Soc Psychol Educ (2012) 15:427–448
DOI 10.1007/s11218-012-9185-3
Why they leave: the impact of stereotype threat
on the attrition of women and minorities from science,
math and engineering majors
Maya A. Beasley · Mary J. Fischer
Received: 26 May 2011 / Accepted: 20 March 2012 / Published online: 23 June 2012
© Springer Science+Business Media B.V. 2012
Abstract This paper examines the effects of group performance anxiety on the attrition of women and minorities from science, math, and engineering majors. While past
research has relied primarily on the academic deficits and lower socioeconomic status
of women and minorities to explain their absence from these fields, we focus on the
impact of stereotype threat—the anxiety caused by the expectation of being judged
based on a negative group stereotype. Using data from the National Longitudinal
Survey of Freshmen, our findings indicate that minorities experience stereotype threat
more strongly than whites, although women do not suffer from stereotype threat more
than men. Our findings also reveal that stereotype threat has a significant positive
effect on the likelihood of women, minorities, and surprisingly, white men leaving
science, technology, engineering and math majors.
Keywords Minorities · Women · Higher education · Science · Majors ·
Stem fields · Stereotype threat
1 Introduction
In January 2005, during a speech to the National Bureau of Economic Research,
Lawrence Summers, then President of Harvard University, observed that innate differences between men and women may be to blame for the lack of women in scientific
and mathematical careers. Specifically, Summers asserted that “In the special case of
science and engineering, there are issues of intrinsic aptitude, and particularly of the
M. A. Beasley (B) · M. J. Fischer
University of Connecticut, Storrs, CT, USA
e-mail: [email protected]
M. J. Fischer
e-mail: [email protected]
123
428
M. A. Beasley, M. J. Fischer
variability of aptitude, and that those considerations are reinforced by what are, in
fact, lesser factors involving socialization and continuing discrimination” (Summers,
2005). His assertion was not unlike those made in the controversial 1994 book The
Bell Curve, which purported that the lower test scores and grades of African-Americans and Hispanics were due to inferior cognitive function (Herrnstein and Murray
1994). While each of these events spurred a storm of debates and ill-will within the
academy, they also identified an increasing problem in the United States: a critical
underrepresentation of women and minorities in the sciences.
The dearth of science, technology, math and engineering (STEM)1 professionals
is in part, a consequence of the low rate of minority and female majors in these academic disciplines. As Elliott et al. (1996) observe, “You can’t play if you don’t stay,
and leaving science or premed for education or history usually means leaving science
or premed forever” (p. 706). It is virtually impossible to pursue a graduate degree or
career in STEM without first majoring in a STEM field. Although a significant number of underrepresented minorities and women may express interest in STEM fields
prior to or at the start of college, the number who ultimately major in these fields
is considerably smaller. Out of a sample of four Ivy League institutions, only 34 and
55 % of African-Americans and Hispanics who initially expressed a interest in science
persisted as science majors relative to 70 and 61 % of Asian and White students respectively (Elliott et al. 1996). National estimates follow a similar pattern. In 2004 the ratio
of the proportion of entering White freshman who intended to major in STEM relative
to White STEM graduates was 0.76 while the respective figures for African-Americans
and Hispanics2 were each only 0.57 (National Science Foundation 2007).
To explain the scarcity of minority and female STEM majors, previous research
has often focused on the academic deficits of minority students (Elliott et al. 1996;
Stangor and Sechrist 1998) and the inaptitude of women to perform in quantitative or
scientific disciplines (Holden 1998; Beckham et al. 1988). Educational statistics do
indicate that a considerable amount of the racial disparity in initial STEM interest can
be attributed to inequalities in primary and secondary education. African-American,
Latino and White students have notably different educational opportunities. Specifically, Whites fare better than Blacks and Latinos in teacher quality, curriculum, class
size, and school size, all of which are correlated with academic performance (DarlingHammond 2004). However, while academic preparation does account for part of the
loss of Black and Hispanic STEM majors, as research can attest considerable variation in the degree of preparation and socioeconomic background at each level of
performance remains (Aronson et al. 1998; Steele 1997; Steele and Aronson 1995).
Such findings are compounded by the erroneousness of claims that the deficit of African-Americans in STEM is based on differences in aptitude. As Stangor and Sechrist
(1998) point out, “Since many students choose their final majors after their first year
in school, it seems unlikely that aptitude is playing a large part in determining them.”
Moreover, the high rate of STEM graduates within historically Black colleges and
1 For the purposes of this article, STEM fields do not include social sciences or psychology—fields in
which both minorities and women are better represented.
2 Hispanics of Puerto Rican or Chicano descent.
123
Why they leave: the impact of stereotype threat
429
universities (HBCU’s) indicates that there is both an interest and the ability to compete within these fields among students of color. In 2004, for example, 19 % of HBCU
graduates were in STEM fields relative to 17 and 30 % of Whites and Asians at all
institutions (National Science Foundation 2007).3
Differences in academic performance by gender, although limited primarily to
STEM fields, have had similar explanations. Some, like Summers, have suggested
that it is a genetic difference in ability (Benbow and Stanley 1980; Robinson et al.
1996; Geary 1996; Benbow et al. 2000). For example, arguments that spatial abilities vary by gender (Hedges and Nowell 1995; Fennema and Sherman 1977) are
not uncommon. However, research has also provided evidence that the difference
lies not in the aptitude of boys and girls, but in the different ways in which boys and
girls believe intelligence and academic performance are related (Georgiou et al. 2007).
Others have proposed that the disparity in male-female performance is largely a matter
of socialization and subsequent interest levels, particularly in primary and secondary
school classrooms (Campbell and Beaudry 1998; Updegraff and Eccles 1996; Eccles
et al. 1990). Yet as is the case for minorities, the fact that some women (of all races) do,
at least initially, intend to major in STEM fields, suggests that differences in aptitude,
socialization, and interest alone cannot explain the movement of young women from
STEM disciplines to social sciences and humanities while in college.
2 Stereotype threat and undergraduate attrition from STEM fields
Given the limited research that directly addresses the high rates of minority and female
drop-outs from STEM disciplines at the college level, we must consider additional theories. In this study, we examine the role of stereotype threat in the attrition of women
and minorities from STEM majors. Defined as the social-psychological threat arising
from a situation or activity for which a negative stereotype about the actor’s group
applies (Steele 1997; Steele and Aronson 1995), stereotype threat has been used to
explain the underperformance of minorities and women in a variety of domains. Specifically, it is the anxiety individuals from stigmatized groups have that their behavior
might confirm—to others or even to themselves—the negative stereotypes imposed
upon their group (Spencer et al. 1999). Stereotype threat is a complex phenomenon that has multiple explanations (Steele et al. 2002b). On one hand, it undermines
achievement by interfering with performance on mental tasks by, among other things,
increasing blood pressure (Blascovich et al. 2001) and reducing working memory
capacity (Schmader and Johns 2003). Stereotype threat also drives students to defend
their self-esteem by disengaging from the domain in question (Aronson et al. 1998).
That is, expected or actual threats to identity in a given area prompt individuals to
make the domain less central to self-concept (Major et al. 1998).
In 1995, Steele and Aronson performed a series of clinical studies which have
been replicated with similar results myriad times on women and racial/ethnic minorities (Schmader et al. 2001, 2004; Major et al. 1998; Quinn and Spencer 2001).
3 While only 21 % of African-Americans received their college degrees from HBCUs, 30 % of African-
Americans who received a degree in STEM graduated from an HBCU. Black.
123
430
M. A. Beasley, M. J. Fischer
In the first study, (Steele and Aronson 1995), African-American and White students
were asked to take an identical exam and were broken into two groups. One group
was told the exam was based on cognitive ability whereas in the other, the exam
was presented without reference to aptitude. African-Americans performed worse
than their White counterparts when the test was described as a measure of ability,
but performed equally to Whites when the test was presented as reflective of something else. In the second study, groups were divided into a race-prime category—
in which students were required to list their race prior to taking the test—and a
non-prime group in which students were asked to list their race at the close of the
exam. African-Americans in the race-prime group fared worse than any other group,
while African-Americans in the non race-prime group performed equally to Whites
(Steele and Aronson 1995). The results of these types of experiments indicate that simple awareness of a stereotype is sufficient to reduce women and minority’s intellectual
performance.
The negative effects of stereotype threat are not limited, however, to explicit situational reminders. They may instead be implicitly activated in domains in which the
stereotypes are well known. For example, women who participated in an exam with
men performed worse than those who participated with only women (Inzlicht and
Ben-Zeev 2000). In essence, susceptibility to stereotype threat requires only that individuals are aware of negative stereotypes about their group and that they recognize the
potential that they will be judged by those stereotypes (Steele et al. 2002a,b; Wheeler
and Petty 2001). Most germane to the study at hand, this threat is particularly pertinent
to those who closely identify with a given domain, as its strongest influence is on the
vanguard of these groups. That is, stereotype threat has the greatest impact on those
individuals with the skills and self-confidence to have identified with a field in which
a negative stereotype about their group is particularly salient (Steele 1997).
In this article we examine whether the reputation of math, science, and engineering
as hostile environments for minorities and women and the subsequent expectation
of racism and sexism in these fields may provoke these students to ultimately withdraw from STEM majors. Although psychologists have conducted numerous studies
to identify the effects of stereotype threat in isolated instances such as taking the SAT
or other exams (See for example Steele 1997; Steele and Aronson 1995), the cumulative effects of this threat in a long-term, situation outside of a laboratory have not been
comprehensively examined. Steele et al. (2002a,b) suggests that aside from its effects
on performance, stereotype threat also decreases the degree of engagement individuals have with a given domain. In an attempt to defend their self-esteem, individuals
may temporarily “disengage” from a specific situation (e.g. an exam), detaching their
egos from their performance in that domain. In these cases, individuals remain identified with the domain, but selectively choose not to identify with a specific situation
(Major et al. 1998). Continuous disengagement resulting from repeated experiences
of racial antagonism may, however, influence persons to “disidentify” entirely with a
domain by continuously distancing themselves from their performance in that area.
That is, repeated instances which trigger disengagement may eventually cause people
to permanently opt out of that domain (Major et al. 1998; Nussbaum and Steele 2007).
Although psychological studies have repeatedly tested and demonstrated the effect
of short-term disengagement (Major et al. 1998; Crocker and Major 1989; Major and
123
Why they leave: the impact of stereotype threat
431
Schmader 1998; Nussbaum and Steele 2007), we know very little about long-term
disidentification. Hence, a key question is whether stereotype threat impacts disidentification and ultimately attrition from STEM fields. Fischer and Massey’s (2007) findings, that felt performance burden (based on externalized stereotypes) and decreasing
work effort (based on internalized stereotypes) over time are negatively related to
academic performance, is the starting point of the present research. Rather than examining the indirect relationships between internalized and externalized stereotypes to
performance, however, we explore their direct effects on leaving STEM majors. Given
the high rates of attrition of women and minorities from STEM disciplines and their
absence from STEM graduate programs, it is imperative to determine whether and
how stereotype threat plays a role.
Our primary hypothesis is that (H1) the experience of stereotype threat for
African-Americans, Hispanics, and women4 is positively related to their attrition from
science, math, and engineering majors. One aspect of stereotype threat which is especially salient to this study is that it can be activated implicitly in domains in which
stereotypes are prevalent. For example, Chavous et al. (2004) found that Black students
showed notably greater levels of stereotype expectations in traditionally male-dominated majors than they did in majors with greater female or minority presences.
Likewise, low levels of female or minority representation heightens expectations of
stereotypic evaluations in group work situations (Cohen and Swim 1995). Thus, the
effect of stereotype threat is likely to be heightened in learning situations in which
stereotypes are well-known and students (of any race or gender) are prone to make
mistakes. In the following sections we provide further theoretical arguments for the
relationships between stereotype threat and race and gender.
3 The role of stereotype threat in the attrition of minorities from STEM majors
African-Americans are perhaps the most marginalized racial group on college campuses and are especially susceptible to negative stereotypes. In a study of undergraduates at an Ivy League university, Torres and Charles (2004) found that White students consistently held racial stereotypes of African-Americans as unqualified for the
University, able to attend only because of affirmative action quotas or athletic ability. In
turn, over 75 % of African-American participants believed that most Whites assumed
they were the recipients of preferential treatment and incapable of being accepted on
their own academic merits. Given the high rate of Black attrition from STEM majors
and the commonly-held negative stereotypes against African-Americans in academia,
we believe (H2) stereotype threat will have a significant positive relationship to Black
attrition from STEM majors.
Hispanics are also stereotyped as being undeserving recipients of affirmative action
in college admissions and do have a low rate of STEM graduates. In 2004, for example, only 14 % of baccalaureates awarded to Hispanics were in STEM fields (National
Science Foundation 2007). While the low rate of Hispanic STEM graduates is wellknown, the majority of studies concerning their college experiences focus only on
troubles related to socioeconomic status and cultural differences (Sy and Brittian 2008;
4 White and non-White women.
123
432
M. A. Beasley, M. J. Fischer
Alberta et al. 2005). Although we take the differences between minority groups seriously, Hispanics’ marginalized status on college campuses may well mean they experience stereotype threat in STEM fields in much the same ways as African-Americans.
Indeed, Smedley et al. (1993) found that Hispanic students on predominantly White
college campuses experience significant psychological stresses and social tensions
with White peers and faculty. Hispanic students also expressed high rates of perceived
racial antagonism. Such racial tensions are directly related to Hispanic students’ adjustment to college (Hurtado et al. 1996). Moreover, Hispanic adolescents who experience
high levels of psychosocial stress, such as those caused by racial antagonism, are more
likely to have anxiety, receive lower grades, and perceive themselves as less competent academically (Alva and de Los Reyes 1999). Thus like African-Americans, (H3)
we expect Hispanics who experience stereotype threat to have a greater likelihood of
attrition from STEM majors.
Asian Americans present perhaps the most difficult minority group about which to
make predictions. On the one hand, they are a marginalized group. On the other hand,
however, Asians are considered a “model minority”. This stereotype first appeared in
the mid 1960s, in large part to discredit the demands of African-Americans for economic justice (Wong et al. 1998). A 1966 US News and World Report article entitled
“Success Story of One Minority Group in the U.S.” observed, “At a time when it is
being proposed that hundreds of billions be spent to uplift Negros and other minorities, the nation’s 300,000 Chinese Americans are moving ahead on their own—with
no help from anyone else” (U.S. News and World Report, 1966 p. 73). According to
the current model minority stereotype, Asian-Americans perform well in school and
work, are diligent and self-sufficient, and are effectively a model for other groups,
particularly other minorities, to follow (Zia 2001). Previous research on university
students found that not only did non-Asian students believe this stereotype, but the
preponderance of Asian-American students accepted it as well. In particular, Asian
and non-Asian students perceived Asian-Americans to be better prepared, more motivated, and have a greater likelihood of career success than Whites (Wong et al. 1998).
Given the positive stereotype about Asian-Americans’ aptitudes in STEM fields, (H4)
we expect that stereotype threat does not affect their attrition from such majors.
4 The role of stereotype threat in the attrition of women from STEM majors
The stereotype that girls and women are bad at math and science is also well-known
throughout the U.S. (Park et al. 2001) and has been implicated in the long-term career
interests of women (Eccles and Wigfield 2002). Although women who major in these
disciplines may not buy into the stereotype, they are quite familiar with it. Rinehart and Watson (1998), for example, found that women in engineering were more
likely than men to sense discriminatory behavior by their professors. Likewise, Steele
et al. (2002a,b) found that undergraduate women in male-dominated disciplines had
stronger perceptions of discrimination towards themselves and other women than did
women in other disciplines, yet they were no less identified with male-dominated fields
of study. Based on psychological studies, it is evident that these concerns impact the
performance of women in STEM disciplines. Prior clinical research on stereotype
123
Why they leave: the impact of stereotype threat
433
threat has firmly established that the activation of this stereotype increases anxiety
and causes women to perform worse on tests in these fields than they otherwise would
(Spencer et al. 1999; Steele 1997; Shih et al. 1999). Based on the impact of stereotype
threat in isolated situations and its proclivity to activate in settings in which group
members are underrepresented, (H5) we anticipate women who experience stereotype
threat to have a greater likelihood of attrition from STEM majors.
5 Race-gender interactions
Aside from the persistent trend among women and minorities respectively to avoid
college majors in science, math, and engineering, regardless of skill (Stangor and
Sechrist 1998; Schmader et al. 2004), female minorities are conspicuously scarce
among STEM graduates. Whether this is simply an additive effect of gender and race,
or whether race and gender have distinct interactions is unclear. The paradox between
the greater proportion of female college attendance among minorities and the absence
of women of all races with STEM degrees requires a more complex examination of the
role of stereotype threat in STEM attrition for men and women of color. In 2004 alone,
67 and 62 % of Black and Hispanic college graduates respectively were female yet
only 53 and 42 % of Black and Hispanic STEM grads were female (National Science
Foundation 2007). We must therefore question not only how stereotype threat affects
female and minority participation in STEM majors, but how the interaction between
race and gender creates different effects for women and men of color.
Black women, for example, outpace their male counterparts at all levels of degree
conferrals (Cohen and Nee 2000). However, Black men still represent nearly onehalf of African-Americans receiving degrees in STEM (National Science Foundation
2007).5 One possible explanation is that Black women face a double threat; that is,
being a member of multiple marginalized groups has an additive effect (Brown 2000).
Black women do indeed carry negative stereotypes on two fronts. Accordingly, we
might expect Black women to be more vulnerable to stereotype threat than Black
men. However the lower rate of Black male degree conferral indicates that Black men
may well suffer from stereotype threat as well. In 2004, the ratio of the proportion
of Black female freshman intending to major in STEM relative to the proportion of
Black women graduating with STEM degrees was 0.61. That same year, the figure
for Black men was 0.60 (National Science Foundation 2007). Cohen and Nee (2000)
stipulate that the absence of Black men at predominantly White colleges and universities may exacerbate their negative experiences on these campuses. Black men may
be particularly susceptible to stereotype threat due to their minimal campus presence
and overrepresentation in college athletics (Lederman 1992). Given the absence of
Black men on predominantly White campuses, and the additional liability of multiple
marginalized identities of Black women, (H6) we anticipate stereotype threat will
have a positive association with Black men and women’s attrition from STEM majors.
Whether stereotype threat has a stronger association with attrition among Black men
or Black women, however, is unclear.
5 According to 2004 figures.
123
434
M. A. Beasley, M. J. Fischer
The interaction of gender and race among Hispanics is also complex. Like African-Americans, a large majority of Hispanic graduates are women, but few of those
graduates receive science, math or engineering degrees. While Hispanic males represent only 38 % of Hispanic college graduates, they comprise 58 % of all Hispanic
STEM graduates (National Science Foundation 2007). Yet, although the proportion of Hispanic and African-American male graduates may be similar, there is
a markedly larger proportion of Hispanic males in STEM than Black men. As
58 % of the Hispanic population receiving science, math and engineering degrees,
they have a larger presence in those fields than their Black male counterparts and
therefore may not suffer to the same degree as Black men or Hispanic women
in STEM attrition. In contrast, the double burden of multiple marginalized identities faced by Latinas makes their susceptibility to stereotype threat greater within
STEM majors. Thus, (H7) we expect stereotype threat to have a stronger association
with attrition from STEM for Hispanic women than it does for their male counterparts.
Asian-American women, present yet another puzzle. While the model minority stereotype is not limited to Asian-American men, Asian-American women
do face negative stereotypes about gender within and outside of Asian-American
populations. Media portrayals of Asian and Asian-American women depict them
as delicate, shy and exotic (Espiritu 1997; Kang 1993), characteristics antithetical to scholarship or careers. Moreover, while the general stereotype of AsianAmericans is closely associated with STEM, the general stereotype of women is
not.
The question is which identity—Asian-American, female, or Asian female—
is most salient? Past research (Shih et al. 1999) established that performance is
dependent on which stereotype is triggered. For individuals with multiple identities relevant to a given task, the more/most salient identity exerts a stronger
influence. In a recent series of experiments on stereotype awareness (Sinclair
et al. 2006) Asian-American women believed they were evaluated less favorably
in math when their gender was salient, but more favorably when their ethnicity
was salient. Likewise, Shih et al. (1999) found that Asian-American women performed better on a quantitative test when their ethnicity was activated but worse
when their gender was activated relative to a control group without a prompt.
Yet in a similar set of studies, Cheryan and Bodenhausen (2000) found just the
opposite: that Asian-American women’s performance on a math test was significantly lower when ethnicity was primed but not significantly changed when gender was primed. Their research showed that the relationship between their identity as Asian and their performance was not direct, however, but mediated by a
decrease in the ability to concentrate. Thus, Asian American women did not lose
motivation due to the ethnic prime, but they did lose concentration which ultimately decreased their performance. Our research, however, focuses on long-term
motivation, not short-term performance. Hence (H8), we expect stereotype threat
to have no significant association with attrition from STEM for Asian men. However, (H9) because Asian women experience negative gender stereotypes, we predict
stereotype threat will have a negative association with attrition from STEM for Asian
women.
123
Why they leave: the impact of stereotype threat
435
6 Methods and measures
The data for this study comes from the National Longitudinal Survey of Freshmen
(NLSF), a probability sample of nearly 4000 students who matriculated into 28
selective colleges and universities as first time freshmen in the Fall of 1999.6 The
baseline sample included 998 Whites, 959 Asians, 916 Latinos, and 1,051 African
Americans. The survey was designed to gather extensive information about respondents prior to their entering college and to measure their initial attitudes, motivations, and perceptions. A detailed description of the sampling methodology, including the 28 institutions and their characteristics, is contained in Massey et al. (2006).
This initial interview was followed-up with subsequent surveys conducted by telephone in the spring of each academic year. In this paper, we focus on the intended
major of students from wave 1 as they entered college, their background characteristics gathered during this initial survey, their early college experiences recorded in
waves 2 and 3, and their subsequent retention or departure from STEM measured in
waves 2–4.
7 Examining the attrition of STEM and non-STEM majors
Our measure of initial intention to major in a STEM major comes from the wave
1 NLSF interview. Students who stated that they intended to major in engineering,
science, math, or computing majors were coded ‘1’ on this measure, while all other
responses were coded ‘0’. As such, the main dependent variable in our analyses is
whether these students who initially intended to major in STEM ended up staying in a
STEM major. Our measure of attrition from STEM is coded 1 if the student reported
a non-STEM major in the latest year they were observed in the sample, thereby preferencing the major named in the senior year if the student was still in the sample at
that point. If the student was unobserved in wave 5, we moved to wave 4 to construct
attrition from STEM. For those missing from waves 4 and 5, we looked instead to
wave 3.7 Table 1 shows the percent of students leaving STEM majors by race/ethnicity and gender. As can be seen, Asian men have the lowest attrition from STEM
at 14 %, followed by Hispanic men at 32 % and White men at 34 %. Black men and
women are the most likely to leave STEM majors at 47 and 41 % respectively. This
paper will examine what factors account for STEM attrition and whether these factors
differ by race/ethnicity and gender.
8 Stereotype threat and performance anxiety measures
Our primary measure of stereotype threat is what we call group based performance
anxiety, which is derived from a series of questions from the third wave about race
6 The NLSF has been used in a variety of notable psychological and sociological studies in recent years
including Massey et al. (2006); Charles et al. (2009); Ehrmann (2007); Rivas-Drake and Mooney (2008). As
of 2011, it was the most recent longitudinal, non-experimental dataset focused on college students available.
7 Students who eventually dropped out of school were not included in this sample.
123
436
M. A. Beasley, M. J. Fischer
and/or gender self-consciousness and the extent to which students feel that their individual performance reflects upon their group. Items include student’s agreement on
three statements: “if I excel academically it reflects positively on my group”, “if I do
poorly academically it reflects negatively on my group”, and “if I don’t do well people
will look down on others like me”. The alpha value for this scale is 0.73.
We also control for what we call general performance anxiety: the extent to which
students feel pressure or anxiety unrelated to their group identity to perform academically. Because stereotype threat is sometimes confused with a more general anxiety,
it is particularly important to include this as a separate variable. This measure is based
on two questions: the extent to which a student agrees that if his/her instructor knows
s/he is having difficulty with class they will think less of the student and the extent to
which the student believes fellow students will think less of him/her if they know s/he
is having difficulty with class. The alpha value for this scale is 0.76.
9 Methodology
Our analysis takes place in three stages. First, we examine the characteristics of
students who declare a STEM major as they are entering college compared to those
who are undeclared or who declared a non-STEM major using a logistic regression.
This model helps us to understand whether there are significant differences between
students who had a STEM major in mind at college entrance compared to those who
did not. Next we conduct an analysis of variance on the mean group anxiety experienced by respected race-gender groups to determine whether there are significant
differences based on these identities. The final stage of the analysis uses a series of
logistic regressions to examine the factors related to leaving STEM majors among
those who entered college as declared STEM majors. We are particularly interested
in whether group based performance anxiety played a role in attrition.
10 Results
We begin this section by examining the racial and gender composition of students that
entered with the intent to major in a STEM field. About one in five of students in the
Table 1 Percent of students that declare and leave STEM fields by race and gender
Declare STEM
Leave STEM
Male
N
Female
N
Male
N
Female
Black
22
353
19
638
47
98
41
Hispanic
23
384
14**
532
34
75
44
Asian
29
417
18***
542
14
86
34***
White
24
475
17**
523
32
64
39
Numbers do not coincide due to lack of response to certain questions
T-tests by gender
∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001
123
N
64
88
104
74
Why they leave: the impact of stereotype threat
437
NLSF sample arrived at college intending to major in science, engineering or math.
As shown in Table 1, this percentage varies somewhat by race/ethnicity and gender,
with Asian men being most likely to express an intention to major in STEM (29 %)
followed by White, Hispanic and Black men at 24, 23 and 22 %, respectively. In all
cases, except for African-Americans, women were far less likely to enter intending to
major in STEM than their male counterparts. Specifically, 18 % of Black and Asian
women intended to major in STEM while 17 % of White women and only 14 % of
Hispanic women did so.
Table 2 shows the results from a logistic regression predicting whether a student
declared a STEM major at college entrance versus being undeclared or declaring
another major. In all cases, Asian males are used as the comparison group given the
positive stereotype associated with their abilities in STEM fields Stereotypes of AsianAmerican academic ability are generally quite positive, particularly those pertaining
to STEM fields (Ho and Jackson 2001). This reflects the more general stereotype of
Asian Americans as hard workers with high intelligence associated with the “model
minority” myth (Sue et al. 1995). Asian-American men are especially well-suited as a
comparison because they have escaped the negative gender stereotypes still ascribed
to Asian-American women and are explicitly regarded as high performers in STEM
fields relative even to white men (Gupta et al. 2011; Lin et al. 2005).
As shown in Model 1, STEM declarers had significantly higher high school GPAs
than did those who had not declared STEM majors (B = 2.09). However, income,
the number of AP courses taken, family income, and whether at least one parent had
attended college had no significant effects on the likelihood of being STEM majors.
Turning to gender and race, Model 2 shows that females were significantly less likely
to declare a STEM major than men (B = 0.59). Hispanics and Whites were both
less likely than Asians to enter college with a declared STEM major, (B = 0.88) and
(B = 0.80) respectively, although not significantly. Blacks, on the other hand, were
more likely to enter with a STEM major than Asians (B = 1.06), but not significantly. Model 3 replaces race and gender variables with interaction terms.8 In this
case, White (B = 0.50), Asian (B = 0.51), Hispanic (B = 0.79) and Black (B = 0.87)
women were all significantly less likely to have declared STEM majors than their
male counterparts.9
Having found that those who declared STEM majors are in some ways different
than those who entered college undecided or as non-STEM majors we now ask whether
men and women from different racial groups who declared STEM majors experience
the same degree of group and general anxiety. Table 3 displays the means and standard
deviations.
While gender appears to play a minimal role in differences among mean group
performance anxiety, the results of a one-way analysis of variance indicate that race
has a significant effect (F = 44.39, p < .001). As shown in Table 3, Black men and
8 We were unable to run a third model in which interaction terms and basic variables were used due to
issues of multicollinearity.
9 Please note: when White men were used as the control group instead of Asian men the results (not shown)
were virtually identical. However, while the effect of being a White male was negative but insignificant,
being an Asian male was positive but insignificant.
123
123
1.07
1.03
2.09
1 ≥ Parent college grad
Number of AP courses
GPA
–
–
–
–
–
–
Hispanic male
Hispanic female
Asian female
White male
White female
∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001
Log likelihood
χ2
Constant
–
Black male
Black female
Race-gender interactions
–
–
–
White
Female
2.32
−0.14
(−0.53)
−4.16***
−197.61
38.95***
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
–
0.59
0.88
0.8
1.06
1.02
(−0.02)
–
1.07
0.84*
(−0.12)
(−0.08)
–
–
–
–
–
–
–
–
–
–
–
–
Hispanic
0.74***
0.03
0.07
−0.14
Black
Race
0.87
Family income
Background characteristics
Exp(β )
SE
Exp(β )
β
Model 2
Model 1
Table 2 Logistic regression of students’ intent to major in STEM fields
(−0.08)
−0.54***
86.68***
−4.14***
–
–
–
–
–
(−0.56)
–
–
–
–
–
–
–
(−0.11)
−0.13
–
–
(−0.12)
(−0.12)
0.06
(−0.15)
(−0.02)
(−0.12)
(−0.08)
SE
−0.22
0.84***
0.02
0.07
−0.17
−1893.75
β
0.50
0.8
0.51
0.41
0.79
0.63
0.87
–
–
–
–
2.29
1.02
1.07
0.84
Exp(β )
Model 3
(−0.16)
−0.70***
89.64***
−1892.27
(−0.56)
(−0.15)
−0.22
−4.02***
(−0.17)
(−0.16)
−0.89***
−0.23
−0.68***
(−0.15)
(−0.16)
−0.47**
(−0.18)
–
–
–
–
(−0.15)
(−0.02)
(−0.12)
(−0.08)
SE
−0.14
–
–
–
–
0.83***
0.02
0.06
−0.17*
β
438
M. A. Beasley, M. J. Fischer
Why they leave: the impact of stereotype threat
439
Table 3 ANOVA of mean group anxiety and general anxiety by race and gender
Group anxiety
General anxiety
Mean
SD
N
Mean
SD
N
Black male
17.12
7.19
77
4.86
4.41
77
Black female
17.76
6.47
111
3.87
4.42
111
Hispanic male
13.44
7.52
86
5.02
4.11
86
Hispanic female
13.99
7.18
72
4.04
4.05
73
Asian male
12.88
6.06
117
5.37
3.92
117
Asian female
12.88
5.70
91
5.15
4.01
91
White male
10.05
5.93
107
4.26
3.00
107
White female
9.73
5.84
83
4.51
3.31
83
SS Btw Races
5532.52
123.18
F
44.39***
2.67*
∗ p < .05, ∗∗ p < .01, ∗∗∗ p < .001
women by far score the highest on group based performance anxiety with means of
17.12 and 17.16. Hispanic women are and men have significantly lower group anxiety
levels of 13.99 and 13.44. Asians’ group based performance anxiety is slightly lower
on average; both men and women have a mean group anxiety of 12.88. Whites have
the lowest mean group anxiety levels such that White men and White women have
group anxiety averages of 10.05 and 9.73 respectively.
We also examined the mean general anxiety for each racial-gender group. Asian men
and women report the highest levels of general performance anxiety of 5.37 and 5.15
respectively, but are followed closely by Hispanic men who average 5.02. Black men
and White women report average scores of 4.86 and 4.51 which are close to White men
and Hispanic women whose mean general anxiety levels are 4.26 and 4.04 respectively.
Black women have the lowest average general performance anxiety averaging 3.87.
While it is evident that men and women of different racial groups experience significantly different levels of group based anxiety (stereotype threat), the impact of that
anxiety is a separate issue. We turn to our primary research question: how does group
based performance anxiety influence the attrition of different racial and gender groups
from STEM majors.
Table 4 shows a series of logistic regressions predicting the odds of leaving a STEM
major for those students who entered college as STEM majors. Model 1 shows that students with higher high school GPA’s are significantly less like to leave a STEM majors,
although the number of AP courses taken, whether at least one parent had attended
college, and family income all had insignificant effects. This finding provides mixed
support for the work by Massey et al. (2006) which found that the academic disadvantages of minority students help explain racial differences in college academic
performance. However, this model does not lend support to our general expectation
that stereotype threat has a positive impact on STEM attrition.
Model 2 adds controls for race and gender, all of which are positively associated with
the odds of leaving a STEM major. Because Asians had the lowest rate of attrition from
STEM majors—23 %—and have a positive stereotype related to their performance in
123
440
M. A. Beasley, M. J. Fischer
Table 4 Logistic regression analysis of attrition from STEM majors
Model 1
Background characteristics
Family income
Model 2
Model 3
β
SE
β
SE
−0.12
(−0.17)
−0.10
(−0.18)
β
SE
−0.13
−0.20
(−0.18)
1 ≥ Parent college grad
−0.16
(−0.24)
−0.22
(−0.25)
Number of AP courses
−0.08
(−0.05)
−0.04
(−0.05)
−0.04
(−0.05)
(−0.25)
GPA
−0.79**
(−0.29)
−0.85**
(−0.3)
−0.78*
(−0.31)
Anxiety
General
−0.01
(−0.02)
0.00
(−0.02)
−0.01
(−0.02)
Group
0.01
(−0.01)
0.01
(−0.01)
−0.07*
(−0.03)
Black
–
–
0.64*
(−0.26)
−0.44
(−0.74)
Hispanic
–
–
0.65*
(−0.26)
−0.06
(−0.75)
White
–
–
0.64**
(−0.25)
−0.57
(−0.76)
Female
–
–
0.45*
(−0.17)
0.30
(−0.55)
Race
General anxiety
Black male
–
–
–
–
0.04
(−0.05)
Black female
–
–
–
–
−0.04
(−0.04)
Hispanic male
–
–
–
–
0.03
(−0.06)
Hispanic female
–
–
–
–
−0.05
(−0.06)
Asian female
–
–
–
–
−0.03
(−0.06)
White male
–
–
–
–
−0.05
(−0.07)
White female
–
–
–
–
−0.04
(−0.06)
Black male
–
–
–
–
0.08*
(−0.03)
Black female
–
–
–
–
0.09**
(−0.03)
Group anxiety
Hispanic male
–
–
–
–
0.04
(−0.04)
Hispanic female
–
–
–
–
0.09*
(−0.04)
Asian female
–
–
–
–
0.06
(−0.04)
White male
–
–
–
–
0.11**
(−0.04)
White female
Constant
–
–
–
–
0.12**
(−0.04)
2.53*
(−1.11)
1.95
(−1.16)
2.50*
(−1.23)
χ2
17.42**
34.81**
Log likelihood
−402.49
−393.80
55.27***
−383.57
N = 637
∗ p < .05,∗∗ p < .01,∗∗∗ p < .001
STEM fields, we again used this as our reference group. Accordingly, Black, Hispanic
and female identities all increase the likelihood of STEM attrition relative to Asian
or male identities. Surprisingly, however, Whiteness also increases the likelihood of
STEM attrition. While we anticipated that White women had a greater likelihood of
STEM attrition, our assumption was based on the anticipated negative effects of their
123
Why they leave: the impact of stereotype threat
441
gender, not their race. The results in Model 2, however, indicate that being White as
compared to being Asian, regardless of gender, has a positive influence on attrition.
Thus being Black, Hispanic, White and female, all increase the likelihood of attrition
from STEM majors.
In Model 3, we add interactions between each racial and gender category with
group anxiety and general anxiety. Due to issues of multicollinearity among categorical variables, however, we were unable to provide a model which examines the basic
and interaction terms for race and gender together in addition to race-gender-anxiety
interactions. Following the recommendations of Hair et al. (1995) we did not include
the variable primarily responsible. In this case, it meant the exclusion of race-gender
interactions. Although we recognize that centering one of the independent variables
is a popular alternative, in these models, the categorical, not continuous variables are
collinear which precludes centering as an option.
This model provides strong support to our hypotheses that minority and/or female
status coupled with group anxiety increases the likelihood of STEM attrition. The
results indicate that the experience of stereotype threat among Black and White men
and women, as well as Hispanic women significantly increase the likelihood of STEM
attrition relative to Asian Men. Although we had not anticipated stereotype threat
to have an impact on attrition from STEM among Whites men, the experience of
stereotype threat among Black and White men and women have a similar effect on
the log odds. Specifically, a 1 standard deviation increase in Black male and Black
female group based performance anxiety (b = 0.08, std = 7.43) (b = 0.09, std = 8.86)
respectively produces, on average, a 0.59 (b = 0.08*7.43) and (0.09*8.86) increase in
the log odds of both Black men and Black women leaving STEM. Similarly a standard
deviation increase in group anxiety among White men (b = 0.11, std = 5.87) increases
the log odds of attrition by 0.65 and by 0.61 and 0.57 for White and Hispanic women
respectively. In contrast, general anxiety interactions had no significant impact on the
log odds of attrition for any group.
Contrary to our expectations, however, White men experiencing group based anxiety were also more likely to leave STEM majors, while Hispanic men were not.
Coupled with findings from Table 2 it is clear that while White men experience less
group-based performance anxiety than all other groups except White women, their
experience of stereotype threat is positively associated with attrition.10
11 Discussion
This study examined the effects of stereotype threat on the attrition of minorities and
women from science, technology, math and engineering majors. As Table 1 shows,
for some women and minorities the primary issue is not a lack of interest in STEM.
White, Asian and Hispanic women do indeed declare STEM majors at significantly
lower rates than their male counterparts. However, the percent of Black and Hispanic
10 Please note: when White men were used as the control group instead of Asian men the results (not
shown) were almost identical. The only major difference was that Asian male group anxiety was significantly negatively associated with attrition from STEM fields while White male group anxiety was
significantly positively associated with attrition.
123
442
M. A. Beasley, M. J. Fischer
men who declare STEM majors upon college entrance is actually close in size to that
of White men, while Asian men declare STEM majors at a significantly higher rate
than all other groups. Likewise, Black women declare stem majors at rates not significantly different than those of Black men. Instead, the rate of attrition from STEM
majors within the first two years of college appears to be significantly higher among
African-Americans, Hispanic women, and White women than it is among White men
and Asian men. This helps to account for the significant disparity in the proportions
of Black, Hispanic female, and White female college graduates with STEM degrees
relative to White and Asian men.
Prior studies on attrition from STEM claim that a lack of preparation and low socioeconomic status are the primary culprits in the dearth of minority and female scientists
and engineers. Descriptive statistics (not shown) reveal that African-Americans and
Hispanics who enter college intending to major in STEM do so with less preparation (as measured by the number of AP courses taken and slightly lower GPAs) and
lower socioeconomic backgrounds than do their Asian and White peers. Similarly,
women who initially declare STEM majors enter with slightly less preparation than
do their male counterparts. Yet the findings presented in Table 2 demonstrate that only
some aspects of preparation play a key role in determining whether students choose
to major in STEM even when race and gender are taken into consideration. However,
accounting for who stays in STEM from each race or gender is a separate issue which
requires the addition of factors besides preparation and socioeconomic status. Our
study focused on whether stereotype threat is one such factor.
Although psychologists have examined the impact of stereotype threat on women
and minorities in short-term testing situations many times, few have explored how
stereotype threat can impact these groups in long-term settings or decision-making.
The present study adds to a small but growing body of research concerning the ways
in which stereotype threat impacts decision-making in long-term circumstances. Carr
and Steele (2010) for example, found that stereotype threat increased women’s aversion to risking taking in financial decisions. Similarly Alter et al. (2010) found that
stereotype threat impairs performance by stimulating avoidance behaviors such as
non-participation. Our results show that the experience of stereotype threat also elicits
decisions by college students to stay or leave STEM fields.
Massey and Fischer (2005), whose research we build on, demonstrated that
performance anxiety does hamper the academic performance of racial minorities. We
extend these findings to determine whether group based performance anxiety (stereotype threat) plays a role in the low proportion of Black, Hispanic, and female scientists
and engineers and their high rates of attrition from these majors. Because Massey and
Fischer’s (2005) research was based on what they referred to as “felt performance
burden” a composite of both our group and general anxiety measures, however, we
first investigated the relationship between race, gender, and group based performance
anxiety. Consistent with prior psychological studies, we found in Table 3 that Whites
and Asians experienced less stereotype threat than their Black and Hispanic counterparts. Contrary to prior findings, however, gender had no significant effect on the
experience of group anxiety. However, as we noted in our findings, while the experience of stereotype threat may be stronger or weaker depending on race and/or gender,
the effects of it are a separate issue.
123
Why they leave: the impact of stereotype threat
443
The results in Table 4 primarily confirm our hypotheses concerning the impact of
stereotype threat among racial and/or gender groups on attrition from STEM majors.
In particular, the experiences of stereotype threat among Black men and women as well
as White and Hispanic women have a significant influence on STEM attrition. This
finding provides strong evidence that stereotype threat takes place not only in testing
situations, but in ongoing activities. Thus stereotype threat not only negatively affects
the test taking abilities of women and minorities, but it inhibits major life experiences
as well.
Also of major interest was our unanticipated finding that the experience of stereotype threat among Whites, particularly White males, has a positive effect on their
likelihood of leaving STEM. That is, like women and minorities, White men experiencing stereotype threat were more likely to drop out of STEM majors. As expected,
Whites, especially White men, experienced a low level of stereotype threat. Yet our
results indicate that those who do experience some degree of group based performance
anxiety suffered in the same ways as their minority and female counterparts. Given the
lack of negative stereotypes regarding academia or STEM fields about White males,
this is a difficult finding to interpret. We conjecture that the awareness of their dwindling numbers in college and STEM, coupled with the visible and perceived dominance
of Asian men in these fields, may cause insecurity among White males equivalent to
a latent stereotype. Asians are indeed overrepresented in STEM fields. According to
recent IPEDS data, STEM majors overall comprised 15 % of graduates in 2005–2006
but over a quarter of Asians (26 %) graduated in that year from these fields of study
(compared to 14 % of Whites).11
An important question to consider in applying the findings of these studies is: would
our results be the same if we examined patterns among students at less selective schools
than the 28 which were sampled in the NLSF? Psychologists at universities with wide
ranges of selectivity have conducted lab experiments with similar and sometimes identical findings to one another. This suggests that stereotype threat may function in the
same ways regardless of the level of selectivity of an institution. Owens and Massey
(2011) have pointed to the virtue of using longitudinal surveys to study more longlasting situations in which stereotype threat might occur. Analyses using survey data
are not meant to replace the exceptional experimental work conducted, but rather to
complement it and provide longitudinal data unavailable for most experiments. We
caution readers, however, that despite drawing on experimental research from a diversity of institutions to predict and interpret our findings, our sample was drawn from
28 selective and highly selective tertiary institutions. As such, we believe our findings
can only be generalized to similarly selective schools.
11 Statistics based on number of bachelors degrees awarded by major by race/ethnicity and gender for
2005–2006 as reported in Table 275 in the Condition of Education 2007 (http://nces.ed.gov/programs/
digest/d07/tables/dt07_275.asp). Note: while 43, 38 and 39 % of Blacks, Hispanics, and women respectively who initially declared STEM majors left, only 34, 23 and 29 % respectively of Whites, Asians, and
Hispanics did so.
123
444
M. A. Beasley, M. J. Fischer
12 Conclusions
The lack of minorities and women in STEM professions and their related scarcity in
STEM college majors has been the source of much concern. This paper has found that
the lack of graduating majors in these fields is not due solely to a lack of initial interest in STEM majors, but rather occurs through attrition from these majors during the
course of college. We explored two explanations for this attrition—lack of academic
preparation and stereotype threat. We find that those who had stronger grades in high
school were in fact more likely to be early declarers of STEM majors, suggesting that
those who came into college wanting to major in these fields were positively selected
in terms of academic preparation. We also show little evidence of an initial race gap in
expressing a desire to major in STEM fields at college entrance. The puzzle remains
then, what happens after students enter college that steers them away from the STEM
majors they initially intended to pursue.
The primary explanation we explored in this paper was stereotype threat. Our main
measure of stereotype threat, which we termed group based performance anxiety, taps
the extent to which students attribute their own performance as reflective of the academic competence of their race and/or gender group. Black STEM majors had the
highest group based performance anxiety, followed by Hispanics and Asians. Whites
had the lowest scores on this measure.
Net of other controls, we find that those who express higher levels of group
based performance anxiety have significantly higher odds of leaving STEM majors.
Regardless of scores on group based performance anxiety, male and female students from all racial/ethnic groups (with the exception of Hispanic men and Asian
women) have higher odds of leaving STEM compared to Asian men. Women’s odds
of leaving STEM are higher than males net of other factors. Cumulatively, this
means that non-Asian and female students with higher levels of group based performance anxiety are predicted to be at the greatest risk of attrition from STEM
majors. These findings suggest that stereotype threat is instrumental in undermining the ambitions of minority and female students from majoring in STEM
fields.
While most of the other research on stereotype threat has focused specifically on
academic performance, our study is unique in that we examine the role of stereotype
threat on students’ propensity to remain in what are often considered to be more challenging majors. Although we are looking at a concrete action rather than performance
per se, our results are consistent with the findings from performance-based studies. These performance-based studies have found that minorities and women tend to
underperform in tests when the test taking conditions invoke a negative group stereotype about which test takers may be anxious about confirming. Similarly, we find that
Hispanics, Blacks, and women from all groups disproportionately leave STEM majors
for which their underrepresentation has at times been attributed to lack of competence
in these fields.
There are several challenges that lie ahead for colleges and universities wishing to
retain greater numbers of women and minorities in STEM majors. The initial interest
of these groups in STEM majors is encouraging. More needs to be done, however, to
understand the process by which students choose to leave these majors. Our findings
123
Why they leave: the impact of stereotype threat
445
suggest that stereotype threat plays a role in their attrition. Fortunately other research
has found that there are ways to reduce the negative effect of stereotype threat on outcomes for vulnerable groups, some of which may be applicable to the case of leaving
STEM majors.
One method to reduce stereotype threat is having more role models from vulnerable
groups. While minorities and women are underrepresented among STEM majors, they
are virtually absent among the faculty in these fields. Contrary to claims that the race
and gender of faculty have minimal influence on students’ interests (Cole and Barber
2003), stronger efforts to recruit and retain minority and female scholars in sciences
and engineering would most certainly help with retraining vulnerable students in these
majors. Even if teachers are not of the same race/ethnicity or gender as the student,
there are mentoring techniques that can reduce the effects of stereotype threat. Cohen
et al. (1999) find that students who received constructive criticism to communicate
high standards while at the same time receiving assurances that they could meet these
standards resulted in students feeling less that they would be judged based on stereotypes. Although it is evident that educators have yet to directly examine how to
diminish stereotype threat, recognition of the role that stereotype threat plays in the
dearth of minorities and women in science, math and engineering fields is a crucial
first step in rectifying the problem.
References
Alberta, G. M., Castellanos, J., Lopez, A. G. L., & Rosales, R. (2005). An examination of academic nonpersistence decisions of Latino undergraduates. Hispanic Journal of Behavioral Sciences, 27(2), 202–223.
Alter, A. L., Aronson, J., Darley, J. M., Rodriguez, C., & Ruble, D. N. (2010). Rising to the threat:
Reducing stereotype threat by reframing the threat as a challenge. Journal of Experimental Social
Psychology, 46(1), 166–171.
Alva, S. A., & de Los Reyes, R. (1999). Psychosocial stress, internalized symptoms, and the academic
achievement of Hispanic adolescents. Journal of Adolescent Research, 14(3), 343–358.
Aronson, J., Quinn, D. M., & Spencer, S. J. (1998). Stereotype threat and the academic underperformance
of minorities and women. In J. K. Swim, C. Stangor, & J. K. Swim (Eds.), Prejudice: The target’s
perspective (pp. 83–103). San Diego, CA, USA: Academic Press.
Beckham, J. C., Carbonell, J. L., & Gustafson, D. J. (1988). Are there sex differences in problem
solving? An investigation of problem context and sex role type. Journal of Psychology, 122(1), 21.
Benbow, C. P., Lubinski, D., Shea, D. L., & Eftekhari-Sanjani, H. (2000). Sex differences in mathematical
reasoning ability at age 13: Their status 20 years later. Psychological Science, 11, 474–480.
Benbow, C. P., & Stanley, J. C. (1980). Sex differences in mathematical ability. Fact or artifact?.
Science, 210, 1262–1264.
Blascovich, J., Spencer, S. J., Quinn, D. M., & Steele, C. M. (2001). African Americans and high
blood pressure: The role of stereotype threat. Psychological Science, 12(3; 3), 225–229.
Brown, T. L. (2000). Gender differences in African American students’ satisfaction with college. Journal
of College Student Development, 41(5), 479–487.
Campbell, J. R., & Beaudry, J. S. (1998). Gender gap linked to differential socialization for high-achieving
senior mathematics students. The Journal of Educational Research, 91(140), 140–147.
Carr, P. B., & Steele, C. M. (2010). Stereotype threat affects financial decision making. Psychological
Science, 21(10), 1411–1416.
Charles, C. Z., Fischer, M. J., Mooney, M. A., & Massey, D. S. (2009). Taming the river: Negotiating
the academic, financial, and social currents in selective colleges and universities. Princeton,
NJ: Princeton University Press.
123
446
M. A. Beasley, M. J. Fischer
Chavous, T. M., Harris, A., Rivas, D., Helaire, L., & Green, L. (2004). Racial stereotypes and gender in
context: African Americans at predominantly black and predominantly white colleges. Sex Roles,
51(1–2), 1–16. Retrieved from CSA Sociological Abstracts database.
Cheryan, S., & Bodenhausen, G. V. (2000). When positive stereotypes threaten intellectual performance:
The psychological hazards of “model minority” status. Psychological Science, 11(5), 399–402.
Cohen, C. J., & Nee, C. E. (2000). Educational attainment and sex differentials in African American
communities. American Behavioral Scientist, 43(7), 1159–1206.
Cohen, G. L., Steele, C. M., & Ross, L. D. (1999). The mentor’s dilemma: Providing critical feedback
across the racial divide. Personality and Social Psychology Bulletin, 25(10), 1302–1318.
Cohen, L. L., & Swim, J. K. (1995). The differential impact of gender ratios on women and men: Tokenism,
self-confidence, and expectations. Personality and Social Psychology Bulletin, 21(9), 876–884.
Cole, S., & Barber, E. G. (2003). Increasing faculty diversity: The occupational choices of high-achieving
minority students. Cambridge, Mass.: Harvard University Press.
Crocker, J., & Major, B. (1989). Social stigma and self esteem: The self-protective properties of
stigma. Psychological Review, 96(4), 608–630.
Darling-Hammond, L. (2004). The color line in American education: Race, resources, and student
achievement. Du Bois Review: Social Science Research on Race, 1(2), 213–246.
Eccles, J. S., Jacobs, J. E., & Harold, R. D. (1990). Gender role stereotypes, expectancy effects, and
parents’ socialization of gender differences. Journal of Social Issues, 46, 183–201.
Eccles, J. S., & Wigfield, A. (2002). Motivational beliefs, values, and goals. Annual Review of
Psychology, 53, 109–132.
Ehrmann, N. (2007). From the ghetto to the ivory tower: Gendered effects of segregation on elite-college
completion. Social Science Quarterly, 88(5), 1392–1414.
Elliott, R., Strenta, C., Adair, R., Matier, M., & Scott, J. (1996). The role of ethnicity in choosing and
leaving science in highly selective institutions. Research in Higher Education, 37(6), 681–709.
Espiritu, Y. L. (1997). Asian American women and men: Labor, laws and love. Thousand Oaks, CA: Sage
Publications.
Fennema, E., & Sherman, J. (1977). Sex-related differences in mathematics achievement, spatial
visualization, and affective factors. American Education Journal, 14, 51–71.
Fischer, M. J., & Massey, D. S. (2007). The effects of affirmative action in higher education. Social
Science Research, 36(2), 531–549.
Geary, D. C. (1996). Sexual selection and sex differences in mathematical abilities. Behavioral and
Brain Sciences, 19, 229–284.
Georgiou, S. N., Stavrinides, P., & Kalavana, T. (2007). Is victor better than victoria at maths?. Educational
Psychology in Practice, 23(4), 329–342.
Gupta, A., Szymanski, D. M., & Leong, F. T. L. (2011). The “model minority myth”: Internalized
racialism of positive stereotypes as correlates of psychological distress, and attitudes toward
help-seeking. Asian American Journal of Psychology, 2(2), 101–114.
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (1995). Multivariate data analysis
(4th ed.). New Jersey: Prentice Hall.
Hedges, L. V., & Nowell, A. (1995). Sex differences in mental test scores, variability, and numbers of
high-scoring individuals. Science, 269, 41–45.
Herrnstein, R. J., & Murray, C. A. (1994). The bell curve: Intelligence and class structure in American
life. New York: Free Press.
Ho, C. C., & Jackson, J. W. (2001). Attitudes toward Asian Americans: Theory and measurement.
Journal of Applied Social Psychology, 31, 1553–1581.
Holden, C. (1998). Boys + girls + math. Science, 279(5356), 1459.
Hurtado, S., Carter, D. F., & Spuler, A. (1996). Latino student transition to college: Assessing difficulties
and factors in successful college adjustment. Research in Higher Education, 37(2), 135–157.
Inzlicht, M., & Ben-Zeev, T. (2000). A threatening intellectual environment: Why females are susceptible to experiencing problem-solving deficits in the presence of males. Psychological Science, 11,
365–371.
Kang, L. H. (1993). The desiring of Asian female bodies: Interracial romance and cinematic subjection. Visual Anthropology Review, 9(1), 5–21.
Lederman, D. (June 17, 1992). Blacks make up large proportion of scholarship atheletes, yet their overall
enrollment lags at division I colleges. Chronicle of Higher Education, 38, A1–A1, A30–A34.
123
Why they leave: the impact of stereotype threat
447
Lin, M. H., Kwan, V. S. Y., Cheung, A., & Fiske, S. T. (2005). Stereotype content model explains
prejudice for an envied outgroup: Scale of anti-Asian American stereotypes. Personality and Social
Psychology Bulletin, 31(1), 34–47.
Major, B., & Schmader, T. (1998). Coping with stigma through psychological disengagement. In J. K.
Swim, & C. Stangor (Eds.), Prejudice: The Target’s perspective (pp. 219–241)
Major, B., Spencer, S. J., Schmader, T., Wolfe, C., & Crocker, J. (1998). Coping with negative stereotypes
about intellectual performance: The role of psychological disengagement. Personality and Social
Psychology Bulletin, 24(1), 34–50.
Massey, D. S., & Fischer, M. J. (2005). Stereotype threat and academic performance: New findings
from a racially diverse sample of college freshmen. Du bois review: Social science research on
race, 2(1), 45–67. doi:10.1017/S1742058X05050058.
Massey, D. S., Charles, C. Z., Lundy, G. F., & Fischer, M. J. (2006). The source of the river: The
social origins of freshmen at America’s selective colleges and universities. Princeton, NJ: Princeton
University Press.
National Science Foundation, Division of Science Resources Statistics. (2007). S&E degrees, by Race/
Ethnicity of recipients: 1995–2004 No NSF 07-308. Arlington, VA: National Science Foundation.
Nussbaum, D. A., & Steele, C. M. (2007). Situational disengagement and persistence in the face of
adversity. Journal of Experimental Social Psychology, 43, 127–134.
Owens, J., & Massey, D. S. (2011). Stereotype threat and college academic performance: A latent
variables approach. Social Science Research, 40(1), 150–166.
Park, L. E., Cook, K. E., & Greenwald, A. G. (2001). Implicit indicators of women’s persistence in
math, science, and engineering Psi Chi Journal of Undergraduate Research, 6, 145-145-152.
Quinn, D. M., & Spencer, S. J. (2001). The interference of stereotype threat with women’s generation
of mathematical problem-solving strategies. Journal of Social Issues, 57(1), 55–71.
Rinehart, J., & Watson, K. (1998). A campus climate survey at texas A&M university. Proceedings
of the 1998 women in engineering conference: Creating a global engineering community through
partnerships, (93-100), West Lafayette, IN.
Rivas-Drake, D., & Mooney, M. (2008). Profiles of Latino adaptation at elite colleges and universities. American Journal of Community Psychology, 42(1–2), 1–16.
Robinson, N. M., Abbott, R. D., Berninger, V. W., & Busse, J. (1996). The structure of abilities
in mathematically precocious young children: Gender similarities and differences. Journal of
Educational Psychology, 88(341), 341–352.
Schmader, T., & Johns, M. (2003). Converging evidence that stereotype threat reduces working memory
capacity. Journal of Personality and Social Psychology, 85(3), 440–452.
Schmader, T., Johns, M., & Barquissau, M. (2004). The costs of accepting gender differences: The
role of stereotype endorsement in women’s experience in the math domain. Sex Roles, 50(11–12),
835–850.
Schmader, T., Major, B., & Gramzow, R. H. (2001). Coping with ethnic stereotypes in the academic domain:
Perceived injustice and psychological disengagement. The Journal of Social Issues, 57(1), 93–111.
Shih, M., Pittinsky, T. L., & Ambady, N. (1999). Stereotype susceptibility: Identity salience and shifts
in quantitative performance. Psychological Science, 10, 80–83.
Sinclair, S., Hardin, C. D., & Lowery, B. S. (2006). Self-stereotyping in the context of multiple social
identities. Journal of Personality and Social Psychology, 90(4), 529–542.
Smedley, B. D., Myers, H. F., & Harrell, S. P. (1993). Minority-status stresses and the college adjustment
of ethnic minority freshmen. The Journal of Higher Education, 64(4), 434–452.
Spencer, S. J., Steele, C. M., & Quinn, D. M. (1999). Stereotype threat and women’s math performance.
Journal of Experimental Social Psychology, 35, 4–28.
Stangor, C., & Sechrist, G. (1998). Conceptualizing the determinants of academic choice and task
performance across social groups. In J. K. Swim, & C. Stangor (Eds.), Prejudice: The target’s
perspective (pp. 105–124). San Diego, CA: Academic Press.
Steele, C. M. (1997). A threat in the air: How stereotypes shape intellectual identity and performance. American Psychologist, 52(6), 613–629.
Steele, C. M., & Aronson, J. (1995). Stereotype threat and the intellectual test performance of African
Americans. Journal of Personality and Social Psychology, 69(5), 797–811.
Steele, J., James, J. B., & Barnett, R. C. (2002a). Learning in a Man’s world: Examining the perceptions
of undergraduate women in male-dominated academic areas. Psychology of Women Quarterly,
26(1), 46–50.
123
448
M. A. Beasley, M. J. Fischer
Steele, C. M., Spencer, S. J., & Aronson, J. (2002b). Contending with group image: The psychology
of stereotype and social identity threat. In M. P. Zanna & M. P. Zanna (Eds.), Advances in
experimental social psychology, vol. 34 (pp. 379–440). San Diego, CA, USA: Academic Press.
Sue, S., Sue, D. W, Sue, L., & Takeuchi, D. T. (1995). Psychopathology among Asian Americans:
A model minority? Cultural Diversity and Mental Health, 1, 39–51.
Sy, S. R., & Brittian, A. (2008). The impact of family obligations on young women’s decisions during
the transition to college: A comparison of Latina, European American, and Asian American
students. Sex Roles: A Journal of Research, 58(9–10), 729–737.
The success story of one minority group in the U.S., (December 26, 1966). U.S. News & World Report,
73–76.
Torres, K. C., & Charles, C. Z. (2004). Metastereotypes and the black-white divide: A qualitative view of
race on an elite college campus. Du Bois Review: Social Science Research on Race, 1(1), 115–149.
Updegraff, K. A., & Eccles, J. S. (1996). Course enrollment as self-regulatory behavior: Who takes
optional high school math courses?. Learning and Individual Differences, 8(3), 239–259.
Wheeler, S. C., & Petty, R. E. (2001). The effects of stereotype activation on behavior: A review of
possible mechanisms. Psychological Bulletin, 127(6), 797–826.
Wong, P., Lai, C. F., Nagasawa, R., & Lin, T. (1998). Asian Americans as a model minority:
Self-perceptions and perceptions by other racial groups. Sociological Perspectives, 41(1), 95–118.
Zia, Helen Asian American Dreams: The Emergence of an American People. (2001). Asian American
dreams: The emergence of an American people (1st ed.) Farrar, Straus and Giroux.
Author Biographies
Maya A. Beasley, Ph.D. is an Associate Professor in the Department of Sociology at the University of
Connecticut and serves on the Board of Advisors for the African American Studies Institute. Her first book,
Opting Out: Losing the Potential of America’s Young Black Elite was published in 2011. She is currently
working on a second manuscript examining the impacts of the types of professions in which female and
minority college graduates are most prevalent and least represented.
Mary J. Fischer, Ph.D. is an Associate Professor in the Department of Sociology at the University of
Connecticut. She has published widely on education and immigration. Among her numerous publications,
Professor Fischer is a co-author of The Source of the River: The Social Origins of Freshmen at America’s
Selective Colleges and Universities and Taming the River: Negotiating the Academic, Financial, and Social
Currents in Selective Colleges and Universities.
123