suggesting that when she presented to an
audience, the audience assumed a lack of merit in
her results. A prior study found that 63.6% of Black
faculty report subtle racism as a source of stress—over
20 points higher than for any other group of faculty
(Hurtado, 2011).
Other respondents expressed less certainty about
whether race or gender was the issue. “It’s challenging
because you don’t know if you’re working twice as
hard because you’re a woman or if you’re working
twice as hard because I’m African American,” said a
mathematician. A Black microbiologist said, “Yes, we
must prove it again and again. We have two strikes
against us and each is addressed separately.” The
prevalence of this experience has been noted in other
studies (Stanley, 2006).
Still others felt gender and racial bias were additive. A
Black biostatistician noted that she sometimes needed
to put her foot down. “[When] it’s moved to a place
that’s almost ugly, where I’ve had to remind people,
‘Look, I have this degree from this very prestigious place.
Yes, you have a dierent degree in a dierent area,
which makes you knowledgeable in a very dierent area
“You don’t know if you’re working twice
as hard because you’re a woman or if
youre working twice as hard because
you’re African American.
16
Gender Bias Against Women of Color in Science
Prove-It-Again
wearing cut-os with holes in them and a t-shirt, I just
would not get any respect at all—particularly when I
was younger—whereas my male colleagues of the same
age could get away with that,” said an Asian-American
in statistics. So she dressed more formally, and
“tend[s] not to be jokey. My male colleagues can joke
around a lot.” People “have told me to loosen up and
I honestly don’t know what I’ve said in response, but I
just had a feeling that if I started to loosen up I would
lose respect.
Successes discounted. Other Asian-American
women reported that their successes were discounted.
One described her department chair saying that she
got grants not due to merit but to politics. An Asian-
American woman in statistics recalled that she was
the only one who had a tenure track position when she
nished her program. Despite the fact that she had
three publications while her White male colleagues had
none, she was told that she had gotten the job because
she was a woman.
These assumptions have concrete consequences, noted
an Asian-American immunologist: “I got my big R01 and
then looked for the position.” She was told she “needed
to wait for a year to be associate professor in order to
move your lab and also he gave me a lot of—I think it’s
excuses.” She accepted the job at an assistant professor
rank nonetheless because she wanted a shorter
commute—only to have a less credentialed man hired
as an associate professor. Even when she managed to
get her rank changed to associate, her salary remained
unchanged, despite the fact that she had brought in
another prestigious grant. She said this kind of thing
was common.
The stolen idea. An Asian-American biochemist
recalled that often her idea was “just portrayed as
somebody else’s idea. And then they would discuss
about it, basically not giving me any credit for what I was
saying.” She got so tired of this that she began to put her
ideas in an email before a meeting, so everyone knew
which ideas originated with her.
A geneticist noted that things had improved when more
Asian-American women entered leadership positions.
“[T]hat has helped changed the atmosphere.”
negative stereotype that women aren’t. Her strategy
was to make sure she was seen as an Asian in STEM
rather than a woman in STEM: “I’m more acceptable,
if you will, as an Asian woman scientist rather than a
woman scientist.
Colleagues’ negative competence assumptions.
Yet this sentiment was surprisingly rare. Most of
the Asian-American women interviewed reported
experiences similar to those reported by Latinas and
Black women. “I have felt always under…extra scrutiny,”
noted an Asian-American woman in astrophysics.
She had the sense that she needed to display her
competence “in many more settings than they are
required of men, of White women, whatever….—[Y]ou
have to prove yourself all the time and that, yes, not a
whole lot is taken on promise.” An Asian-American in
statistics described the attitude: “If you’re perfect we
might accept you, but if you’re not perfect, forget it.” She
continued, “Your expertise constantly being questioned
is probably the biggest thing—you know, people just
assuming that you’re not going to be able to cut it.” Asian-
Americans also reported disrespect: a geophysicist
recalled when her colleagues told her students that she
would not get tenure, and “it felt so wrong.”
Students’ negative competence assumptions.
An Asian-American biochemist reported her sense,
when she starts a class of “an uphill kind of battle….I get
the impression that students don’t believe that I know
what I’m supposed to know…?” Said an Asian-American
statistics professor, “I think my worst experience was
probably an almost all male engineering stats course
where, if I pointed out a couple of dierent ways of doing
a problem, the teaching evaluations came back saying
‘She doesn’t know what she’s talking about.’” When her
White male colleagues did the same thing, they were
labeled “inventive” and “smart.”
To enhance their authority, the Asian-American women
interviewed tended to be much more formal than
their male colleagues. “Because if I went into my class
“If you’re perfect we might accept you,
but if you’re not perfect, forget it.
Gender Bias Against Women of Color in Science
Executive Summary 17
18
Gender Bias Against Women of Color in Science
The Tightrope
Whites and 47.8% for Black women. Moreover, in the
interviews, Latinas often reported that they were faulted
for being angry or “too emotional” when they behaved
assertively—something never reported by women from
other groups.
Asian-American women are more likely than women
from other groups to be policed into femininity, and
penalized for stereotypically masculine behavior. The
nal evidence of this pattern concerns self-promotion.
Nearly half (48.8%) of Asian-Americans surveyed
reported backlash for self-promotion, as compared to
roughly a third of women from other groups: 37.3% of
Whites, 31.1% of Latinas, and 30.4% of Black women.
The survey contradicts an experimental study that
found that Black women are allowed to behave in more
dominant ways than White women without pushback
(Livingston, Rossette, & Washington, 2012). In our survey,
Blacks and Whites reported backlash for behaving
assertively and showing anger at about the same rates.
In a counter-intuitive nding, White women (41.8%) were
most likely to report they are asked to do more service
work than others, a higher level than Black women
(37.5%), Asian-Americans (32.5%), and Latinas (31.3%).
All four groups of women tended to attribute Tightrope
issues to gender, although race remained more salient
for Black women.
Asian-Americans
Asian-Americans often encountered pressures to
play traditionally feminine roles—and pushback if
they didn’t. Asian-Americans surveyed reported that
they had encountered pressures to play traditionally
feminine roles such as oce mother or dutiful daughter
DUE TO PRESCRIPTIVE GENDER BIAS, WOMEN WALK
a tightrope between being seen as too feminine, and
so liked but not respected—or too masculine, and so
respected but disliked (Fiske, S. T., Cuddy, A. J., & Xu, J.,
1999). Studies have documented that Asians (men as
well as women) are seen as more feminine than Whites,
while Black people are seen as more masculine than
White people (Go, Thomas, & Jackson, 2008; Johnson,
Freeman, & Paulker, 2012; Galinsky, Hall, & Cuddy, 2013).
So it comes as no surprise that Asian-American women
encounter more “too feminine” problems—and Black
women encounter fewer—than do other women. White
women and Latinas generally fall somewhere in between.
Asian-Americans surveyed were more likely (40.9%)
than other women to report pressures to play
traditionally feminine roles such as oce mother or
dutiful daughter, as compared with White women
(35.9%) and Latinas (28.1%). Black women rarely
identied this as a problem (8.0%).
Asian-Americans also more often reported backlash
for stereotypically masculine behaviors. Most striking,
fully 61.4% reported pushback for assertiveness. It
seems that the stereotypes of Asians as passive mean
that Asian-American women who aren’t passive seem
more transgressive. The other three groups of women
also reported pushback for assertiveness, but at lower
levels: 53.2% of White women, 50.0% of Blacks and
46.9% of Latinas.
The survey suggests that the racial stereotype of the
“ery Latin” may leave more room for Latinas to behave
assertively, but the same stereotype disadvantages
Latinas who show anger. Latinas were more likely
than other groups of women to say they did not feel
free to express anger at work: 59.4% reported this, as
compared with 54.4% for Asian-Americans, 49.7% for
The Tightrope
Women walk a tightrope between being
seen as too feminine, and so liked but
not respected—or too masculine, and so
respected but disliked.
61.4% Asian-
Americans surveyed
reported pushback for
assertiveness.
61.4%
19
Gender Bias Against Women of Color in Science
The Tightrope
The Tightrope is very narrow for Asian-Americans: one
soil microbiologist, who reported being penalized for her
masculine style, also reported having been penalized
earlier in her career for being too feminine. Now a
professor, she talks with students about being assertive,
and about the “dierence between being assertive and
being a bitch.”
Sometimes colleagues’ bias was very open: “I’ve gotten
remarks like ‘I didn’t expect someone that was Indian…
and female to be like this,’” said an Asian-American soil
microbiologist. She found it a challenge to “t some sort
of stereotype of this, I don’t know, quiet, subservient
woman or something.” Again, the Tightrope was narrow:
“if a woman promotes herself, then she’s too forward or
too aggressive.” Her solution was to signal masculinity
through clothing, which is “my way of not really being
masculine but kind of conforming to a dress code so
that I am respected.
An Asian-American physicist perfectly articulated her
dilemma, saying that the Tightrope sounded “very, very
familiar. And I think it’s a struggle that most women
or even I go through is how do you portray yourself? I
mean, where is the balance, right? I mean, you…are a
woman…you don’t have to be a man. But, at the same
time, if you want to t in, do you have to behave like the
men? And I think I see that a lot. And I know of a lot of
women who go through this struggle of how should you
portray yourself and be respected for what you are…. I
still nd that a struggle.”
Politically adept women ried o stereotypes to keep
colleagues o balance. “[I]f you’re a young man you’re
a boy genius,” said an astrophysicist. “But if you’re a
young woman, you are so threatening that, in order to
be able to cope and to be liked and not intensely disliked
by everybody else,” things get dicult. “I have had to
become as amiable as possible and a group player all
the time, not looking out for myself, so damp down my
ambition in some ways…. I rarely talk about the prizes I
get, the media attention I get. I mean, I keep it all really
at much higher rates than other women. Asian-
American women were also much more likely to report
backlash if they engaged in stereotypically masculine
behaviors, such as self-assertion (61.4%) and self-
promotion (48.8%), suggesting that the stereotype that
Asian-American women are more feminine than Whites
is also a stereotype that they should be more feminine.
The stereotype of Asians as passive plays a role. A
geophysicist noted the expectation “that Asians are
supposed to be very passive. And when you add women
to that, they really don’t expect Asian women to stand
up for themselves, or they expect the dragon lady, the
extreme opposite. You can’t just be a normal person.
There’s no expectation for you to be normal.” An Asian
in viral immunology agreed, saying that, as an Asian,
she was seen as someone who “should be like feminine,
yeah. Shouldn’t be aggressive.”
Some refused to conform because they felt that doing
so undercut their authority. “I just feel like it’s kind of
sad you have to portray yourself as a tough bitch in
order to stand on your ground. It’s hard,” mused an
immunologist. “I’m very candid and I do not hesitate
to open my mouth and that was probably not the
submissive female person,” said an Asian-American
biologist. “I think that being an oriental female
immediately started, I guess, having a reputation of
being a dragon lady.” Colleagues in other departments
told her to watch her back. “Early on when I started
working here, a faculty colleague of mine said…, ‘I can
hear you way down the hall because your balls clang.’”
“If you want to t in, do you have to
behave like the men?”
20
Gender Bias Against Women of Color in Science
The Tightrope
that in her current department, female administrators
had been around for a long time, so “women can behave
quite assertively and aggressively and be respected.”
She concluded, “so things are good.”
Black Women
While Asians are seen by Whites as more feminine
than Whites, Black women are seen by Whites as more
masculine (Galinsky, Hall, & Cuddy, 2013). So it is
not surprising that Black women reported both less
pressure to play traditionally feminine roles and less
backlash for behaving in masculine ways. Black women
reported rarely feeling pressure to play traditionally
feminine roles such as oce mother or dutiful daughter:
only 8.0% of Black women did. (Other women’s
agreement ranged from 28% to 41%.) A microbiologist
described how she did not suer fools lightly. When
students come to her for tea, sympathy, and deferred
deadlines, “I’m like, I do keep count of how many
grandmothers people have. You can’t do it three times.”
Thus Black scientists surveyed reported the lowest
level of pushback for self-promotion (30.4%, as
compared to 31.3% for Latinas, 37.3% for White
women, 48.8% for Asian-Americans). Black women
also were less likely than other women to report that
they did not feel free to express anger at work (47.8%,
as compared to 49.7% of Whites, 54.5% of Asian-
Americans, and 59.4% of Latinas).
Studies show that open expressions of anger tend to
increase the perceived status of a man, but decrease
that of a woman (Brescoll & Uhlmann, 2008), but the
extent to which this is true may dier based on race.
An experimental study found that Black women are
less likely than White women to encounter backlash
for behaving in dominant ways (Livingston, Rossette,
& Washington, 2012), and the interviews contain
damped down. But, now in the age of the Internet, right,
everybody knows everything.” This is “gender judo”:
using feminine stereotypes that typically hold women
back to, instead, propel them forward. While this
strategy had proved successful in managing backlash,
she believed she’d also paid a price for downplaying her
accomplishments.
Self-promotion challenges. Women of all groups
often struggle with self-promotion, which often is seen
as appropriate in men (“he knows his own worth”)
but distasteful in women (Rudman, 1998), who are
expected to be demure, modest, and helpful (Prentice
& Carranza, 2002). Many Asian-Americans nd self-
promotion particularly dicult. “It’s our upbringing
that you’re taught to be humble and not boast about
your achievements and give credit to others and
being boastful is just being rude….If people nd and
appreciate, that’s good for you. If not, that’s okay is
what we are taught. And so, it’s so inherent in us that in
a society where it’s more self-promoting…that it’s really
hard….Even those who do it eventually, it takes a very
long time to learn that. And you pay a price for that,”
said a geophysicist.
Students’ stereotypes. The “den mother” role is
common for Asian-American women professors.
Sometimes it’s a self-conscious strategy—gender
judo—to dodge pushback for being seen as too
accomplished or too masculine by adopting a feminine
persona. Often, though, the femininity feels mandated
and uncomfortable, as students demand attention and
emotional support from women that they rarely require
of male professors. Said a physicist, “The weaker
female grad students said ‘Oh, I thought, as a woman,
she would understand my problems.’ They expected
me to be sort of motherly towards them and spend
time counseling them and so on, which is not my job.” A
statistician reported similar experiences, saying that
students “expect me to be more helping—you know,
always willing to help. Where a male faculty member
could just refuse and not have that negatively aect him.
Whereas if female faculty members just refuse, that can
negatively aect them.
Again women reported that things got easier when
they transitioned to environments with more women
colleagues in professional roles. A statistician noted
Black women reported both less
pressure to play traditionally feminine
roles and less backlash for behaving
in masculine ways.
21
Gender Bias Against Women of Color in Science
The Tightrope
realize.’” These ndings echo an earlier study of physics
graduate students that found that they strategically
adopted a “loud Black girl” persona (Ong, 2005).
In sum, the interview evidence appears to conrm the
experimental evidence that Black women can behave
in more dominant ways than White women and Asian-
Americans; the ndings with respect to Latinas are
murkier. Yet the picture is complex: the survey evidence
appears to contradict that nding. In the survey, White
women (52.3%) and Black women (54.2%) report
pushback for being assertive with about the same
frequency as each other; with Latinas not far behind
(46.9%). More research is needed.
Avoiding the “angry Black woman” stereotype and
other backlash. There are limits. A statistician noted,
that the Tightrope is “particularly sensitive” because
“you have to avoid the stereotype of the ‘angry Black
female,’” which “diminishes your opinion and the weight
of your argument.” A microbiologist recalled getting
testy with a colleague who wanted to correct a student’s
many examples of Black women saying that dominant
behavior works for them. Said a Black woman in
medical imaging, “I’ve never really dealt with being
thought of as a bitch, but I have—I kind of aspire to that
a little bit because I see, at this university at least, that—
actually it’s a very eective perception to have.” She
continued, “And when I am most successful is when I
come out of my passive mode…. I am assertive, that’s
when I am most rewarded. I won’t say that’s when I’m
most productive, but that’s when I’m most rewarded.
A Black statistician noted that she felt she could get
respect for being like a prototypical man—aggressive or
assertive. So did a mathematician, who embraced “the
perception of the angry Black woman is that we’re very,
very strong-willed. We don’t take any mess and we get
the job done, right?”
Other women agreed. A Black statistician noted, “I
certainly can’t walk in the classroom and come o as
being timid, right? Because then students will try and
walk all over me. You go in there, you’re assertive, you
lay down the rules of the syllabus on the rst day. At
least if you come o on that rst day as being stern—I’m
not saying you have to be nasty, of course, but very
set and this is what you want to do, this is the goal
of the class, this is my role, this is your role. It lays
down the groundwork.” A prior study found that Black
professors (both men and women) tend to be judged as
signicantly less competent and legitimate than White
and Asian-American professors—and were seen as
having fewer interpersonal skills than Whites (Bavishi,
Madera & Hebl, 2010).
A doctor recalled sending an email when she was
truly annoyed with a colleague: “When I nished the
email and read it, you could tell that it had a bite to
it. [Laughter.] This person was someone that I really
didn’t care if they got the bite because I wanted ‘em
to get the bite.” Her partner noted that the email had
an attitude and asked “‘Now, why did you send that?’ I
said, ’Because I was ticked.’ He goes, ‘Well, that had an
attitude to it.’ I said, ‘I know.’ I said, ‘I meant for it to have
an attitude.’” She sent it to a colleague who “has this
attitude of, well, I’m in charge and I know what’s best
and kind of push over people. I wanted him to know I
wasn’t just gonna go away or just back o just because
this is the way he said it. I sent this email and, yeah, it
had a bite to it. Within ten minutes—this is at 9:00 at
night—within ten minutes I got a response from this
guy and the response was, ’Oh, I am so sorry. I didn’t
“[Y]ou have to avoid the stereotype
of the ‘angry Black female,’” which
“diminishes your opinion and the
weight of your argument.
22
Gender Bias Against Women of Color in Science
The Tightrope
as an “angry Black woman” she tried not to raise her
voice or to be too animated, which, she acknowledged,
contributed to her timidity in meetings.
The single most shocking story was told by a
microbiologist who, earlier in her career, suered a
traumatic brain injury. When some White males who
worked for her came to visit “I asked them the questions
that a boss would ask, like ‘Where are we with the
project? Did you take care of this and that and that?.’”
The hospital sta thought she was “unnecessarily
brusque, undeferential” and that she “needed to stay in
rehabilitation longer until I started acting like a woman.
One of her colleagues suggested she act the “Southern
belle” so “I dropped my IQ by several points and started
looking for little things to decorate myself with.” She
raised the pitch of her voice and chose pink hospital
gowns. “All the sudden, they let me out.”
This scientist proceeded to describe the Tightrope
in classic terms. “[I]t’s a ne line you have to walk,
because sometimes I do nd myself trying to not come
o too aggressive, because I know it can be, I guess,
viewed as she is bitchy or whatever. At the same time, I
try not to let people walk over me…[or] come across as
weak and helpless, you know [laughter]?”
Playing traditionally feminine roles and doing the
oce housework. The survey found that only 8.0%
of Black women reported pressure to play traditionally
feminine roles, yet the interviews surfaced a number of
women who did so. One Black mathematician noted that
she’s “kind of seen as this motherly nurturing person in
the department.” Colleagues often sent students who
were having problems to her. “I’m not a counselor, but
I’m the only female in my department. And I work with a
lot of foreign faculty members who have expectations of
women. And the expectations that they have is that, you
know, women are supposed to be caring and nurturing
technique in her research lab “—they were pretty much
saying that what I was telling the student was wrong.
She let them have it. “I pretty much bluntly invited them
to leave my lab, and told them that if they had issue with
things that go on in my lab, to address me rst of all,
and if I couldn’t give them satisfaction, they were free
to take it up with the administration, but unless they
saw an imminent danger.” She noted, “I’m calm. I don’t
raise my voice.... Because if I were as assertive as some
Caucasian colleagues that are male, I would be called a
mad Black woman.... For that reason, I choose to—and
actually, it’s just my personality to be soft-spoken.”
A doctor also reported self-editing to avoid backlash,
saying that she dressed more femininely because,
if she “dressed like Hilary Clinton, wore pantsuits
all the time or just kind of didn’t care as much about
her appearance,” she felt she would be regarded as
“aggressive as opposed to just neutral. I think a plain-
dressing Black woman would be taken as aggressive
or as—and then, especially with the hair.” Whether to
let one’s hair grow natural, of course, has long been
a delicate issue. One Black woman recounted, after
becoming department chair, how a colleague had
“spent 45 minutes telling me how I needed to dress
more appropriately for the position that I was going to
assume” and that she “should wear more skirts and
apply make-up….I have been told that wearing my hair
naturally was not a professional kind of hairstyle.”
Other Black women describe backlash as a problem and
gender judo as a solution. A biologist who noted that she
tends to be “a very direct speaker” said that her Chair
got “very angry and was like don’t talk to me like that.
She had heard male colleagues talking that way, without
incident. But she felt she had to “put cotton candy in
my mouth and, oh—I had to do very—a lot of deferring.
‘I can’t do this without your help, I really need you to
do this,’ if you—and I had to put him in that masculine
‘I’ll take care of it role,’ and I had to take the feminine ‘I
need you to help me, I need to be saved’ role. And a lot
of times, that was how I had to deal with him in order to
get what I needed to get things done.” This interviewee
felt that White women could get away with being direct,
“whereas with me, it was seen as more threatening.
A cancer biologist exemplied “stereotype threat”
(Steele, & Aronson, 1995)—when someone shapes
their behavior in order to avoid a stereotype and, in
doing so, becomes less eective. To avoid being seen
“I’m calm. I don’t raise my voice....
Because if I were as assertive as some
Caucasian colleagues that are male, I
would be called a mad Black woman....”
23
Gender Bias Against Women of Color in Science
The Tightrope
was like I’m not crying. I’m not raising my voice. I’m not
doing anything. Why am I being emotional when I’m
telling you that this is just simply wrong….”
Again and again, Latinas reported being criticized as
“angry” when they behave assertively. Said a Latina
biochemist, “my department chair basically called me
to his oce afterwards and told me that I was giving
the impression that I was an angry lady and basically
encouraged me not to open my mouth and express
my opinion during faculty meetings because people
were going to think that I was just a hysterical woman.”
She noted that she had acted no dierently than her
male colleagues in expressing her views. Sometimes
backlash came from students rather than colleagues. A
neuroscientist recalled what happened when she asked
a student to leave her lab because the student had
been disrupting the smooth functioning of the lab. The
student told her, “You’re just too emotional. If you were
just a little bit more cool-headed.” The neuroscientist
noted dryly that, “On the other hand there are some
people that think that I’m just really too strict and too
non-female-like.”
Another theme was that Latinas were overly emotional
or “crazy,” a charge rarely reported by other groups of
women. “I have found that it is much more accepted for
a male to be aggressive,” said a Latina engineer. “Many
professors that will even kick the doors and everything,
and nobody seems to care about that. I can guarantee
if a female does it, they will feel that she’s crazy.” Said
a statistician, “many times, when a woman has a
dissonant voice, they are called, here and also back
home, a crazy so and so.”
Some of the scientists tightly controlled their emotional
expression in order to avoid these stereotypes. “You
have to be completely emotionless because that
person’s just going to say, ‘Oh she’s a woman’” and
see you as weak, noted a Latina in anatomy. A Latina
biochemist recalled getting angry when someone did
and to take care of the kids.” Another Black woman, a
biologist, noted the expectation that women are a good
t for emotion work: “it’s like, ‘Yeah, you can tell me all
your problems because that’s my job sort of to help you
solve your problems,’ as opposed to coping with my
own.” She protested, “This is in the workplace.”
The most poignant story was of a Black scientist whose
mentors were “very adamant” that she didn’t “need
to sit on every blasted committee.” So, in a meeting
with the provost, she pointed out that Whites as well as
people of color could be tapped to serve on diversity
committees. The provost’s response was to invite her to
serve on another committee. “Of course I’m not going
to say no to the provost. This is the man who basically
has my tenure in his hands.” Other studies have noted
that women of color sometimes are more committed
to “race-based service” (Baez, quoted in Stanley, 2006).
Among our informants, the focus was more on how
such service was extracted regardless of the wishes of
the professor of color.
Latinas
Angry—or assertive? An important nding of the
survey was that for Latinas, much more than for other
groups of women, expressing anger is a danger zone:
59.4% said they did not feel free to express anger at
work (as compared with 54.5% of Asian-Americans,
49.7% of White women, and 47.8% of Black women).
The interviews also found that Latinas are often seen as
angry when they’re not: Latinas who behave assertively
reported that they often were discredited as “angry”
or “too emotional” even when they werent angry; they
just weren’t deferential. In the survey, Latinas reported
the lowest levels of pushback for behaving assertively
(46.9%), although Black women (54.2%) and White
women (52.3%) were close. Still, almost half of the Latina
scientists surveyed reported pushback for assertiveness
and the interviews provided many examples.
Said an environmental engineer, “Everybody is afraid
that I’m just going to start crying or that I’m just going
to get really mad.” She noted “a lot of fear that, the
Hispanics and the Black women, we’ll just blow in a
meeting because we are so much more emotional and
we cannot handle ourselves in the way that everybody
else can.” She had protested when a job candidate kept
being referred to as the “minority candidate,” she was
told to “‘stop being so emotional about syntax.’ And I
Latinas reported that they often were
discredited as “angry” or “too emotional
even when they weren’t angry.
24
Gender Bias Against Women of Color in Science
The Tightrope
Large loads of oce housework. In the survey,
about a quarter of Latina scientists (28.1%) reported
expectations that they play traditionally feminine roles
such as oce mother/dutiful daughter—considerably
less than Asian-Americans (40.9%) and White women
(35.9%) but much more than Black women (8.0%).
Yet the interviews contained many reports of Latina
scientists expected to play traditionally feminine roles,
including literal housework as well as emotion work and
work typically performed by administrative sta.
The Latina scientists interviewed reported that both
students and colleagues expected them to do oce
housework. A Latina bioengineer remarked that students
expect women professors “to be more motherly and
more willing to make exceptions for them, if they want
to.” Male colleagues could tell students to leave the
classroom if they were not paying attention. “They can
say things quite frankly, rudely, and people love them.
They think they’re great. If I said that I’d be crucied.
They would think I was the biggest, most horrible
something she considered clearly inappropriate. “I was
called to the principal’s oce to use a metaphor.” She
was “absolutely sure” that none of her male colleagues
who got angry at faculty meetings got called on it.
Latinas walk a Tightrope, just as other women do.
“You have to thread very nely,” said an engineer. You
have to “speak up your mind” without making your male
colleagues feel “emasculated. So it’s ne thread.” An
aggressive style works for men but not women, said a
Latina in clinical science. “A similar behaving woman would
not be received with respect, more likely be denigrated.”
Some felt expectations that women would be “soft,”
understanding, and “accommodating.” “[I] have to be
very assertive to be heard and sometimes people take
that as aggressive,” said a Latina immunologist, but if
you’re too feminine, “then they think you’re not smart
enough.” “You have to walk a very ne line,” remarked an
engineer, “You cannot let them walk over you. Otherwise,
you’re not going to get anything accomplished.”
25
Gender Bias Against Women of Color in Science
The Tightrope
to notch that dress code up a bit and call it a day. But
Latinas often felt caught. “You’re expected as a scientist
to look a little scruy and not well taken care of,” said
an immunologist. Note the conation of feminine dress
and being “well taken care of.” Lamented a biomedical
researcher, “So if you dress well, you get less respect.”
Just as Asian-Americans struggled to reconcile the
pressures to self-promote with the cultural mandate
to be modest, Latinas struggled to reconcile cultural
mandates of feminine dress with dress norms in science.
A biochemist nailed the dilemma: “You are kind of exotic.”
She had to “tone down” a lot so she is perceived as
“culturally neutral” when she presents her science. “…I
don’t want them to be distracted by my earrings or by the
loud print in my shirt or by my hair or whatever.”
A neuroscientist said she tried not to wear too much
makeup because “I don’t want to be perceived as less
than knowledgeable about what I do.” An engineer
recalled trying to look more masculine in the classroom
in order to establish her authority, given that other
signals (she felt) undercut it: that she was only 26, petite,
and had an accent. “I would wear always pants, pantsuits
just to try to assert a position out of fear that nobody
would see me as a gure that they could respect.
Latinas who didn’t eschew highly feminine dress often
were counseled to do so. When she moved institutions,
an engineer said, her dean took her aside and told her
to dress more professionally. “So it’s really dicult,
because if you dress the way that you want to dress, you
stand out.
Another engineer’s advisor coached her for a job
interview by telling her, “‘You don’t want to wear a pink…
owery dress … wear a nice dark-colored pantsuit.’”
Several other women had received similar advice.
Other women stood their ground and made their refusal
to conform a point of pride. “I cannot make them stop
thinking about, let’s say, the color of my shoes,” said
a Latina in biomedical research, “because they’re
checking them out as they’re talking to me, and that
used to annoy me a lot. But, I just ignore it and I just
keep talking about my science.” “I will dress in the way
that I feel comfortable, because if I’m dressed in a way
that I’m not comfortable, my whole game is o,” an
environmental engineer remarked.
Even women who refused to compromise on clothing
made allowances. The environmental engineer was
witch there ever was.” Both male and female students
expected women to be supportive and nurturing. “They
would never expect a male professor to respond well
for example with them like breaking down crying in their
oce. I denitely feel that masculine/feminine gender
roles, those expectations, I feel them on, yeah, a daily
basis….I’m pretty aggressive. I nd that both men and
women… are going to immediately… call [you a] witch. I’d
use another word but it would be rude. [chuckles.]”
Latinas reported literal housework and admin roles
never reported by other groups of women. A Latina
bioengineer reported male faculty who “expected
female faculty members to serve them tea or coee
or take notes.” Noted a Latina in biomedical research,
“They treat you like their mother, like they can get
whatever you can from you, and there’s no limit. Like, if
you keep helping, they keep asking.”
The most shocking example was of a Latina in clinical
science who was literally treated as an administrative
assistant. “I think there are times when I am asked
to be kind of the mother of the group,” she said. This
included tasks like making sure everyone lled out their
paperwork or setting up a meeting. “I play many roles
that…could be done by a competent administrative
assistant if we happen to have had a competent
administrative assistant, which we don’t.” She had tried
to get rid of these “administrative duties [that]…eat into
my time,” but without success.
Men have higher salaries, noted an engineer, but women
are expected to do more service. An environmental
engineer reported that male colleagues try to delegate
“managerial tasks, making copies, making sure that
everybody’s going to be on the meeting.”
Dress is an important issue. Many Latinas sensed a
tension between the way they believe a woman should
look and the dress expected of scientists. Respondents
widely acknowledged that scientists are “normally
blue-jeans-and-sneakers people.” Non-Latinas tended
The Latina scientists reported that both
students and colleagues expected them
to do oce housework.
26
Gender Bias Against Women of Color in Science
The Tightrope
you’ll completely shut them down.” Her solution was to
downplay her ambition, and instead present herself as
more communal—one of the team. A statistician agreed.
“I try to do it sweet and polite, but I make my point and I
say what I think…. When you are a woman, you have to
do that. If not, they will walk over you with heavy boots.
“There are smart ways of being assertive,” concluded a
biochemist, “and not-so-smart ways.”
One particularly astute woman in geography articulated
the strategy Professor Deborah Gruenfeld calls “playing
high” and “playing low” (Gruenfeld, 2013), using a
stereotypically feminine demeanor when you are with
people higher in status, and stereotypically masculine
demeanor when you are with people lower in status: “I
am really careful about the way that I present myself and
my image,” she said. “The way I present myself changes
depending on who I’m meeting with.” When she’s
meeting with high-level university ocials, she barely
talks and acts “shy and respectful. And I’m very clearly
like the subordinate person in the room. But then in other
meetings where I’m more familiar with people or I’m in
more of a leadership role, then I would act a lot more
direct and authoritative. But, at the same time, I’m still
known for always being like really nice and someone who
sort of comes up with little jokes, is fun at meetings.”
careful to wear “nothing revealing, nothing tight,
because I’m very careful because, Hispanics especially,
we like tight clothing. So I’m very careful to always look
for clothing for work that’s not overly tight, that is not
revealing.” A biochemist noted that, in Mexico “it would
be pretty common that we wear tight clothes and…
miniskirts, and I don’t do that here because…I wouldn’t
be considered a serious scientist, or my message
would be lost.”
Some Latinas used feminine dress to create room
for themselves to behave in highly valued masculine
ways. “I happen to be a very girly girl,” said another
engineer. “I like high heels, I like cute dresses. Actually,
that makes me stand out at conferences. I don’t try to
dress like a man with the pants and the pantsuits and
that kind of stu. I never do that. I don’t own a single
pantsuit.” She felt that, for the most part, her style
was received positively. She was very outspoken, she
said, and “aggressive, using the word that men use; but
what you see doesn’t match.” She’d been told she was
a contradiction, and “I think that actually has been a
positive thing in my career, because I surprise people.
It’s actually a good thing to surprise people, they
remember you.” This is gender judo: doing a masculine
thing (being assertive) in a feminine way (in a stylish
dress). It’s a common strategy women use to defuse
backlash against masculine behavior.
Gender judo. Latinas were much more explicit about
gender judo than were women of other groups. An
environmental engineer recalled her mentor warning her
that “trying to be the man didn’t work because people
immediately—you immediately get called the bitch.” Her
mentor recommended gender judo: “she just started
using her charm in the way that she talked to people,
smiling a lot, and she became a lot more of herself. And I
tried—and that really stuck with me.”
An engineer reported being told, “‘you’re very assertive
in a very sweet way.’ I get what I want in a very sweet
way…. Doesn’t antagonize anybody.” Note how she
does a masculine thing (being assertive) in a feminine
way (being sweet). Another Latina said that when she
needed to be assertive, “I try to do it more in a calm,
rm way. I actually think that’s worked really well for me.”
A statistician agreed, telling her younger colleagues that
they needed to “be pleasant but rm.”
A bioengineer noted that, particularly with older men,
one has to be careful “you’re not so aggressive that
“The way I present myself changes
depending on who I’m meeting with.
Gender Bias Against Women of Color in Science
Executive Summary 27
In terms of its impact on the careers
of women in STEM, motherhood is a
no-win proposition.
28
Gender Bias Against Women of Color in Science
Maternal Wall
Whereas mothers may well be seen as good mothers
but uncommitted scientists, women without children
often are seen as somehow lacking as full human
beings “without a life” (Cuddy & Wolf, 2013; DePaulo,
2006). This may explain why women without children
work the longest hours of any group of workers (Trades
Union Congress, 2008). Asian-Americans (34.5%) were
far more likely than other women to say they felt they
needed to spend more time working to compensate
for the schedule of other colleagues who are mothers,
followed by Latinas (23.8%). Black women (15.4%) and
White women (13.6%) were far less likely to say this.
There’s a stigma against scientists who have children
and a dierent stigma against those who don’t. In
terms of its impact on the careers of women in STEM,
motherhood is a no-win proposition.
Asian-Americans
Negative competence and commitment assumptions.
“I feel like people think that Asian woman, they are
caring and then they will give up their professions for
their children,” said an immunologist. Said another
Asian-American, “I have to ght very hard to show that
I am good scientist as well as a good mother.” “People
do judge women who have kids,” said another Asian-
American immunologist, and there’s “this perception
that if you’re a mother, you can’t be a high-achieving
scientist,” although she thought this was changing fast.
Other women did not note progress. “You can either be
perceived as the nurturer or extremely competent, but
it’s pretty hard to be perceived as both,” noted a chemist.
An Asian-American soil microbiologist put it slightly
dierently, saying you can either be “the superscientist”
or the “supermom,” but not both. An Asian-American
physicist described the sentiment that “if you had a full
blown career, that’s inconsistent with being a mother.”
Women in STEM often are competing against men
with stay-at-home wives. An immunologist noted this,
but also said that the full professors with daughters
were “actually a little bit more sympathetic because
they tended to have daughters who were going through
the same thing.” A soil immunologist found the most
support from her administrative assistant, who was
very supportive when she had to cancel class or a
EXPERIMENTAL STUDIES SHOW THAT THE MATERNAL
wall, once triggered, is by far the most damaging form
of gender bias. The most famous study gave people
identical resumes, one but not the other a mother, and
found that the mothers were 79% less likely to be hired,
only half as likely to be promoted, oered an average of
$11,000 less in salary, and held to higher performance
and punctuality standards (Correll, Benard, & Paik,
2007). Other studies (Benard & Correll, 2008) have
conrmed that motherhood not only triggers very
strong negative competence and commitment
assumptions; mothers also walk a tightrope: if they
are seen as indisputably competent and committed,
mothers tend to be disliked and held to higher
performance standards by women (although not by
men) (Benard & Correll, 2010). Evidently, women often
see mothers who work long hours as bad mothers—and
therefore as bad people.
The survey measured one form of maternal wall bias, and
found that Black (7.7%) and Latina (9.1%) scientists who
were mothers were far less likely than White (26.0%)
and Asian-American mothers (26.7%) to report that their
colleagues had communicated that they should work
fewer hours after their children were born. For Black
women, this nding may reect the stereotype that
Black mothers should work rather than stay home with
their children (Cuddy & Wolf, 2013). All groups tended to
attribute Maternal Wall problems to gender.
Maternal wall bias aects non-mothers too. One study
found that women without children encounter the
highest level of general workplace harassment of any
group (Berdahl & Moon, 2013).
There’s a stigma against scientists who
have children and a dierent stigma
against those who don’t. Mothers are
seen as uncommitted, while women
without children are seen as somehow
lacking as full human beings.
Maternal Wall
29
Gender Bias Against Women of Color in Science
Maternal Wall
an Asian woman, we give priority to our children and
family, how can you just leave your husband and be here.”
It hurt, she said, “I didn’t know what to say, and I didn’t
have the energy to ght these comments. I would come
back, and it would make me cry.” But her own mother
reassured her: “That’s why you’re dierent. You go ahead
in life. Don’t bother about them. Not everyone has the
smarts or has the sensitiveness, and you can’t just teach
everybody, just move on.” She did.
Pink-collar ghetto. Most of the women professors
interviewed were tenure-track, but a biologist who was
not highlighted the perils of the “trailing spouse”: “you
got hired on the soft money, and they start forgetting
the promises, and you nd…you are stuck….” She felt
cheated and angry.
Family care extends beyond children. A geophysicist
highlighted that minorities are more likely than other
Americans to have family care issues that extend
beyond children. “I think a lot of professors don’t
realize that often the successful minority student is the
most successful person in their entire family, and they
have to take care of everybody else.” Their caregiving
responsibilities can extend to “aunts and their uncles
and their grandparents and their parents and their
brothers and sisters and their brothers’ and sisters’
children, because even as a grad student, they could be
making more money than anybody else in the family.
A bright spot: one biochemist’s experience shows that
motherhood can t well with science. Asked whether
she had hit the maternal wall, she responded, “I’ve never
experienced this.” A single mother for over a decade,
she has had a very positive experience: “everybody who
meets me always congratulates me on how wonderful
daughter I’ve raised and how well accomplished I am in
my eld and something that I’ve always got accolades
on, both for my daughter and for my career… [N]one of
meeting “because she’s been through it and she is going
through it.
Mary Ann Mason and her team have documented that
the largest leak of women out of the STEM pipeline is
when they start families (Mason, Goulden, & Frasch,
2010). Women in graduate school are anxious about
how they can become both scientists and mothers, said
an Asian-American statistician. Upon learning she has
a child, students ask her questions like, “Is it possible
to have a kid and be an academic? Is it better to have a
kid while you’re doing your Ph.D. or when you’re doing
your post doc?” This happens, typically, with students
from other departments where all of the advisors are
male. She mentioned a colleague in biology who said
that, after the birth of her rst child, “the oodgates
opened and all sorts of female grad students and post
docs would come talk to her about this, because this is
something that nobody talks about very openly.
The irony, said a microbiologist, is that it’s not true that
mothers can’t succeed in science. She felt that mothers
“are actually more productive because they have a
set schedule. They have to come in at a certain time
because, at the end of the day, they have to leave and
go pick up their kids. So they’re a lot more organized.
They’re a lot more ecient…. They are very selective
about the meetings that they go to and get the most out
of that meeting.” Many others mentioned that scientists
who are mothers often are more focused and ecient
than their colleagues.
When it comes to motherhood, the U.S. “mindset is
kind of more backward than other country,” said an
immunologist originally from Taiwan, where, she noted
children are in school until 5:30 in the evening. Because
the educational system is not set up for working
mothers, she said, a lot of highly educated women have
to give up their jobs in order to educate their children.
Support from their families. Women from India and
China discussed how their mothers supported their
careers, and encouraged them to continue. When the
immunologist was thinking of quitting, her mother urged
her not to, reminding her that her children would grow
up, and lauding her for “trying so hard to hold on to your
dream and if you give it now, you might never get it back.”
She persevered. A geophysicist discussed having to live
on a dierent continent than her husband when her child
was a toddler. She felt judged by both by Europeans and
by some “Asian mothers themselves saying that, you’re
Many mentioned that scientists who
are mothers often are more focused
and ecient than their colleagues.
30
Gender Bias Against Women of Color in Science
Maternal Wall
but in a dierent tone of voice. One Black woman
recalled a colleague saying, “Wow, why are you here so
early? You should be home with the baby.” She found
herself “almost trying to explain to him, ‘No, no, no, it’s
okay. The baby is with my mother-in-law. She’s with
family.’” She later learned that his wife had stayed home
for the rst year of his child’s life.
When a supervisor believes that mothers “can’t do it
all,” noted a Black doctor, that becomes a self-fullling
prophecy. She recalled a colleague who ended up going
part time because the chief in her department was
“insensitive to that need of trying to be a parent and a
full-time employee.”
Maternal wall for women without children. While
women with children denitely reported bias against
mothers, women without children felt disadvantaged,
my faculty advisors have restricted me in bringing my
daughter to the lab, you know, have a little oce, and
she could sit with me as long as I was working. I was
allowed to work from home any time. So, yeah, I got it
really lucky in the last seven years on that front.” It’s not
impossible to combine science with children; one only
wishes more environments recognized that.
Black Women
Negative competence and commitment assumptions.
A Black microbiologist noted that she would never admit
it if she had to be absent to care for a family member
because to do so might be seen as her being “weak” or
noncommitted. “[T]here is an assumption,” said a Black
microbiologist without children, “that your career is
more of a hobby than a career, and you’re only going to
do it until you nd a husband and/or have a family. It’s
not taken as something that’s serious. You’re taken as
more of a passerby on your way home to be a wife and
mother.” A Black statistician recalled that a colleague
came up to her and told her she should be at home
with her child. A Black biochemist remarked that
women “always want to get their job before anybody
notices they’re pregnant. I was like, why would they
do that? Because it lowers my chances of getting the
job.” A Black microbiologist said that maternal wall bias
played a role in her decision not to have children: “Yes.
I was aware of it as early as high school, which is why I
decided as an adolescent never to have children.
Some Black women encountered race-specic
stereotypes. A microbiologist stated that, while “I don’t
have any data, being a Black woman with children gets
complex because the assumption is once you start,
you’re never going to stop. You’ll end up being a welfare
queen. So I also didn’t want to deal with that.
Hostile, and benevolent, disapproval of working
mothers. A Black microbiologist reported that a colleague
had been told that “she should go have little babies, she
should go home.” Similarly a Black mathematician recalled
women students came to her disturbed when a male
“professor told them that they shouldn’t be in this class,
that they should be at home having babies.
In addition to this “hostile prescriptive stereotyping,”
some also reported “benevolent prescriptive
stereotyping,” through comments that again send the
message that good mothers belong with their children—
31
Gender Bias Against Women of Color in Science
Maternal Wall
The tragedy is that it’s so easy to get it right. A Black
doctor recalled how worried she was when she had to
tell her supervisor she was pregnant. He surprised her:
“he’s actually very sensitive to the female faculty and the
fact that we have children.” He thinks the tenure clock is
“stupid,” she noted, because it penalizes women when
they want to have children. “I think he’s an anomaly.
[Laughter] but he actually gets it….Part of it, his wife is
a physician, so I’m sure she’s probably beat him over
the head and grilled some of this stu into him, which is
probably a good thing.
In another hopeful story, a Black statistician who
was “initially very fearful of sharing the news with my
department” also found a supportive response when she
nally got up the nerve to tell her department chair. He
asked why she stopped by and “I’m literally stuttering
through the statement saying that I just wanted to inform
you that I won’t be able to participate with the summer
program this summer. In my mind I’m watching his face
drop when I say this. Then I conclude, ‘Because I’m
expecting. Because I’m pregnant,’ and he lit up. Mind
you, this is male chair, right? He lights up, he gets—he’s
so excited. ‘Oh, I’m so happy for you.’ I was actually in
shock that he responded like this because I had braced
myself—ironically enough I was more prepared to face a
backlash than a happy response, right? I’m just standing
there a little stunned and taken aback and like oh, okay
[laughing]… my son was basically the department baby.”
STEM would lose far fewer women if more department
chairs reacted in this way.
Latinas
Negative competence and commitment assumptions.
Many Latinas reported maternal wall bias. “If you want to
have a family,” said an environmental engineer, “people
do put in question how much you want your career.” A
Latina bioengineer’s advisor told her, “Well, I don’t want
you to get your Ph.D.; you’re just going to get married
and have kids.” She reported she was “basically told to
too. A Black woman in microbiology felt that, although
she didn’t want children, “it’s something that individuals
are dying to know, because it’s almost, like you say,
they’re ready to hold it against me.” She recalled a Black
colleague asking her, when she described her job, “How
can you do that? Doesn’t your husband want babies?
Your husband will never get babies with you doing all of
that.” “I just looked at him and said, ‘Doesn’t your wife
want to do something other than have babies? She’s
pregnant every time I see her.’” She was told her salary
was lower than her male colleagues’ because they
had families to support. “The biases are there,” she
concluded. (Note that this is illegal sex discrimination.)
Family-friendly policies and the exibility stigma.
Black mothers, unlike those of other groups, discussed
the family friendly policies—and lack of them. One
scientist noted that her institution’s lack of clear policies
for how to temporarily replace women on maternity
leave left her “scrambling.” Others highlighted the
“exibility stigma”—the stigma often encountered for
use of stop-the-clock policies (Williams, Blair-Loy, &
Berdahl, 2013). Said a Black statistician, “other people
felt like they were doing me a favor and I’m like ‘You’re
not doing me a favor!’ [Laughs] ‘This is just, this is
the policy right now.’” You have a legal right to leave
under the Family and Medical Leave Act, she observed,
whereas “other people will try to make you feel like
they’re doing something special for you.”
Several women felt pressured not to use their institution’s
family leave policies. A Black electrical engineer recalled
a colleague who almost decided not to stop the tenure
clock. “But it is something that is clearly stated in the
rules, yet in practice, most of the female faculty that I’ve
spoken to and some of the male faculty did advise me
against doing it.” Note that this kind of advice can easily
be seen as illegal interference with Family and Medical
Leave. (Family and Medical Leave Act of 1993, 2006.)
A Black statistician noted that some of her colleagues
did not use her institution’s stop-the-clock policy. She
believes they chose not to do so because they do not
want to appear “weak” or as though they are receiving
“special consideration.” The same woman recalls she
was admonished by her doctor for her reluctance to ask
for maternity leave. Her doctor told her there was no
explanation for her health issues “other than stress.”
Several women felt pressured not to use
their institution’s family leave policies.
32
Gender Bias Against Women of Color in Science
Maternal Wall
by Robert Drago and his colleagues emerged in a
comment by a Latina engineer who said she had
decided, for now, not to have children because other
women in her department did not, and the wives of
the male faculty “are not working mothers, they are
at home taking care of the kids.” Of course, if young
women feel that they will not be able to have children if
they choose science, fewer will choose science—that’s a
price male scientists don’t have to pay.
Family pressures to have children. In the survey,
69% of both Latinas and Asian-Americans described
pressure from their families to have children (as
contrasted with 60% of Whites and 31% of Blacks),
but family pressure to have children emerged strongly
only in the interviews of Latinas—especially Mexican-
Americans. Said a Latina biochemist, “Every good
Mexican woman has kids in their 20s. Like I told you,
I’m not following the norm with my culture. I address
that like anything else. It’s like it’s my life, I will have kids
when and if I want them.” The notion that traditional
Chicano/Mexican culture “Places a higher premium on
motherhood” has been noted in other studies of women
of color in academia (Stanley, 2006).
Other women received the message not only that they
should have children but that they should not have
careers. Said a Latina bioengineer, “Family is extremely
important. Achieving for something higher, at least
in my case, it was seen as a waste of time. ‘Why are
you pursuing graduate school when you should be
working?’ or ‘Why are you pursuing graduate school
when you have a husband to take care of?’” Others
faced expectations that they would shoulder all or
most of the family work. “[B]eing a mother I think goes
across all cultures,” mused an immunologist, “and it’s
just a challenge for all. In terms of being a Hispanic
mother…our culture expects women to denitely be
the primary caregiver….99 percent of the work was my
responsibility.” A Latina doctor noted, “I feel like I have
a very specic role in keeping my family running,” a
pressure she saw as self-imposed.
Once again there were happy stories. A Latina engineer
who found out she was expecting shortly after she
accepted her position found that her “colleagues are
extremely supportive. I bring my child three times a
week into my oce. I take her up to the lab when I need
leave” when she had a child as a post-doc. Sometimes
the comments may be subtler, “like, ‘I called them, but
they’re never in their oce,’ or ‘They won’t be here after
a certain time of day,’” said a woman in anatomy.
More subtly, a Latina who runs a lab recalled that, after
she had a baby, colleagues related to her as a mother
rather than a scientist, “they thought that there was
nothing that they could talk to you other than, ‘Oh,
how’s your son?’” She recognized that they meant well,
“But, I have lots of other things to talk about.”
Even some women without children reported maternal
wall bias against colleagues with children. A biologist
recalled “Some guy saying he was not going to hire a
female research assistant because it’s likely that she
was going to get pregnant and then he’ll just have to nd
for maternity leave and those things.” One year, noted a
Latina engineer, “a lot of men especially started taking
me a lot more seriously because I was the single woman,
gung-ho, very career focused. So I was taken very
seriously by men.” An engineer spoke of a colleague
who returned to teaching three days after a Cesarean
section because “‘I don’t want to be perceived as not
doing my job because I have a kid.’ I said, ‘But you just
had a C-section.’”
Hostile disapproval of working mothers. Assumptions
that mothers were not committed were matched by
judgments if they were: A biomedical engineer reported,
“many people sayI would never let somebody else…raise
my children as if like our nanny is raising our children.
Some mentioned a double standard for mothers and
fathers. A Latina biologist noted that when men said
they had to leave to pick up their children, “people will
stop and say, ‘Oh, you are such a great dad. That is so
wonderful that you spend time with your kids.’” The
reaction when women did the same was very dierent.
Bias avoidance. The pattern of bias avoidance
(Bardoel, Drago, Cooper, & Colbeck, 2011) documented
Assumptions that mothers were not
committed were matched by judgments
if they were.
33
Gender Bias Against Women of Color in Science
Maternal Wall
Several Latinas expressed concern about losing a lot of
women scientists because they are pushed out after they
have children. Said one, “you’re just losing a lot of people
that eventually will probably still even go back to putting
in like even more time later on. I don’t know if that makes
any sense.” Latinas, like women from other groups,
pointed out that the mothers they knew had become
more ecient scientists since they had children.
Again, a simple way to keep women in STEM is not to
drive them out after they have children.
to, you know, set up stu. Nobody—if I need an extra
pair of hands, somebody will knock on my door, one
of the guys, and said, ‘Oh, let me hold the baby for a
little bit.’” Because of the support from her colleagues,
she felt no need to stop the tenure clock. She took six
weeks of maternity leave, and was encouraged to come
back slowly. “So, I really—I have had a very, very good
experience so far.”
A Latina biochemist had a similar experience. “[M]y
employer is a fantastic employer…. as an institution,
they get it that…women have a right to have babies…[and
take] maternity leave.” Noting that her department chair
is a “family man,” she said he set the tone for the rest of
the department. When she had trouble with a nanny who
did not arrive as planned, “…he basically said, ‘Just do
what you need to do to take care of your baby.’”
Gender Bias Against Women of Color in Science
Executive Summary34
35
Gender Bias Against Women of Color in Science
Tug of War
In addition, when asked more specic questions,
patterned conicts emerged. One is a pass-through of
Tightrope bias. As women walk the tightrope between
being seen as too masculine and too feminine, they
may end up judging each other for failing to achieve the
right balance. Roughly half of the scientists surveyed
agreed that “some women have just ‘turned into men.’”
Once again answers diered markedly by race/ethnicity.
Asian-American scientists were far more likely (70.5%)
to agree than were other groups (50.0% of Latinas,
48.8% of Black women, 42.1% of Whites).
Maternal wall bias also can be passed through from
woman to woman. Thus 41.7% of those surveyed agreed
that “some women just don’t understand the level of
commitment it takes to be a scientist.” This pattern
diered less by race/ethnicity: 42.1% of Whites, 38.6%
of Asian-Americans, 37.5% of Latinas, and 36.9% of
Black women agreed.
Another Tug of War problem is when women
professionals nd it dicult to get administrative
support personnel (who are typically women) to do their
work. This may occur because support personnel feel
more comfortable pushing back against women than
men, or because support personnel perceive men as
having more power to help their careers, or for other
reasons. “I have heard administrative assistants say
that they would not want to work with a woman boss—
because they’re harder to work with—which I thought
was astounding,” remarked one scientist. This was
relatively rare overall: only 18.2% of women reported
it as a problem. But Latinas were far more likely
(35.5%) to report it than were other groups (20.5%
of Asian-Americans, 16.9% of Whites, and 15.4% of
Black women). The interviews suggest this combines
racial and gender bias: One scientist was very aware
of the racial dynamic involved, saying “conscious or
unconscious,” there is resistance based on the fact that
“there is this Mexican woman telling them what to do.
“FEMALE RIVALRY IN THE WORKPLACE MAY
sometimes be as important as sexism in holding women
back in their careers,” opined an article in London’s
Sunday Times (Dobson & Iredale, 2006). But female
rivalry is often the result of sexism. Two 2011 studies
found that a common strategy for women experiencing
gender discrimination in the course of their careers was
to stereotype, distance themselves from, and criticize,
other women (Derks, Ellemers, van Laar, & de Groot,
2011; Derks, van Laar & de Groot, 2011).
An important proviso: by discussing the gender
dynamics that set women against each other, we are
not saying that women never support each other.
As has been noted, three-quarters (75.5%) of the
scientists surveyed reported that the women in their
environments supported each other. Nor are we
saying that women should support each other every
single millisecond: to say that would be to enforce
the prescriptive stereotype that women ought to be
endlessly seless and communal. Men don’t always
support each other, and when they don’t, the immediate
assumption is not that they have personality problems.
Instead our contention is that women’s workplace disputes
over gender play a much larger role in complicating oce
politics for women than do men’s disputes over gender
with men. The reasons for this are complex, and it’s
the bottom line that’s important—gender bias against
women often fuels conict among women.
The survey results highlight the complexity of this
phenomenon. Although three-fourths of the scientists
said that women support each other, Black women
(56.0%) were far less likely than other groups of
women to agree with this statement (70.5% of Asian-
Americans, 76.9% of Whites, and 78.9% of Latinas did).
Tug of War
75.5% reported that
the women in their work
environments supported
each other.
75.5%
Gender bias against women often fuels
conict among women.
36
Gender Bias Against Women of Color in Science
Tug of War
The three other types of gender bias also can fuel Tugs
of War.
Prove-It-Again pass-through. Older women who have
had to prove themselves over and over again may hold
younger women to higher standards than men. An
Asian-American in statistics described an experience
told to her by a woman colleague: “I did not know the
older senior female scientist personally, but as we
talked it became evident to me that the older woman
scientist probably had to go through hell to get to where
she was—you know to get to her senior position. Since
she had had to go through hell, she wanted to make sure
that everybody else had to go through hell.” As a result,
she said, her “junior scientist was just having a horrible,
horrible time of it.
Pass-through of Tightrope bias. If the Tightrope
often requires women to balance the masculine and the
feminine, women may be divided by dierent balances.
An Asian-American described a colleague who “was
very much the ‘I will bake cookies for my students, I’ll
pick up everyone’s plates after a lunch.’” Her colleague
asked her, “‘Well, how can you leave your baby at
home?’ It’s like ‘Well, I work. I don’t think babies need
to come to the Statistics Department.’ [Laughs] I have
colleagues, I mean, we all had kids about the same age,
but they were never questioned about ‘Was it okay for’—
you know, so somehow I wasn’t being feminine enough
by actually just coming to work. [Laughs].” Note how
the more stereotypically feminine woman judged her
colleague for making the wrong balance between being
too masculine and too feminine. Survey participants
suggested this is common: 51.4% agreed that “I feel
some women have just ‘turned into men,’ assimilating to
the way men run their careers and their lives.
In addition, sometimes women expect other women
to shoulder the kind of oce housework that is rarely
A nal pattern is tokenism, where women are forced to
compete with each other for the one “woman’s spot.”
About a fth (20.6%) of scientists surveyed reported
this, but the incidence varied a lot by race. About a third
of Black women (32.0%) and Asian-American (29.9%)
women reported this problem, as compared with lower
levels among Latinas (21.9%) and Whites (17.3%).
Some women reported no Tug of War because there
were too few women in their departments. Said one,
“It’s probably because, in engineering, there are very few
women, and it happens that I most of the time was the
only one.” An engineer agreed. “So I don’t think we have
enough females in the department or the school for
such patterns to happen,” she said.
Women often support each other. First, the good
news. Said a Latina biochemist, “the women in my
department and especially the women doing science
here in my institution, we are really—we bond together.
We support each other a lot. If anything, I’ve gotten
a lot of support.” “I’ve been very impressed at my
current workplace of this solidarity among women,
said another Latina scientist. An Asian-American
pathologist said, “[T]he women faculty I met that older
than me [are] always very encouraging, very helpful
and very kind to me.” An Asian-American geophysicist
agreed: “I’ve had senior women administrators been so
supportive with me that I have just good feelings and
good thoughts about that.”
An Asian-American soil microbiologist spoke of how
supportive other women were when her daughter got
sick “for quite a long time and so I actually ended up
getting behind in my research. Whenever I would sort of
go into this panicky mode of ‘Oh my God, will I ever go
back to writing papers?’—I actually had a couple of senior
colleagues elsewhere who [were]…incredibly supportive.
One of them very clearly said ‘You know, right now you
take care of your kid because she’s sick. Just remember
that way back, you knew how to do a Ph.D. so you know
exactly how to write papers. It’ll happen.’”
Nonetheless, the interviews and survey also reported
several classic Tugs of War.
Tokenism. A fth of the scientists surveyed (20.6%)
reported “I feel like I am competing with my female
colleagues for the ‘woman’s spot.’” Tokenism often
fuels conict among women, as politically savvy and
ambitious women vie for the woman’s spot.
Older women who had to prove
themselves over and over again
may hold younger women to higher
standards than men.
37
Gender Bias Against Women of Color in Science
Tug of War
your plan.’...I was a little abbergasted….I don’t think a
women’s group is synonymous with a mother’s group.
I felt like perhaps she was angry at women like me.
Mothers who feel judged for being mothers may sense
that it’s less risky to express anger at other women than
at men. At a simpler level, the harsh fact that women
of all races are often under hydraulic pressure to have
children may make women who don’t want children very
emphatic. For all these reasons, gender bias against
mothers turns into conict among women.
Conict between women scientists and their
female bosses and students. “Immediately,” said
a doctor, “the male doctor gets more attention than
the female. And it’s sad that it comes from other
female administrators and the non-professionals in the
system…that does occur a lot.” A grad student reported
colleagues who said they did not want to work with a
woman: “I’ve also heard females say things like ‘I want
a male boss.’ I’m like, why do you want a male advisor?
It makes no sense.… [T]hey have the feeling that well
maybe [a female advisor is], I don’t know, they call it PMS,
or something? That if she’s going to take it out on them,
that they are always very moody and stu like that. It’s a
female thing…. It’s, I don’t know, even within ourselves, I
still see the bias.” Years of studies document that it’s not
only men who stereotype women. Women do, too.
Asian-Americans
Tokenism. Many Asian-American women reported
the tokenism eect. One Asian-American in biophysics
pinpointed precisely how tokenism creates conict
among women, saying that when “each department
wants to have a female faculty” a department with two
women will nd themselves pitted against each other:
“one female will be the one to stay, the other one will
not. And I have seen that kind of situation.” An Asian-
American doctor pointed out that, if there were only one
“man’s position,” men would behave the same: “they’ll
ght to death among themselves to reach the top. So why
shouldn’t a woman do that?” Said an Asian-American
scientist, “Oh yes, the notion of there’s only room for one,
I face it very, very actively. As I told you, when I was hired,
I was hired along with this older woman at the same
position. And yeah, she still hasn’t given up. We both got
tenure. She tried to block my tenure. And also, there’s a
premium for being the rst X, right, woman, rst woman
blah, blah, blah. And the minute there’s another woman
extracted from men. Said an Asian-American, “I feel
that female leaders can be as bad as a male leader in
terms of gender bias.” Her female boss expected her
to edit her grant, a “secretarial job….And Im sure that
she will not ask men to do that.” This may be driven by
stereotyping—women are expected to be helpful—or it
may simply reect that the leader sensed the political
reality that asking a man to do this kind of work might
be politically more costly than asking a woman.
Mommy wars. Because mothers and women without
children encounter quite dierent types of maternal
wall bias, its not surprising to nd women judging
each other around issues related to children. On the
one hand, mothers may resent non-mothers on the
grounds that they have it easy. On the other hand,
non-mothers may resent mothers for getting “special
treatment” or for reinforcing stereotypes that women
need special treatment.
One scientist recalled conict over a women’s group
when another professor said “‘Well you just don’t
understand because you don’t want kids, and that’s not
38
Gender Bias Against Women of Color in Science
Tug of War
would deprive me of information or resources that I’m
entitled to.…I’m a person of color, they felt it was easier
for them to try and undermine me.”
An Asian-American geophysicist clearly recognized
that the tokenism eect disappears when women are
no longer tokens, saying “you reach this tipping point
where there can no longer just be one spot, that there’s
not a quota, we have to have our token woman, and
then you want to be that token woman—where sort of
having them around is just sort of more normal, it’s
not an oddity. And when you get to that point, then the
competition goes down because you’re not ghting for
that one position.
Tightrope pass-through. A self-aware Asian-American
physicist noted that “it does seem like there is a tightrope
of not too feminine, not too masculine.” She noticed
herself “wincing when some [undergraduates] seem
in my mind a little bit more feminine than I would feel
professionally comfortable with. On the other hand, I’m
happy that they feel comfortable being the way they are.”
Prove-It-Again pass-through. “I know women can be
very prejudiced against other women and if one woman
is in a higher position and could be super critical of
other women and wouldn’t support them,” said another
Asian-American. “They’re harsher to women in some
cases. Well, I think there are several reasons behind that
because the person at the top could be there because she
struggled a lot and had to work extra hard and so expects
other women to have done as much as she has.” Another
scientist agreed that sometimes happened. “I was very
much encouraged because I had a woman mentor.” In
fact, she noted, that’s why she went into her eld. “But,
I have seen how other—sometimes, it’s other women
harder on other women….‘Well, I had to ght my way to
the top. You need to do that, too, on your own,’ attitude.
Mommy wars. A simple, straightforward reason that
resentments arise between mothers and women
without children is that the latter often feel they get
work dumped on them by parents. Said one Asian-
American scientist, “People immediately assume
that because I don’t have children that I should be the
person who takes our colloquium guest every Thursday
when we have a colloquium to dinner, that I should be
there as the faculty member, because they all have their
wives and their great husbands and their children to
go back to, and someone who’s single basically can be
called upon to do this all the time….”
coming along the pike, you feel that you’ll be displaced
from this position of being like the rst tenured woman
or whatever, right, if you’re a senior older woman. We try
to take it for granted that women will help us, but they
almost never do. Why is that?” If there’s only room for
one woman to succeed, undercutting the competition is
a logical response.
Another Asian-American oered a slightly dierent
theory, saying that she felt some of her female
colleagues are “conicted.” On the one hand, they
want to help younger women. “And yet, at the same
time, they don’t want to lose their… power positions.”
Her approach was to acknowledge that she wouldn’t
be there absent the eorts of the older women: I
“remember to thank them and remind them that, without
them, I wouldn’t be here. I wouldn’t have made it. So
I’m continuously humble.” She noted “it’s the same in
general when… you express respect and gratitude to
your grandparents or even your great-grandparents
if they are still alive. You have to recognize what they
had to go through and appreciate what they had to go
through in order for you to have what you have today.
Here the Asian tradition of respect to elders clearly had
served her well in defusing potential conict.
Another Asian-American described a situation where
she and another woman of color, somewhat older
than she, joined their department at the same time:
“Intensively competitive because of that, because she
always felt she needed—she should have a higher salary
because she has more experience.” Studies show
that women tend to compare their salaries with other
women’s rather than men’s (Buchanan, 2005).
In addition, the tokenism eect can fuel conict among
women when White women attempt to deploy their
racial privilege to cushion the eect of gender bias. One
Asian-American described situations where “women
“[T]he minute there’s another woman
coming along the pike, you feel that
you’ll be displaced from this position of
being the rst tenured woman.
39
Gender Bias Against Women of Color in Science
Tug of War
the same deference as childcare. Said one woman,
“Because women like me who don’t have children, we
have extra burdens. Like we have more responsibility
on average. We’re taking care of our elderly parents,
right, because we are the single people in the family.
Everybody—siblings are married and whatever, and
those things—eldercare often comes on the plate
of single people. I don’t t. It makes me feel acutely
uncomfortable because I’m not interested in school
districts. That’s all they want to talk about. I have very
little in common with most of these people.”
Other women stressed generational divides. One
senior Asian-American noted how tricky it is for
women of her generation to give advice to younger
women. Sometimes, she noted, “advice from us are
not appropriate. Times has changed.” For example, she
noted that she had children later in life, but today you
“can start a family almost any time. Just have to work
out the problems and work out the situation. And—but,
sometimes, I still tend to think, ‘Don’t have a family that
soon,’ but then I realize that may not be a good advice to
the younger female faculty anymore.
Black Women
Tokenism. Black women were much less likely than
other women to feel that women in their environments
supported each other. In the interviews, there was less
talk of tokenism, and what there was concerned conicts
based on race, not gender. One Black woman noted that
sometimes there was a dynamic by which Blacks were
forced to compete because there was only room for
“one ‘chosen’ one.” Another described a senior woman
who, “when she’s speaking, she pretty much focuses her
attention on the men….So I’m thinking she might be one
of those type of women where, okay, there’s only room
for one.” She noted, “it’s been a survival tactic on their
part how to survive in a male dominated environment.
And so they probably are not even conscious of what
they’re doing.” Said another woman, “It was challenging
to sit on that committee and have other women discredit
what I had to contribute because I was a junior faculty
member, because I was the only African American
on this committee, and because I was coming from
a historically Black institution. And so, they have
stereotypes about that, too.”
Tokenism also led to generational conict. A Black
microbiologist found more senior women discouraging
Other Asian-American scientists without children
described resentment by mothers. Said an Asian-
American, “[T]he older White women, for them they
can’t handle the fact that I am single, living it up.” Said
another, “I don’t want to get married to some guy, some
random guy, and have 2.2 children because that’s what
everybody does. And until I meet somebody I really
want to be with, I don’t. I’m not interested in buying a
house and settling down. And so, I live in apartments
and I just have a single lifestyle. And that annoys all
these women no end.” Do they make snarky comments,
asked the interviewer? “Oh, totally.
Note how the mothers judge women without children.
Another woman recalled when a female colleague
“opined that the university ‘is full of these super ambitious
women like you who are so focused on their career that
they don’t have a concept of family. It has all passed
them by and that’s why we have not had childcare here,
because the university is lled with powerful women
like you,’ a really backhanded way, ‘Powerful women like
you who just don’t care.’” She continued, “Everybody
came up to me afterwards and said, ‘My God, you had so
much poise when this woman attacked you.’ This woman
didn’t even realize that she attacked me. She didn’t
even apologize.” She continued, “There’s an enormous
amount of resentment at women who, like my generation
now, are actually making a choice to be single. We are
not left on the shelf because we wear thick glasses and
we are unattractive and we can’t nd any man. We are
making a choice that, ‘You know what? I don’t like this
traditional marriage thing. I don’t want to do it. I am not
sure I want to have children, so I’m—my clock isn’t ticking.
And if it’s ticking, Im not listening.’” She continued, “I
have had many senior women come up to me and say,
“‘You should have children. It’s very selsh to not have
children….’ [S]he was trying to gure out if I was lesbian.
It’s just unbelievable.”
This dynamic is further fueled when women have
eldercare responsibilities that they don’t feel are given
“There’s an enormous amount of
resentment at women who are
actually making a choice to be single.
40
Gender Bias Against Women of Color in Science
Tug of War
to immunize herself against Prove-It-Again bias by
presenting herself as very feminine.
Tightrope pass-through. A Black biologist was very
self-reective about how her advice to a student
to “man up” may have reected the Tug of War. “I
remember having a graduate student that we worked
together on our PhD and that she more so had I guess
those traditional female qualities that if would say, you
know, kind of very passive or very soft spoken if you
want to say. And then, she cried a lot. And I remember
I would always tell her, you need to man up, you know,
stop all that crying, because they are going to keep
walking over you and keep criticizing you on your
research and your papers and things like that if you
don’t stand up and take charge….Probably I could have
told her in a dierent way.”
A Black doctor interpreted White women’s insistence on
empathy through a racial lens, referring to the “mammy
syndrome”: White women, in her view, expect Black
women “to be understanding and be kind of nurturing
her from trying to excel “because it wasn’t going to
do any good. Its kind of like, ‘You’re a Black woman.
You’re only going to get so far, so don’t worry yourself
out trying to go further than that.’” This is another very
pure example of how gender bias against women fuels
conict among women.
Prove-It-Again pass-through. A Black scientist
noted that, when she initiated a conversation, a female
colleague “told me that it wasn’t fair that I was allowed
to apply for a promotion” early, and that “I should go
through exactly what she went through in order to earn
promotion. And she had an awful experience.” Another
Black scientist described “a female colleague, and
she is much more feminine than I am in terms of those
stereotypical behaviors. When she fails to get something
done or she repeatedly makes the same mistake over
and over again, it’s dismissed. Oh, that’s just her, she
needs somebody to take care of her….But, when I do
something, I’m denitely held accountable for any minor
things that are not absolutely correct. And people get
really upset and angry.” Notice one woman’s strategy
41
Gender Bias Against Women of Color in Science
Tug of War
advised younger colleagues “not to take advantage of
their rights” to things such as maternity leave and stop-
the-clock. Another Black woman discussed her advisor,
who said, after she got pregnant, that after the grant
nished, she’d have to leave. “So it was very upsetting.
So I wrote a letter stating what I had done and how I had
kept up even though I had to take some time o. But,
essentially, she was saying, ‘Having a family is more
important for you. You should just stay home and do that.
I don’t think you can be—have an academic scientic
career.’” She was remarkably understanding, saying “You
have to deal with it and try to understand it and know
that they were doing the best that they knew how….[You]
could see in her face” that the senior woman had had
lots of disappointments, “and I think lots of regret.” In
her view, the senior women “didn’t mean any harm. They
were I guess trying to protect me from grief.”
Latinas
Tokenism. One Latina engineer observed that she has
seen women very much taking care of their turf. “It’s, ‘If I
let go of this turf, then who am I? I’m not going to let the
younger women in,’ even though I’m here telling them
that I will let them in. And when you hear the words it’s,
‘Yes, yes, yes. Let’s do this. I’ll let you in. I want you to
succeed.’ But when you start getting close to succeed,
the doors just start closing.” Another Latina, a doctor,
was very self-reective about how Tugs of War stem from
tokenism, specically from the tendency to compare
women with women. “I’m facing a dicult promotion
right now,” she said, “because I don’t have good NIH
funding. And one of my female colleagues who’s a few
years ahead of me, and she’s doing really well right now,
I’ll admit, I’m jealous. And part of it is every success that
she achieves makes me look worse….”
Prove-It-Again pass-through. A Latina engineer
described generational conict surrounding work-life
balance. The older women, she said, “were just very,
‘This is what we need to do. This is how we do it now.’
They just don’t care about anything else. They just want
to work, work, work, and prove themselves all the time.
I struggled with that a lot because I felt that you should
have a little bit more balance.”
Tightrope pass-through. One Latina reected on
women divided by the masculine-feminine balancing
act: “There’s so few females that if you are the type to
sort of dress up and be very girly you’ll be kind of on
because I’m Black and because I understand what it’s
like to be oppressed.
Conict between professionals and admins. Unlike
Asian-Americans, Black women and Latinas reported
a lot of conict between women professionals and
administrative support personnel. Said a microbiologist,
“I’ve noticed that administrative sta sometimes they
don’t respect people. I don’t even know if I would use
the word ‘respect,’ but I think they respond dierently to
when they have a male boss than a female boss. I’ve seen
it with my own eyes and it’s unfortunate.” She noted this
issue can become more complicated for women of color.
A few women also felt that admins expected women
professionals to do a specic kind of oce housework:
emotion work. Said a Black female doctor, “I do think
that there’s an expectation from female sta that the
female supervisors will be more—will be easier, will
be more nurturing, will be more understanding, for
example, if they have to leave if—because of their
families….” She continued: “sta are less tolerant of
women who are not like that….I think that often causes
problems between female sta and female supervisors.”
She also felt there was a racial dimension that fueled
conict between herself and White administrative
support sta. Black women support personnel, she
noted, “do not expect me to want to know anything
about their personal business. But yet, we are very
respectful to each other….I feel that I know these
women well and that we’re good colleagues and work
well together. And if I go and ask them for something,
they try their best to help me. And the same with me.”
But there’s “no expectation of knowing people’s lives.”
In contrast, “White women share a lot of personal
business, and it’s a bonding with them. And I don’t think
that that expectation occurs among Black women.
Mommy wars. Black women also spoke less of mommy
wars. An engineer noted that older colleagues sometimes
Black women were much less
likely than other women to report
that women in their environments
supported each other.
42
Gender Bias Against Women of Color in Science
Tug of War
young person be my boss and make me wait. You know,
I’m working 30 extra minutes here. This is completely
unacceptable,’ kind of thing.
Several other Latinas reported that support personnel
undercut their authority by calling women by their rst
name but men by their titles. Said one Latina, “sometimes
you go and talk to one secretary and there is a group of
faculty in the room and she addresses you by your rst
name but addresses everybody else as doctors. You’re
like well I’m also a doctor what is the dierence here?”
Mommy wars. The pass-through was clearest from the
comments of a doctor, who said, “People are surprised—
they’re still, even at this age, that they’re surprised that
you can have children and still continue to do research
and hopefully do good work. If you meet other women
that are not in science and having decided to be primary
caregivers to their children, those are the ones that
precisely tell you, ‘Well, I could never do that….’” Note
how one group of mothers is judging another group
as bad mothers. Another mother reected, “If women
don’t have children, then a scientist—we tend to
think, ‘Well, of course they can do great work.’…Then
sometimes we tend to ascribe their success to the fact
that they don’t have children…which is probably not fair
to them either.”
If mothers judge non-mothers, women without children
judge right back. Said an engineer, “I think at rst I
was a little bit shocked and hurt because I had been
working with her. It really made me say, ‘Hey, I’m not
just—I believe in family, and I believe in becoming a
mom. I believe in doing that, but I also believe in having
a career.’ It just made me push harder to get my degree.
Said a doctor, “There’s that interesting internal gender
bias with women who aren’t supportive of my decision
not to have a family, as if that undermines the whole
women’s cause. [chuckles.]”
your own because most of the females that are in the
department are not the girly type.
Conict between professionals and admins. Like
Black women, Latinas reported a lot of conict with
admins. One scientist was very aware of the racial
dynamic involved, saying “conscious or unconscious,”
there is resistance based on the fact that “there is this
Mexican woman telling them what to do.” “I have heard
administrative assistants say that they would not want
to work with a woman boss—because they’re harder to
work with—which I thought was astounding. This was
an older White woman who said this, who had been
working for a White male for a very long time and we
hired a minority woman and she did not want to work
for her. Her expression of that was, ‘I don’t want to work
for a woman.’ I don’t know how much of it was truly
gender or gender bias and how much of it was ethnic,
race related…It was easier to say, ‘I don’t want to work
for a woman,’ than, ‘I don’t want to work for a Latina
woman.’” Another Latina agreed that a racial dynamic is
sometimes involved, saying “most of the times female
bosses have a lot more resistance from other females in
the group, not from everybody, but it happens especially
if there’s a dierence in race.” She described a White
woman who had “a lot of resistance from African-
American women working under her.” Another Latina
also felt that “African-American females are much more
reluctant to work with a White female. It is a big, big,
big issue.” The interviewer asked whether they could
work with Latinas. “No, no, no. They will work with other
African-American women or with males.”
Others framed the issue as one of gender. An engineer
noted that admins expressed the view that their women
bosses were “too demanding. I said, ‘Well, but, the boss
that you had before was equally demanding. The guy
that you were working under was equally demanding.’
‘Yeah, but, it’s dierent.’ I said, ‘What is the dierence?’
‘Well, that she’s a woman. And she should understand
that we—sometimes we don’t want to do this.’ I said,
‘Well, no, but the thing is, the work is one, and it has to
be done.’ In particular, for example, that they will be
more lenient if they have to leave or if they don’t feel
like coming one day or there’s a deadline that they
have to allow them a little bit, slacking a little bit more
the deadline, which they would never do with a male
boss.” Others felt that age also played a factor. Said one
Latina, “I don’t know if it was also age….I was younger
than her….And she felt like, you know, ‘How could this
“[C]onscious or unconscious,” there
is resistance based on the fact that
“there is this Mexican woman telling
them what to do.
43
Gender Bias Against Women of Color in Science
Tug of War
these extra things for me because I have kids?’” She
continued, “they let me put the extra hours in for them
and let me put these extra hours—let me do this extra
thing and just one more….we’re actually bringing up
that kind of bias and trying to have a very open talk
between the women who have children and women who
don’t.” “Where it shows up most,” said an engineer, is
“when I’m writing proposals with women who do have
children, I always get sent the proposal by 5:00 p.m. and
be asked to have my revision back by morning because
they cannot work at night and I can.” “[T]hat happens a
lot,” she noted. Another Latina mused, “At the moment,
I was probably mad at the women that had children,
thinking ‘Why should I, who do not have children, pick
up the slack for the women that have children? It’s a
choice.’ And then, of course you think about this for
10 minutes, and you realize it’s not the women you
need to be pissed o at. It’s the men that make the
assignments….” Note how, at rst, her anger at gender
bias was directed against other women. Then she made
a self-conscious correcting, recognizing that gender
bias was also putting other women in a dicult situation.
Women without children have “no life.” Latinas
without children were far more likely than other women
to report assumptions that they should work all the
time because they had “no lives” outside of work, which
of course fueled resentment by the women without
children. One described the White male chair of her
department, who would say, “‘Oh, since you don’t have
children, can you please do this evening thing since you
don’t have a family to go home to?And so, one day
I said, ‘You know what? I have a family. It’s composed
of a husband, and I want to be home in the evening as
well. So you’re discriminating against me because I
have no children.’ And that put a pretty quick stop to
that….And if you are reluctant to get the mothers or the
fathers away from their children, then don’t have these
functions at night.”
Latinas reported that pressures on women without
children came from men as well as women. Said an
engineer, “a lot of my female friends who had children
started actually putting a lot on me as in, ‘We have
kids. Can you do this? Can you stay over this meeting?
Can you do this committee for me? Can you do all of
Gender Bias Against Women of Color in Science
Executive Summary44
I was in a car accident and was hit by an
18-wheeler truck…So when I drive next to
large trucks it took me a while to overcome
that fear…I was always cautious in being
around those types of trucks because it had
an impact on my life. And so someone who
has experienced some type of racism or
stereotype, it’s not going to be as easy for
them to get over it as you think.
– Black, female biologist
45
Gender Bias Against Women of Color in Science
Bias that Does Not Fit the Four Patterns Template
expressions of anger to race, whereas the other three
groups of women tend to attribute them to gender.
In addition, each group of women of color reported
experiences that dier substantially from those of White
women—and each other.
Black Women
Isolation. The interviews with women of color reected
a sense of bleak isolation not evidenced by Williams’
interviews of White women (using the same protocol)
(Williams & Dempsey, 2014). A microbiologist reported
“feelings of inadequacy” and “some depression,” which
she attributed to racial bias. “It just takes you longer,
she said, “because you really don’t have the support
that you need.”
This isolation sometimes reects exclusion. Said a
biologist, “So a lot of times, there are things that people
exclude me from because they say, ‘oh, she would be
uncomfortable….’[T]hey think for me… ‘Oh, well, she’s
going to be the only Black person there… just don’t
invite her, she won’t feel comfortable.’”
Another biologist described “Isolation… you don’t
know who you can trust….And alienating—this has
been a very lonely life.” Another scientist said she did
not socialize with her colleagues because, “when you
get to know people more socially, that’s where the—to
me, that lessens your authority.” She worried that, as
a junior person, if “it’s too social, then I think there’s a
greater risk of you being put in that subservient position,
or being looked at that way.” She attributed this
problem to gender, but it is a problem only Black women
mentioned—and they mentioned it often.
“Do I socialize with any of my colleagues?,” said a doctor.
“Not really.” Ocial oce parties she attended but just,
“‘Oh, it’s after work. Let’s go get a drink and hang out.’ I
don’t really do that and I guess part of that, particularly
with the men in the division, I don’t want to lose that
edge, I guess. I don’t want it perceived as, ‘Well, you
know, she comes out drinking with us. She’s just one of
us so we can treat her however.’”
ALTHOUGH WOMEN OF COLOR EXPERIENCE THE
same bias patterns encountered by White women (often
in somewhat dierent ways), they also experience
patterns of bias that do not t the Four Patterns template.
Most notably, nearly half of Black women (48.0%)
and Latinas (46.9%) report having been mistaken for
administrative or custodial sta, an experience far
less common for White (32.4%) and Asian-American
(23.3%) women scientists. Black women tend to
attribute this to their race (44.12%) while White women
(37.8%) and Asian-Americans (26.7%) tend to attribute
this to gender, with Latinas about evenly split (29.2%:
gender, 22.9%: race).
This reected a general pattern. Black women generally
were more likely than other groups to attribute bias to race
as opposed to gender. For example, Black women (43.8%)
tended to attribute prove-it-again problems with both their
colleagues and students to their race, whereas the other
three groups tended to attribute them to gender.
All groups of women tend to attribute tightrope
problems to gender. All groups of women tended to
attribute pressures to play traditionally feminine roles
to gender, although Black women and Latinas were less
likely to do so than Whites and Asian Americans. All
groups again attribute backlash for assertiveness and
self-promotion to gender, although race still is more
salient for Black women than for other women. Black
women were more likely to attribute pushback for
Women of Color also Experience Bias
that Does Not Fit the Four Patterns Template
48% of Black women
and 46.9% of
Latinas report having
been mistaken for
administrative or
custodial sta.
48%
46.9%
46
Gender Bias Against Women of Color in Science
Bias that Does Not Fit the Four Patterns Template
or more so oended. And so, when explaining the
situation in class many of the White female students
thought that they were being overly sensitive and
that they just needed to get over it.” Another biologist
recalled starting a new job where she was the only Black
person and a lot of people came in and started telling
her negative stories about people of color. “I didn’t
think much about it,” she said. “But I just thought it was
strange that she just came out and told me that her
parents just didn’t like Africans Americans and that they
still don’t now and that when African Americans moved
in their neighborhood during that time period that it was
a lot of tension. And I was just like, oh, okay.
Latinas
Isolation. Isolation came up less often among Latinas.
However, a Latina geographer had a dierent take on
social isolation, saying that White people are “afraid
of people of color in a way, like just worried about like
they’re going to say the wrong thing or do the wrong
thing. So they avoid that entirely.
Disrespect. A distinctive avor springs out from some
of the interviews of Latinas in STEM: disrespect. A
Latina in chemical and biomedical engineering learned
from a student that one of her colleagues had “called
me nauseatingly stupid in class to the other students.”
The comment still haunts her, she said. Every time
she doesn’t get a grant, “the rst thing that comes
to my mind is, ‘Well, he did indeed tell me that I was
nauseatingly stupid, and that’s probably why I’m not
getting this grant,’ even though I have grants….[T]here’s
a lot of that internalizing. And after talking to a lot of
women who are minorities, there’s a lot of that.”
Racial stereotypes. More commonly, Latinas
encountered racial stereotypes. “Just comments here
and there, assumptions people made, ‘Oh, you’re
Hispanic so you love tacos and you love spicy foods.’
That’s not true. Just, ‘Oh, you’re very into drinking and
music,’ and just stereotyping, a lot of stereotyping,” said
a bio-engineer. A neuroscientist recalled a “joke”: “‘Oh,
be careful. She’s Puerto Rican and she may be carrying a
knife in her purse.’”
A woman of Mexican heritage commented, “There
seems to be a stereotype that, if you are from Mexico,
you are lazy, and you only like to either sleep by a cactus
or party. And I’ve really battled extremely hard all of
Although Black women (41.7%) were the most likely to
report on the survey that “I feel that socially engaging
with my colleagues may negatively aect perceptions
of my competence,” many Latinas (37.5%), Asian-
American women (36.4%), and White women (31.8%)
reported the same thing—but this pattern showed up
only in interviews with Black women. “I do not discuss
personal things with people,” said a microbiologist.
Judge me for me, not my personal life.” She said she
kept her personal life separate because “I don’t want
anything in my family life to be used against me.
Racial stereotypes. Black women also reported being
openly confronted by negative racial stereotypes. The
post-doctoral advisor of a biologist “turns to me and
says, hey, do you have any family on drugs or in jail….”
Another recalled when a professor made a comment
about how she would understand about rats because
she came from an urban area “and everyone laughed. I
didn’t think it was funny. And that no one—and that the
other students, specically my colleagues didn’t—my
female colleagues didn’t understand why I was upset
47
Gender Bias Against Women of Color in Science
Bias that Does Not Fit the Four Patterns Template
to ask him.’ First, they assume I am the secretary for all
the faculty around, and second, sometimes they assume
I am the janitor, even during oce hours.”
Accent discrimination. One Latina also encountered
accent discrimination, noting that a colleague is “very
open with me, and he says, ‘Yeah, in the moment you
open your mouth and you have an accent, people
dismiss what you are saying,’ so my greatest barrier is
that people listen to what I say and not how I talk.” She
commented, “You develop a thick skin.”
Asian-Americans
Racial stereotypes. Asians also reported stereotypes,
notably the “forever foreign” assumption that they
were foreigners. Said a physicist, “I’ve had a number of
conversations where people ask me where am I from.
And the answer Im from Pittsburgh is really not what
they want, right? And the fact of the matter is that I
grew up in Pittsburgh, Pennsylvania, and I went to an
expensive private school and then I went to Princeton
and Cornell. So, I’ve had like sort of a really high end
Ivy League education, right? And I speak English
‘surprisingly well.’ I should speak English surprisingly
well,” she noted dryly.
Isolation. Again, isolation came up less commonly
among Asian-American women than among Black
women. But for some, it was a factor. Said an
astrophysicist, “I don’t look like anybody else along any
dimension. And that has been very, very isolating. Very,
very isola ting… .”
Demeaning comments. A biologist recalled a diagram
“to illustrate our department and the expertise and who
interacts with who,” drawn by the department head “with
three circles overlapping. I am in one of those circles way
out on the edge and I said, ‘You know if I am a little bit
more to the right, I would be outside the department.’”
Again, these kind of demeaning comments did not
emerge in interviews with White women.
Accent discrimination. An immunologist said that
her colleagues made fun of her accent when she was
a student. One told her, “oh, if you can speak English
without accent and then you can come back and
discuss with me….I was very angry. I reported to my
mentor” who told her “don’t ever write anything down if
you cannot say anything nice.” So she let it go.
these stereotypes. I work really hard at it.” Note how she
attributed her Prove-It-Again problems to race rather
than gender, and felt the brunt of negative competence
assumptions based on race. “I have actually heard
people discuss Hispanic people as being lazy,” said
a Latina in anatomy. “I immediately tell them that my
mother is Mexican-American, and that usually makes
them very uncomfortable. At which point I’ve even had
people say, ‘Oh but you’re just half.’” Another Latina
noted that pervasive image “of the friendly Mexican
or the passive Mexican or the disorganized Mexican,
you know, I am much more organized than the average
faculty member in my department. And the ethnic
stereotype wouldn’t tell you that. People would think
that, you know, we Mexicans are always late, and we’re
disorganized.” A woman originally from Brazil also
encountered stereotypes, saying that Whites “tend
to think Brazilians are very friendly and approachable.
Even I don’t know party animals maybe….Because the
only image that they show about Brazil most of the time
on TV internationally is Carnival, right, Mardi Gras. It is
soccer time and World Cup time when everybody’s on
the street jumping around and laughing and having fun.”
Assumed to be janitors. Latinas encountered
persistent assumptions that they were janitorial sta,
even if they had on white lab coats. A statistician said
that she accepted that perhaps she is around the lab
when other professors aren’t “but they assume that I
am the janitor, okay?... I always amuse my friends with
my janitor stories, but it has happened, not only at weird
hours.” She calmly informed someone that she only had
the key to the oce, not the janitor’s closet.
Assumed to be admins. Latinas also are assumed to be
administrative support sta. “First thing, for a woman,
they always assume I am the secretary of the faculty
around, so if they see my door open, they come and ask
me if doctor so and so, somebody that doesn’t have a
doctoral degree, but they assume, because he’s a man,
that it’s a doctor. They come and they ask me if doctor so
and so is going to come. I said, ‘I don’t know. You’ll have
“Yeah, in the moment you open your
mouth and you have an accent, people
dismiss what you are saying...
48
Gender Bias Against Women of Color in Science
Conclusion
women to do really well in sciences, and engineering,
and things like that, than it is for men,” she noted. “In
my society, I’m the man. [Laughter.] I’m not the woman.
The men in my society are your society’s women,” she
observed. She believes her strong, dominant manner
leads to clashes with male colleagues who expect her
to behave in a more subservient way. She recounted
that when she has a dispute with a White man, she often
seeks advice from White women on how to act. “It’s just
I can’t automatically receive that cultural information
that a White woman would [have], but I don’t.”
In sharp contrast, her concerns raised about the
Maternal Wall were similar to those raised by other
women. She observed that many women in her eld
“do not have children and delay childbirth for a very
long time to pursue career interests…. I’ve thought
about it myself, and I don’t know what the solution is. I
personally am planning to have children in my late 30s
simply because of the career issue. If you would have
asked me when I was 22, ‘When are you gonna have
your rst child?’ I was happy to think, ‘Oh, 27.… I’ll have
my career going by then. Things’ll be set.’ No. Wasn’t
true. Twenty-seven came and went. Then, when I was 27,
I did the readjustment. I was, ‘Maybe 31, 32.’ Nope. That
didn’t happen. Now, I’m, ‘Maybe 38.’ [Laughter.]”
This interview serves to highlight just how little we know
about the experience of women of color, how little we
know about how the experience of gender and gender
bias diers by race, and how little we know about how
racial bias is experienced in science. This report cannot
ll that void—far from it. But our hope is to help the
many well-intentioned people working to retain women
in STEM to forge new, more inclusive conversations in
which women’s varied experiences feel honored, and in
which a broad range of women feels included. 
OF THE 60 SCIENTISTS INTERVIEWED FOR THIS
study, only one was Native American. While she is not
necessarily representative, her viewpoint highlights how
race can deeply color the ways women of color experience
gender identity, and gender bias. While she said that each
of the four patterns of bias sounded familiar, she felt that
the challenges she had faced were attributable more to
“cultural dierences” between herself and members of the
“dominant society” than to gender.
She repeatedly raised the diculty she faces in relating
to her colleagues, particularly White men. “I come from
a totally dierent culture.” She likened her experiences
communicating with members of the dominant culture
to “two aliens meet[ing].” “There’s no common
understanding …” To be a scientist who is also a Native
American, “You have to be okay with being totally
ostracized in every way…. You have to be willing to
continually confront that.” Her lack of a support group
meant that she had to advocate for herself.
In addition, her experience of the Tightrope was unique.
She explained that the gender roles in her culture are
the “reverse” of the roles in “dominant society.” She
described how in her culture, women are considered
more condent and dominant and typically play
the “provider” role, whereas men are considered
“submissive.” “In our culture, it’s more common for
Conclusion
“You have to be okay with being totally
ostracized in every way.
49
Gender Bias Against Women of Color in Science
Bias Interrupters
4) RATCHET UP IF NECESSARY. A stronger interrupter
would be to have the department chair negotiate all
start-up packages, described below.
Example: Oce housework
1) ASSESS. Use interviews or focus groups to identify
the kinds of “oce housework” that exist in your
department. Here are some common types:
• Routinehousework:Planningparties,scheduling
meetings, ordering supplies, taking notes, doing
other administrative tasks or (literal) housework.
• Undervaluedwork:Mentoringotherpeople’s
students, serving on low-power committees,
putting on programs for students, etc.
Once you have identied the oce housework,
develop objective metrics to measure who is doing
it, e.g., by analyzing the membership of high-power
versus low-power committees over a period of years;
or a survey given to both male and female faculty
members asking whether they have done various
tasks (e.g. planned a party, mentored another
professor’s students, ordered equipment).
2) IMPLEMENT A BIAS INTERRUPTER. If women are
planning the parties, assign an admin to plan the
parties. If women are ordering equipment, establish
a rule that each professor orders his or her own
equipment, or that admins order all equipment.
If women are mentoring other people’s students,
implement a system whereby professors notify the
department chair each time they mentor another
professor’s students.
3) MEASURE. Follow up to see whether the
“housework” is more evenly distributed among
professors.
4) RATCHET UP IF NECESSARY. For example, if women
are still mentoring far more students than men, it may
be time to establish clear rules, e.g. that professors
all make time to mentor their own students, or that
professors who spend a lot of time mentoring the
students of others are relieved of committee work (on
the grounds that their service is mentoring).
Most of the research on interrupting subtle bias has
focused on self-monitoring (e.g., Rudman, Ashmore,
Gary, 2001). Williams has developed a dierent
approach that focuses on redesigning basic business
systems to interrupt subtle bias in real time (Williams,
2014), a model of organizational change called “Metrics-
Driven Bias Interrupters.”
The basic model has four steps:
1) ASSESS. Using interviews or focus groups,
investigate whether, and how, subtle bias is playing
out in your institution in hiring, Rank and Tenure
processes, compensation, and elsewhere. Where
bias is suspected, identify an objective metric that
will measure whether bias exists.
2) IMPLEMENT A BIAS INTERRUPTER. Put in place a
Bias Interrupter.
3) MEASURE. Measure to see if the intervention
interrupted the bias eectively enough so that the
metric improved.
4) RATCHET UP IF NECESSARY. If the metric did
not show improvement, strengthen or modify the
Interrupters until it does.
This report will allow STEM departments to jump over
the rst step of determining whether subtle bias exists,
and move directly to developing objective metrics to
assess how the bias is playing out in everyday ways.
Example: Start-up packages
1) ASSESS. Measure start-up packages of men and
women in your department. Is there a patterned
dierence? While you are at it, compare the start-up
packages of dierent racial groups.
2) IMPLEMENT A BIAS INTERRUPTER. Change
procedures to interrupt bias. You might start
with a gentle interrupter, say by assigning each
professor a mentor as soon as a job oer is made,
with a mandate to help the candidate successfully
negotiate a fair start-up package.
3) MEASURE. Did the metric improve?
Bias Interrupters
50
Gender Bias Against Women of Color in Science
Bias Interrupters
4. How to conduct a search process to control for bias.
For an excellent, evidence-based protocol for the search
process that is designed to control for bias, see http://
advance.cornell.edu/documents/Vet-School-Search-
Process.pdf.
5. Require an evidence-based bias training of each
search committee. For examples: http://search.
committee.module.rutgers.edu/otherAAUs.shtml.
A training available to all will soon be posted on
toolsforchangeinstem.org. Best practice: the University
of Florida requires that every search committee
member participate in an online training module; a
refresher course is required every three years.
6. Manage the campus visit to control for bias. For an
excellent, evidence-based protocol for how to handle
the campus visit to control for bias, see http://advance.
cornell.edu/documents/Managing-the-Campus-Visits.
pdf.
7. Provide structured way to provide feedback on the
candidates. For an excellent form designed to control
for bias, see http://advance.cornell.edu/documents/
CandidateEvaluationTool.pdf.
8. Legal and illegal questions. For a good brief
guide, see http://www.hr.umich.edu/empserv/
department/empsel/legalchart.html. A fast-growing
area of employment law involves lawsuits by mothers,
and others, for discrimination based on family
responsibilities. To avoid problems, see http://advance.
cornell.edu/documents/October2010EmployerAlert.
doc.
9. Dual-career hiring and other family friendly policies.
Women scientists are far more likely than male scientists
to be married to other scientists, so a dual-career hiring
program is vital to successful recruitment of women. For
a good model universities can use in preparing an FAQ for
search committees, see http://www.advance.rackham.
umich.edu/FAQDualCareer.pdf. For a good guide for
university administrators on how to establish a best-
practice program, see http://gender.stanford.edu/sites/
default/les/DualCareerFinal_0.pdf.
11. Start-up packages. Women who negotiate hard
tend to encounter backlash (Bowles, Babcock & Lei,
2007). Some department chairs at the University of
Michigan negotiate for resources with a list of requested
items from potential new hires. http://worklifelaw.org/
wp-content/uploads/2013/01/Eective-Policies-and-
Best Practices
Throughout recruiting, hiring, tenure and
promotions processes
1. Send a clear message that stereotypes exist, but
that they can be overcome—and that the institution
has a commitment to controlling them. An experiment
found that merely informing people of the existence of
stereotypes risks increasing the penalties incident to
stereotyping. This can be controlled by communicating
that a “vast majority of people try to overcome their
stereotypic preconceptions”—a simple statement
that sharply reduced stereotyping, and the penalties
to diverse candidates often associated with it. http://
psycnet.apa.org/psycinfo/2014-43472-001.
Recruiting and hiring
Guide to best practice: http://sitemaker.umich.edu/
advance/les/HandbookforFacultySearchesandHiring.
pdf.
1. Dening the parameters of the search. Dening
the parameters of the search in too narrow a way can
bleach women out of the application pool in many
elds, particularly those with few women. For excellent
guidance on how to dene a search, see http://advance.
cornell.edu/documents/planning-the-search.pdf.
2. Drafting the advertisement. Ads that use masculine
gendered words like “competitive,” “assertive,” and
“ambitious” tend to decrease the number of women
applicants (Gaucher, Friesen, & Kay, 2011). Because
women in STEM are far more likely than men to have a
professional spouse, it is important to signal openness
to dual-career hiring. For a good example of language
that signals openness to diversity and dual-career
hiring, see http://advance.cornell.edu/documents/
Sample-Lang-for-Ad.pdf.
3. Reviewing resumes. When women musicians began
to audition behind a screen, the percentage of women
hired by symphony orchestras increased by 46% (Goldin
& Rouse, 2000). Initial resume screenings should be
blinded for race and gender wherever possible. Establish
criteria before screening begins to avoid “casuistry”: an
experiment found that, when a man had more education,
subjects tended to choose the man and cite education as
important, whereas when a woman had more education,
they tended to hire the man and cite experience as
important (Uhlmann &. Cohen, 2005).
51
Gender Bias Against Women of Color in Science
Bias Interrupters
Climate
In addition to the many excellent climate surveys
available on-line, two specic issues emerge from the
bias literature.
1. “Screamers” and Bullying. A department climate that
tolerates bullies and “screamers” will systematically
disadvantage women and people of color. This is
because prescriptive gender bias means that women
often are punished for open displays of anger even
in environments where men nd that displays of
anger actually increase their status (Brescoll &
Uhlmann, 2008). Both Black men and Black women
tend to encounter backlash if they are seen as “angry
Blacks.” In addition, in a social context where Latinos
(probably of both sexes) are often written o as overly
emotional (“ery Latins”) even if they don’t show anger,
open displays of anger may well also carry negative
consequences for Latinos.
2. Self-promotion. A departmental climate that
encourages open self-promotion also will systematically
disadvantage women. This is because prescriptive
gender bias means that women who self-promote often
trigger dislike and other forms of backlash, even when
men are doing precisely the same thing (Rudman,
1998). The Interrupter is to limit self-promotion to
formal contexts or, if that’s impossible, at least to
establish formal ways in which women can publicize
their accomplishments in a way that seems socially
appropriate. Examples are a monthly email from the
Chair publicizing publications, conference presentations,
grants, prizes and other accomplishments of members
of the department or—better yet—a section of
departmental meetings that does so. This also will help
modest men, who encounter pushback when they don’t
self-promote (Moss-Racusin, Phelan & Rudman, 2010),
as well as Black men, who often encounter a backlash
when they do (Hall & Livingston, 2012).
Trainings
An inuential study found that trainings did not improve
outcomes for women and diverse candidates (Kalev,
Kelly, & Dobbin, 2006). This study did not control for
the quality of the training provided. Its ndings probably
were inuenced by the many unscientic, sensitivity-
type trainings oered by diversity trainers.
Particularly in science, evidence-based trainings are
required. The ideal is where information about subtle
Programs-for-Retention-and-Advancement-of-Women-
in-Academia.pdf#cb2.
Committee Assignments & Other Oce Housework
Divide high-prole glamour work committees from low-
prole “oce housework” and keep track of how many
committees and other service obligations male and
female faculty have. If there’s a signicant imbalance,
interrupt the bias by redistributing assignments (or
at least limiting the number of low-power committees
women serve on).
Promotion and Tenure
1. Self-promotion. Processes that require people to
brag will push women onto the tightrope—disliked but
respected if they do, and liked but not respected if they
don’t (Rudman, 1998). Self-promotion should be limited
to formal contexts in which both men and women are
sent the message that everyone is expected to share his
or her accomplishments. Best practice: the department
chair asks everyone for their accomplishments
periodically and sends around a list. Best practice:
establish a norm discouraging self-promotion in
informal contexts.
2. Language in P & T Letters. Put language in all Rank
and Tenure letters to ensure that people are not
penalized for stopping-the-clock and/or using parental
leave policies, following the example of the University of
California, Davis. http://worklifelaw.org/wp-content/
uploads/2013/01/Eective-Policies-and-Programs-for-
Retention-and-Advancement-of-Women-in-Academia.
pdf#cb2.
3. Bias check. Have someone trained in the Four
Patterns of Gender Bias read through all P & T letters
to check for common patterns of gender bias. Provide
a feedback loop to faculty colleagues whose letters
consistently reect bias; obviously, this feedback loop
has to be designed carefully in order not to trigger
backlash. Trainings will soon be available at www.
worklifelaw.org.
4. Student evaluations. Evaluations should be presented
as distributions rather than averages, in order not to
penalize women for polarized evaluations (Fleming,
Petty, & White, 2005; Linville & Jones, 1980). When
evaluations are polarized, analyze whether the dynamic
has been aected by race and/or gender. Provide
coaching for women and minorities who have polarized
evaluations.
52
Gender Bias Against Women of Color in Science
Bias Interrupters
biases is built into trainings that also cover other, “hard”
topics. An example is a Training for Search Committees
that discusses their duties and university procedures,
and also discusses how biases can creep into hiring
decisions. Bias training should be incorporated into
annual workshops for Department Chairs and Search
Committees.
For online trainings to address gender bias in
STEM, see http://www.toolsforchangeinstem.org/
workshop-catalog/ and http://www.hunter.cuny.edu/
gendertutorial/tutorial1.html.
For an online training on bias designed for department
chairs, see http://www.toolsforchangeinstem.org/
workshop-catalog/ (Building a Department in an Era of
Tight Budgets: It’s Cheaper to Keep Her).
For an online training that focuses on how to avoid
legal liability related to gender bias, see http://www.
toolsforchangeinstem.org/workshop-catalog/ (Some
Things Are Illegal).
An eective model for delivering bias training is the
STRIDE program at the University of Michigan. STRIDE
recruits full professors to participate in an ongoing
committee that provides advice on how to recruit
and retain a diverse faculty. Each STRIDE member
attends three half-days of training and reads from a
recommended reading list. They receive teaching relief
for participating in the program. Colleagues then can
request that a STRIDE member lead workshops for
department chairs, search committees, and in other
venues to educate their peers.
Parenthood and family caregiving
For trainings for department chairs and others
on parenthood and science, see http://www.
toolsforchangeinstem.org/workshop-catalog/ (Do
Babies Matter?; The Competitive Edge: Best Practices
for Family Friendly Policies).
For a comprehensive list of best family friendly
practices, see http://www.worklifelaw.org/pubs/
worklife_academia_FINAL.pdf.
53
Gender Bias Against Women of Color in Science
Appendix A
Survey respondents were recruited through the
Association for Women in Science (AWIS), which sent
emails to its membership recruiting participants.
Interviewees also were recruited through AWIS.
Interviewees, who are all scientists, were equally divided
between Latinas, Asian-Americans, and Black women,
with one interview of a Native American.
Breakdown of survey respondents:
Race of Respondent N %
White/Caucasian 398 72.4%
Black/African-American 26 4.7%
Hispanic/Latino 32 5.8%
Asian 45 8.2%
Native-American 2.4%
Pacic Islander 00%
Mixed Race 39 7.1%
Other 81.5%
Total 550 100%
Appendix
54
Gender Bias Against Women of Color in Science
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Joan C. Williams
Distinguished Professor
Hastings Foundation Chair
University of California,
Hastings College of the Law
Katherine W. Phillips
Paul Calello Professor of Leadership & Ethics
Senior Vice Dean
Columbia Business School,
Columbia University
Erika V. Hall
Assistant Professor of
Organization & Management
Emory University
Goizueta Business School
Published online at www.worklifelaw.org.
© 2014 Joan C. Williams, Katherine W. Phillips &
Erika V. Hall
... Asian American female students experience educational environments as both racialized and gendered spaces and face additional challenges when the model minority myth and the perception Asians are innately good at science and math collide with stereotypes of women as low performers in technical fields as well as perceptions of Asian American women as submissive, passive, and obedient (Hune, 2006;Patel, 2008;Williams et al., 2014). Some Asian American women also experience distinct forms of marginalization, sometimes from within their respective communities. ...
... In a study of women of color scientists, Williams et al. (2014) revealed that Asian American women felt the need to provide more evidence of competence than men to be viewed as equally competent than any other ethnic group, including White women. In fact, the findings suggested Asian American women's experiences were shaped more by the negative stereotype of women as low performers in science or not as technically competent as men than the positive stereotype that Asians naturally excelled in science. ...
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National efforts to improve equitable teaching practices in biology education have led to an increase in research on the barriers to student participation and performance, as well as solutions for overcoming these barriers. Fewer studies have examined the extent to which the resulting data trends and effective strategies are generalizable across multiple contexts or are specific to individual classrooms, institutions, or geographic regions. To address gaps in our understanding, as well as to establish baseline information about students across contexts, a working group associated with a research coordination network (Equity and Diversity in Undergraduate STEM, EDU-STEM) convened in Las Vegas, Nevada, in No-vember of 2019. We addressed the following objectives: 1) characterize the present state of equity and diversity in undergraduate biology education research; 2) address the value of a network of educators focused on science, technology, engineering, and mathematics equity; 3) summarize the status of data collection and results; 4) identify and prioritize questions and interventions for future collaboration; and 5) construct a recruitment plan that will further the efforts of the EDU-STEM research coordination network. The report that follows is a summary of the conclusions and future directions from our discussion.
... Numerous studies highlight the potential problems women face in male dominated STEM occupations. In the US, for example, Williams et al. (2014) find that 34.5 per cent of women working in science had reported sexual harassment. Scientists conducting fieldwork were at even greater risk, with two-thirds (64 per cent) of researchers surveyed internationally experiencing sexual harassment, mostly at the hands of a senior researcher. ...
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... With respect to uncivil treatment, 20% of women and 22% of Black employees reported experiencing small, repeated slights at work, as compared to 4% of men and white employees (Funk & Parker, 2018). Similarly, some scholars have asserted that racialized women working in science and engineering are at increased risk for biased treatment than men and white women (e.g., less access to desirable assignments/teams and being asked to continually prove their competency), as their belonging can be challenged because of both their gender and racial identities (e.g., Ong, Wright, Espinosa, & Orfield, 2011;Williams, Phillips, & Hall, 2014;Williams, Li, Rincon, & Finn, 2016). ...
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There is little scholarly evidence describing the gendered and racialized climate faced by women in Canadian academic natural sciences and engineering (NSE). We address this gap with a sociological examination of selective incivility, harassment, and discrimination amongst NSE faculty from 12 Canadian universities; asking if women, and racialized female faculty in particular, are more likely to experience mistreatment at work than their white, male colleagues. Analyses of survey data indicated that women were significantly more likely to be mistreated by their co-workers and students than male faculty. Moreover, harassment and discrimination were associated with greater professional marginalization for women, including delayed advancement. Thus, taking a sociological approach to interpersonal mistreatment emphasizes the connection between employee interactions and structural gender inequality in male-dominated NSE. We found mixed evidence with respect to race: racialized women reported less co-worker and student mistreatment than their white female counterparts, but these results were only marginally significant; and racialized men reported significantly more harassment and discrimination than white men. As such, our findings suggest the importance of investigating the organizational employment setting to better understand which workers are at greater risk for mistreatment in different job contexts.
... It is also important to recognize that students possess multiple identities that interact, resulting in unique lived experiences. Black women, for example, encounter a combination of challenges that cannot be understood through their race or gender alone [22,44]. Efforts to expose undergraduate students to counter-stereotypical examples of scientists have the potential to narrow equity gaps and broaden participation of marginalized and under-represented groups in STEM. ...
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Background Previous research shows that men often receive more research funding than women, but does not provide empirical evidence as to why this occurs. In 2014, the Canadian Institutes of Health Research (CIHR) created a natural experiment by dividing all investigator-initiated funding into two new grant programs: one with and one without an explicit review focus on the caliber of the principal investigator. Methods We analyzed application success among 23,918 grant applications from 7,093 unique principal investigators in a 5-year natural experiment across all investigator-initiated CIHR grant programs in 2011-2016. We used Generalized Estimating Equations to account for multiple applications by the same applicant and an interaction term between each principal investigator’s self-reported sex and grant programs to compare success rates between male and female applicants under different review criteria. Results The overall grant success rate across all competitions was 15.8%. After adjusting for age and research domain, the predicted probability of funding success in traditional programs was 0.9 percentage points higher for male than for female principal investigators (OR 0.934, 95% CI 0.854-1.022). In the new program focused on the proposed science, the gap was 0.9 percentage points in favour of male principal investigators (OR 0.998, 95% CI 0.794-1.229). In the new program with an explicit review focus on the caliber of the principal investigator, the gap was 4.0 percentage points in favour of male principal investigators (OR 0.705, 95% CI 0.519- 0.960). Interpretation This study suggests gender gaps in grant funding are attributable to less favourable assessments of women as principal investigators, not differences in assessments of the quality of science led by women. We propose ways for funders to avoid allowing gender bias to influence research funding. Funding This study was unfunded.
Chapter
This chapter documents the experiences of the ongoing journey of an African American female physicist. They correspond to those in documented studies of other African Americans and females in both the specific field of physics as well as the broader area encompassing Science, Technology, Engineering, and Mathematics (STEM). While there are some anomalies, when scaled with the norm of these groups, there is a thread of consistencies in the obstructions and difficulties that seem to be unique to mostly African Americans and on a smaller scale to White females. The intent of this writing is to shine a light on the status of affairs particularly in the scientific Ph.D. community, an area that many have felt was immune to the difficulties faced by African Americans on the lower end of society. It is evident that our society is neither “post-racial” nor “post-sexist”, even on the higher intellectual turf.
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The aim of this article is to discuss the position of ethnic minority women (Hungarian, Slovak, and Romanian) in relation to their career-building in the Serbian higher education system and reaching decision-making positions (such as rector, vice-rector, dean, head of department, etc.). The author defines two hypotheses: (1) that there are invisible biases (gender-based, ethnicity-based, and segregation-related) in the sciences that put ethnic minority women in a challenging position when attempting to build a career in academia, and (2) that these women encounter a glass ceiling when trying to reach more senior positions. The analysis is based on 16 semi-structured interviews conducted with Hungarian, Slovak, and Romanian female teaching staff employed at two Serbian universities. Intersectionality as a theoretical framework and method was used in the analysis of interviews, along with narrative analysis. Analysis of the interviews showed that ethnic minority women adopt specific strategies when discussing and explaining their difficulties and opportunities in the higher education system of Serbia. The intersectional analysis indicates that ethnic minority women struggle with invisible biases at the individual level, and, due to the horizontal segregation in sciences, have to overcome a situation of double jeopardy in Science, Technology, Engineering and Mathematics (STEM) studies. The findings suggest that women from ethnic minorities face a glass ceiling in relation to obtaining decision-making positions. Namely, such positions are usually only guaranteed to them within their own ethnic enclaves at departments with majority female staff. However, positions higher than these are rarely attainable.
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Stepping Up Women's STEM Careers in Infrastructure: An Overview of Promising Approaches describes a variety of ways to level the pathway for women entering into and progressing in science, technology, engineering, and mathematics (STEM) employment within the infrastructure sectors—energy and extractives; water; transport; and digital development. It is composed of three volumes : Volume 1 distills the findings from an extensive literature review, a global stocktaking exercise, key informant interviews, and five case studies in order to provide World Bank Group project teams with insights that they can use to support women’s STEM careers in infrastructure at each stage of their careers—from initial attraction to the sectors and job recruitment, to retention within organizations, and advancement to managerial and leadership roles. The report is intended to underpin and expand the existing knowledge on gender equality issues, under the World Bank’s Energy Sector Management Assistance Program (ESMAP).The case studies featured form part of the insight captured in the associated report Stepping Up Women’s STEM Careers in Infrastructure: Case Studies (Volume 1). Volume 2 is composed of five case studies that describe a variety of contexts in which measures are being implemented to attract, recruit, retain, and advance women in science, technology, engineering, and mathematics (STEM) roles in the infrastructure sectors across Ethiopia, the Lao People’s Democratic Republic (Lao PDR), North Macedonia, Panama, and Solomon Islands. The first three case studies profiled in this document focus specifically on recruitment, retention, or advancement. The remaining two case studies focus on organizations that are tackling the issue of women’s underrepresentation holistically, in each of the crucial stages of a woman’s career. The case studies featured form part of the insight captured in the main report Stepping Up Women’s STEM Careers in Infrastructure: An Overview of Promising Approaches (Volume 1). Volume 3 summary note provides a brief overview of some of the findings from an extensive literature review, a global stocktaking exercise, key informant interviews, and five case studies (featured in Volume 1 and 2) in order to provide World Bank Group project teams with insights that they can use to support women’s STEM careers in infrastructure at each stage of their careers