Emerging Trends in The Social and Behavioral Sciences

Why So Few Women in Mathematically Intensive Fields?

Item

Title

Why So Few Women in Mathematically Intensive Fields?

Author

Ceci, Stephen J.

Williams, Wendy M.

Research Area

Class, Status and Power

Topic

Gender and Gender Inequality

Abstract

Women have made huge gains in all fields of science over the past four decades, greatly increasing their presence in PhD programs and in postdoctoral positions. But, their progress has been greater in some fields than others. Although women constitute a critical mass of faculty in fields such as biology, medicine, psychology, veterinary science, and sociology, they continue to be underrepresented in mathematically intensive fields such as engineering, physics, chemistry, economics, computer science, and mathematics. In this essay, we describe both data and argument pertinent to women's underrepresentation, organized around three alleged causes. After reviewing these three causes, we conclude that neither sex differences in mathematical and spatial ability, nor the often‐alleged bias against women in science, can explain their dearth, whereas choices and family formation plans go a long way toward doing so.

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Identifier

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extracted text

Why So Few Women in
Mathematically Intensive Fields?
STEPHEN J. CECI and WENDY M. WILLIAMS

Abstract
Women have made huge gains in all fields of science over the past four decades,
greatly increasing their presence in PhD programs and in postdoctoral positions.
But, their progress has been greater in some fields than others. Although women
constitute a critical mass of faculty in fields such as biology, medicine, psychology,
veterinary science, and sociology, they continue to be underrepresented in mathematically intensive fields such as engineering, physics, chemistry, economics, computer science, and mathematics. In this essay, we describe both data and argument
pertinent to women’s underrepresentation, organized around three alleged causes.
After reviewing these three causes, we conclude that neither sex differences in mathematical and spatial ability, nor the often-alleged bias against women in science, can
explain their dearth, whereas choices and family formation plans go a long way
toward doing so.

WHY SO FEW WOMEN IN MATHEMATICALLY INTENSIVE FIELDS?
That women are underrepresented in math-intensive fields is not
controversial—all who are familiar with the data have been aware of
the dearth of women in mathematics-based fields for many decades:
There is agreement that women are underrepresented in all math-intensive fields
in the academy: in geoscience, engineering, economics, math and computer science,
and physical science (so-called GEMP) in 2010, women comprised only 25–44% of
tenure-track assistant professors and 7–16% of full professors (authors’ calculations
based on the NSF 2010 Survey of Doctorate Recipients). But there is heated debate
over why women are so conspicuously absent in these fields compared to social and
life sciences, where the comparable figures are 66% of assistant professorships in
psychology, 45% in social science (excluding economics), and 38% in biology; for
full professors, the figures are 35%, 23%, and 24%, respectively. (Ceci, Ginther,
Kahn, & Williams, 2014)

Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In this Emerging Trends essay, we review and analyze reasons for the
shortage of women in math-intensive fields, beginning with the claim that
women’s underrepresentation can be explained by sex differences in mathematical and spatial ability favoring males, coupled with bias against females
in myriad forms. Following our presentation of the argument and evidence
in favor of these alleged causes, we present evidence suggesting that they
cannot explain women’s underrepresentation in math-intensive careers and
that other causes are more consistent with the data. We begin, however,
with an acknowledgment that despite their current underrepresentation in
math-based fields, women have made tremendous progress over the past
four decades, sometimes quadrupling their presence (Ceci et al., 2014).
WHAT ARE THE CAUSES OF WOMEN’S CURRENT
UNDERREPRESENTATION IN MATH-INTENSIVE FIELDS?
If we had written this essay many years ago, our answer would differ from
what we provide here. This is because the trends are changing fast, and
today they look very different from the past. Even a decade ago, the data
looked somewhat different, and data more than a decade old are rapidly
becoming obsolete. Below, we address three broad claims for women’s
underrepresentation in mathematically intensive careers: (i) males outperforming females in spatial and mathematical domains, resulting in fewer
females in the extremely highly math-talented level needed for admission to
graduate programs and beyond; (ii) biases against hiring of mathematically
capable female applicants and bias in evaluating their work-products (e.g.,
journal submissions and grant applications), and (iii) sex differences in
preferences and choices that lead men and women down different career
paths even when they have comparable mathematical talent. Our analysis is
based on the most current findings.
SEX DIFFERENCES IN MATHEMATICAL AND SPATIAL APTITUDE
Some have suggested that the shortage of women in math-intensive fields is
rooted in aptitude differences that are visible among males and females very
early in life and which accumulate over the lifecourse. We have reviewed
this argument in detail elsewhere, and the interested reader can find the
relevant references and findings there (Ceci, Williams, & Barnett, 2009;
Ceci et al., 2014). In short, the argument is that males already exhibit better
three-dimensional spatial-rotation ability by 3–4 months of age, and this spatial superiority grows over time to give them an advantage in mathematics
(e.g., geometry) and spatial cognition, two key aptitudes involved in fields
such as engineering, computer science, and physics. There have been over

Why So Few Women in Mathematically Intensive Fields?

3

100 analyses showing substantial male superiority in three-dimensional
mental rotation, with effect sizes favoring men that are large, on the order
of 0.5–1.0 standard deviations (Voyer, Boyer, & Bryden, 1995). The male
superiority for spatial 3D rotation is found across the life span (in infants
through the elderly) and across many nations (Ceci et al., 2009).
There are three main reasons why we were led to reject this hypothesis
as a major explanation of women’s underrepresentation in math-intensive
careers. First, the picture is more complicated than the infant studies suggest,
with some failures to replicate and some studies finding no sex differences by
9 months of age. Generally, sex differences at this early age are also dependent
on whether the mental-rotation task requires a rigid surface transformation
or a nonrigid one (a shape that is rigid is one in which the distance and orientation of points within it remain unchanged when the shape is transformed or
rotated; sex differences are often pronounced on such rigid surface rotations)
and whether the task is speeded or not (see Ceci et al., 2014 for review).
Thus, it is not a simple matter of males being better than females. Second, on average, girls and women do as well as boys and men in mathematics from the early grades through college; on average, females earn 0.1–0.2
grade points higher than males in math courses. In other words, there are
few persuasive causal connections between early spatial ability and subsequent mathematical ability. If women comprise nearly half of the bachelor
degrees in mathematics, and on average they earn better grades in mathematics classes throughout high school and college, then how can early spatial differences be responsible for their underrepresentation in mathematical
fields? Thus, whatever native ability advantage males have in mathematics
and spatial cognition, it does not seem to preclude females from achieving at
high levels in mathematics.
However, the above evidence of sex differences in spatial and mathematical ability is based on average performance, not on stellar performance, which
some might argue is needed to be successful in math and engineering fields.
Specifically, although there are no sex differences in average math scores,
males are overrepresented among the top 1% on math aptitude tests such
as the SAT-M and GRE-Q (both by ratios of approximately 2 to 1). So, can
this 2–1 asymmetry at the right tail of the math-ability distribution explain
the shortage of women in math-intensive fields? Perhaps, to get accepted into
doctoral programs in highly quantitative fields, there will be two male applicants admitted for every one female applicant admitted. Although this could
contribute to women’s shortage in math-intensive fields, we concluded that
the 2:1 ratio among the top 1% of math scorers would predict many more
women in these fields, if mathematics was the controlling reason for their
shortage. Depending on the math-based field under analysis, women today
occupy fewer than 16% of full professorships (and sometimes even fewer

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

than 5%). Thus, if the dearth of women in these professions was the result
of a 2:1 ratio in mathematics aptitude alone, then there should be at least
one-third women in them, but fewer than half that percentage of women
occupy top positions.
As a side note, there are many examples of cultural and ethnic reversals of
male superiority among high math scorers. In the United States, for example,
female Latino kindergartners outperform male Latino kindergartners, and
across the globe, there are other instances in which females excel over males
at the right tail of the math distribution (Ceci, Ginther, et al., 2014; Ceci,
Williams, et al., 2009). This does not gainsay the very real overrepresentation
of males among the top 1% or beyond (e.g., males outnumber females at
the extreme right tail, i.e., the top 0.01%—1 in 10,000—roughly 3.8:1). But,
it does argue that such sex differences are not carved in stone and that
elsewhere females have achieved parity or superiority, suggesting that the
sociocultural environment plays an important role in bringing latent talent
to fruition.
BIAS AGAINST WOMEN AND THEIR WORK-PRODUCTS
If math and spatial advantages enjoyed by males cannot account for the relatively lower percentage of women engineers, physicists, computer scientists,
economists, and mathematicians, then what factor can? One common argument is that it results from bias against women and their work-products,
affecting interviewing and hiring and evaluations of lectures, manuscripts,
and grant applications. This is a common claim in gender-equity reports and
in the media, and we have documented many recent such claims (Ceci et al.,
2014). A frequent claim is that women are in short supply, because they have
to be better than men to be interviewed and hired. In short, the claim of
biases against women scientists and engineers by search committees that
prefer to hire males over equally (or more) qualified females, by grant panels that downgrade proposals from women scientists, and by journal editors
and reviewers who rate papers higher when a male name is on it, is pervasive. Consider a few of the many such claims, which we have catalogued
elsewhere (Ceci et al., 2014):
“It is now recognized that (sex) biases functional many levels within science
including funding, allocation, employment, publication, and general research
directions”
(Lortie et al., 2007, p. 1247).
“These experimental findings suggest that, contrary to some assertions, gender discrimination in science is not a myth. Specifically, when presented with

Why So Few Women in Mathematically Intensive Fields?

5

identical applicants who differed only by their gender, science faculty members
evaluated the male student as superior, were more likely to hire him, paid him
more money, and offered him more career mentoring”
(Moss-Racusin, C. Commentary and Analysis from SPSP.org September 21, 2012
http://spsptalks.wordpress.com/2012/09/21/are-science-faculty-biased).
“Research has pointed to (sex) bias in peer review and hiring. For example, a
female postdoctoral applicant had to … publish at least three more papers in
a prestigious science journal or an additional 20 papers in lesser-known specialty journals to be judged as productive as a male applicant … . The systematic
underrating of female applicants could help explain the lower success rate of
female scientists in achieving high academic ranks”
(American Association of University Women: Hill, Corbett, & Rose, 2010, p. 24).
“Psychological research has shown that most people– even those who explicitly and sincerely avow egalitarian views– hold what have been described as
implicit biases … There are countless situations in which such mechanisms
are triggered: classroom situations, hiring committees, refereeing of papers for
journals, distribution of departmental tasks (research, teaching, admin.) etc.”
(Oct. 2, 2010 at http://www.newappsblog.com/2010/10/implicit-biases1.html).
“Women and minorities must both deal with implicit bias, a problem that is
well-documented in the social science literature … Donna Dean (President of
the Association for Women in Science) describes the problem of implicit bias in
these terms: ‘People are most comfortable with people who think and look like
themselves.”
(Powell, K. (2007). Beyond the glass ceiling. Nature, 448, p. 99)

October 8, 2013 issue of US News & World Report; the headline reads:
STEM Roundup: Bias, Not Babies, Hamper Women in STEM (http://www.
usnews.com/news/stem-solutions/articles/2013/10/08/stem-roundup-biasnot-babies-hamper-women-in-stem?s_cid=rss:stem-roundup-bias-not-babieshamper-women-in-stem)

Another recent illustration of the bias claim can be seen in the New York
Times Sunday Magazine article by Pollack, October 2013, who writes that the
underrepresentation of women in math-intensive fields is due—at least in
part—to male underestimations of women’s competence and that this is
why women are not hired for tenure-track jobs. Her essay is replete with
such claims, for example, when she quotes a male mathematics professor at
Yale about his explanation for the shortage of female math professors there:

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

“I guess I just haven’t seen that many women whose work I’m excited about.”
(http://www.nytimes.com/2013/10/06/magazine/why-are-there-still-sofew-women-in-science.html)
An even more recent version of this claim appears in an article in the journal
Nature and the myriad blogs that it spawned, for example,
“In the past, fewer women worked outside the home and as that gradually
shifted, there was hiring bias, which means historically women have had fewer
science citations than men. That’s simple numbers, just like fewer handicapped
people and conservatives get citations in modern academia. But is that bias?
The authors (in Nature) say it is.”
(Science 2.0 http://www.science20.com/news_articles/are_journal_citations_
biased_against_women-126192)

Given the ubiquity of such claims of bias in evaluating and hiring women,
one might imagine that the evidentiary base of these claims is sound. On one
level, it is––each of the above claims is supported by studies demonstrating
that women or their work-products (e.g., papers, grants, lectures) are downgraded vis-à-vis comparable work-products of men. Over a hundred such
studies exist, dating back nearly four decades. However, there is a disconnect
between these studies and the source of women’s current underrepresentation in math-intensive fields. None of these showings of bias can be causally
tied to the current shortage of women in the math-intensive fields—the very
fields where they are most underrepresented. We have reviewed the evidence
for the claim that grant and journal reviewers are biased against women and
found it lacking. We have also reviewed the evidence regarding biased hiring and have found it lacking as well—in fact, real-world hiring data show
that actual hiring decisions in STEM fields favor women (Ceci et al., 2014).
Taken as a whole, this large literature provides no support for the claim of
bias against women by journal and grant reviewers or by search committees,
notwithstanding assertions to the contrary. Our conclusion stated:
“We find the evidence for recent sex discrimination–when it exists–is aberrant,
of small magnitude, and is superseded by larger, more sophisticated analyses
showing no bias or occasionally bias in favor of women. Although real barriers are still faced by women in science, especially mathematical sciences, our
findings suggest that historic forms of discrimination cannot explain current
UNDERREPRESENTATION”
(Ceci & Williams, 2011, p. 3157).

Why So Few Women in Mathematically Intensive Fields?

7

SEX DIFFERENCES IN CAREER INTERESTS
If neither female inferiority in mathematical aptitude nor bias against hiring
female applicants or rating their work-products is the primary cause of the
dearth of women in math-intensive fields, then what is? Part of the answer
to this question begins long before women apply for tenure-track careers in
science and engineering departments––even before they decide on their college major. The other part of the answer occurs much later and is rooted in
the decision to become a mother. We begin with the first of these causes.
Sex differences in career interests and aspirations are evident long before
college students declare their major. By early adolescence, surveys reveal that
few girls aspire to be engineers, physicists, or computer scientists; in contrast,
about a quarter of boys do aspire to working in these fields. Instead, girls
profess to be interested in biology, law, and medicine, both human and animal. Generally, there is a so-called “people-thing” dimension along which
males and female differ, with females tilting toward activities and careers
that involve living things (nursing, social work, education, medicine, biology, animal science), whereas males are more likely to lean toward symbol manipulation and inanimate objects, hence engineering, computer science, and physics. This “people-thing” dimension has been amply demonstrated in surveys of over hundreds of thousands of people and suggests
an important source of gendered differences in careers. In one meta-analysis
of the people-versus-things dimension, Sue, Rounds, and Armstrong (2009)
revealed large sex differences in vocational and educational choices; Lippa
(2010) analyzed more than 200,000 people in 53 nations as part of a BBC Internet survey and reported a large effect size (1.40) in gendered occupations.
Adolescent girls appear less certain than boys that science has a positive
societal influence, and they report being less certain that science can help
solve environmental and social problems. They are also more likely to think
scientists are “uncaring”; they are more unsure of their interest in STEM
careers, and they have significantly greater interest in biology, whereas boys
have greater interest in chemistry and physics (Bennett & Hogarth, 2009).
Throughout high school, females maintain interests in medicine, biology,
law, humanities, and social sciences, whereas males are more likely to prefer
science and math careers. These early preferences are reflected in college
majors, with roughly only 21% of physics majors being females, 22% of
computer science majors being females, and 24% of civil engineers being
females (electrical engineering and mechanical engineering each having
around 13% females, and chemical engineering 17%).
None of these sex differences is immutable, however, and there have been
dramatic increases in the percentage of females declaring math-intensive
majors over the past 40 years; so, it is very possible that women’s fraction

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

of these majors will continue to increase. But, as far as the current dearth
of women is concerned, these figures mimic the professed aspirations of
boys and girls in adolescent and high school surveys and are therefore
unsurprising. In fact, were it the case that women suddenly comprised
half or more of engineering majors after claiming to be uninterested in the
subject a few years earlier, this would be surprising. Of course, initial interest
is not the entire story; for example, even among those females who aspire
to science careers, more of them switch out of a science major than do their
male counterparts (Ceci et al., 2014).
It is also the case that many more females have symmetrical ability
patterns (high in both math and verbal ability) than males, who tend to
be asymmetric, with high math ability coupled with unremarkable verbal
ability. Research has shown that an asymmetric ability profile is associated
with ability self-concepts that lead to entry into science fields. Wang, Eccles,
and Kenny (2013) demonstrated that the decision to pursue a STEM career
hinges on two things: (i) it presupposes a high level of math ability, and (ii)
STEM entry is most likely to occur when high math ability is accompanied
by relatively lower verbal ability, a condition more likely to be true of males.
It is as if having only strong math ability leads one to think of herself or
himself in terms, such as “I am good at math,” whereas being strong at math
and verbal leads to greater ambivalence about career goals. And, bear in
mind that this finding occurs even when math ability is comparable between
males and females.
Thus, sex differences in ability self-concepts and career interests are likely
contributors to women’s underrepresentation in math-intensive fields. Gendered preferences among adolescents and young adults lead to the shortage of women in fields that they rate as less desirable. A related gendered
preference has to do with lifestyle choices made later in life, particularly,
the choice to pursue motherhood (Williams & Ceci, 2012). Although among
high school students sex differences in family formation are not pronounced,
later in life the decision to have children becomes quite a significant factor in
women’s exit from tenure-track science careers. Women, and to a lesser extent
men, increasingly express dissatisfaction with the work-obsessed lives of academics at research-intensive institutions, as opposed to teaching-intensive
colleges. Surveys indicate that both women and men desire greater work–life
balance. Women especially desire balance between the demands of a family
and a job, something that surveys indicate men are somewhat less concerned
about. A manifestation of this is that many more women PhDs than men
PhDs opt not to apply for tenure-track positions or postdocs on finishing graduate school (Mason, Goulden, & Frasch, 2009; Williams & Ceci, 2012). The
mere plan to have children in the future is sufficient to dissuade more women

Why So Few Women in Mathematically Intensive Fields?

9

postdocs than men from pursuing fast-track research positions (Mason et al.,
2009).
In sum, in explaining women’s current underrepresentation in mathintensive fields, we are left with two explanations that are compelling—sex
differences in career interests and preferences, and sex differences in the
choice to be a parent and in lifecourse planning related to parental roles.
Men’s superior ability in very high-level mathematics also probably contributes to women’s choices to pursue other fields relative to men’s choices
to pursue math-based fields. And, outright bias and discrimination, while
extremely important as a historical factor, has receded greatly in importance
over the past four decades.
FUTURE DIRECTIONS
Research on women’s underrepresentation in science is being conducted in
numerous disciplines—psychology, economics, sociology, and beyond—and
the body of literature grows daily. Our understandings of the critical factors in underrepresentation today must evolve quickly to keep pace with the
growing body of knowledge on the topic. The most fruitful new analyses are
likely to be the ones that disentangle the complexities that mark key decision points in women’s lives—decisions about what subjects are interesting
and whether to take math- and science-focused programming in middle and
high school, decisions about college majors and auxiliary coursework, and
later about potentially applying to graduate school in STEM fields, decisions
about whether to apply for tenure-track academic jobs, or to follow a partner’s career, or to delay children, or to have them earlier in life. We also need
research on why women choose to leave the academy, and to what extent
they are pushed out versus simply wanting another life with more time for
children and nonwork pursuits. Our understandings would be informed by
lifecourse analyses that remain open to the possibilities that discrimination so
characteristic of older women’s experiences has been greatly reduced in the
lives of younger women, and that these younger women may face very different challenges today. The most informative future directions for research on
the women in science debate will explore the challenges of choosing motherhood for STEM scientists, and hopefully will open a discussion of how these
challenges can be softened so that women are not forced to leave a potentially fruitful 40-year career because of the needs of their children during a
single 5-year span of time. In sum, the best tools for researchers interested
in helping women maximize their well-being and success are surely an open
mind about what exactly limits women today and an awareness of the huge
corpus of high-quality, empirical work across many fields of inquiry that can
inform the debate.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

REFERENCES
Bennett, J., & Hogarth, S. (2009). Would you want to talk to a scientist at a party? High
school students’ attitudes to school science and to science. International Journal of
Science Education, 31, 1975–1998.
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation
in science: Sociocultural and biological considerations. Psychological Bulletin, 135,
218–261.
Ceci, S. J., & Williams, W. M. (2011). Understanding Current Causes of Women’s
Underrepresentation in Science. Proceedings of the National Academy of Sciences, 108,
3157–3162.
Ceci, S. J., Ginther, D., Kahn, S., & Williams, W. M. (2014). Women in Academic Science:
A Changing Landscape (Vol. 15, pp. 75–141). Psychological Science in the Public Interest.
Lippa, R. A. (2010). Sex differences in personality traits and gender-related
occupational preferences across 53 nations: Testing evolutionary and socialenvironmental theories. Archives of Sexual Behavior, 39, 619–636.
Mason, M. A., Goulden, M., & Frasch, K. (2009). Why graduate students reject the
fast track. Academe, 95, 11–16.
Sue, R., Rounds, J., & Armstrong, P. (2009). Men and things, women and people: A
meta-analysis of sex differences in interests. Psychological Bulletin, 135, 859–884.
Voyer, D., Boyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological
Bulletin, 117, 250–270.
Wang, M., Eccles, J., & Kenny, S. (2013). Not lack of ability but more choice: Individual and
gender differences in STEM career choice (Vol. 24, pp. 770–775). Psychological Science.
doi:10.1177/0956797612458937
Williams, W. M., & Ceci, S. J. (2012). When scientists choose motherhood. American
Scientist, 100, 138–145.

STEPHEN J. CECI SHORT BIOGRAPHY
Stephen J. Ceci is the H. L. Carr Chaired Professor of Developmental
Psychology at Cornell University. He is the author of over 350 publications
and the recipient of numerous scientific awards, including APA’s Thorndike
Award for Lifetime Contribution to Theoretical and Empirical Research;
The Society for Research in Child Development’s (SRCD) Award for Distinguished Contributions to Public Policy for Children; The Society for
Research in Child Development’s (SRCD) Lifetime Distinguished Scientific
Contribution; the American Psychological Association’s Distinguished
Scientific Award for the Applications of Psychology; and the Association
for Psychological Science’s James McKeen Cattell Award for Lifetime
Contribution to Scientific Psychology. He is listed among Diener et al.’s most
eminent psychologists of the modern era.

Why So Few Women in Mathematically Intensive Fields?

11

WENDY M. WILLIAMS SHORT BIOGRAPHY
Wendy M. Williams is Professor in the Department of Human Development
at Cornell University, where she studies development, assessment, training,
and societal implications of intelligence. Williams founded, and now directs,
the Cornell Institute for Women in Science (CIWS), a National Institutes of
Health––funded research and outreach center that studies and promotes the
careers of women scientists. In addition to dozens of articles and chapters on
her research, Williams has authored nine books and edited five volumes. Her
research has been featured in Nature, American Scientist, Newsweek, Business
Week, Science, Scientific American, The New York Times, The Washington Post,
USA Today, The Philadelphia Inquirer, The Chronicle of Higher Education, and
Child Magazine. She is a Fellow of the Association for Psychological Science
(APS) and four divisions of the American Psychological Association (APA),
and she has received two early career awards from APA and an award for
her work on women in science. She holds PhD and Master’s degrees in psychology from Yale University, a Master’s in physical anthropology from Yale,
and a BA in English and Biology from Columbia University, awarded cum
laude with special distinction.
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12

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

Gender and Women’s Influence in Public Settings (Political Science), Tali
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Culture as Situated Cognition (Psychology), Daphna Oyserman
Sociology of Entrepreneurship (Sociology), Martin Ruef
Born This Way: Thinking Sociologically about Essentialism (Sociology),
Kristen Schilt
Stereotype Threat (Psychology), Toni Schmader and William M. Hall
Gender and the Transition to Adulthood: A Diverse Pathways View (Sociology), Ingrid Schoon
Family Income Composition (Economics), Kristin E. Smith
The Underrepresentation of Women in Elective Office (Political Science),
Sarah F. Anzia
Transnational Work Careers (Sociology), Roland Verwiebe
Gender and Work (Sociology), Christine L. Williams and Megan Tobias Neely



Why So Few Women in
Mathematically Intensive Fields?
STEPHEN J. CECI and WENDY M. WILLIAMS

Abstract
Women have made huge gains in all fields of science over the past four decades,
greatly increasing their presence in PhD programs and in postdoctoral positions.
But, their progress has been greater in some fields than others. Although women
constitute a critical mass of faculty in fields such as biology, medicine, psychology,
veterinary science, and sociology, they continue to be underrepresented in mathematically intensive fields such as engineering, physics, chemistry, economics, computer science, and mathematics. In this essay, we describe both data and argument
pertinent to women’s underrepresentation, organized around three alleged causes.
After reviewing these three causes, we conclude that neither sex differences in mathematical and spatial ability, nor the often-alleged bias against women in science, can
explain their dearth, whereas choices and family formation plans go a long way
toward doing so.

WHY SO FEW WOMEN IN MATHEMATICALLY INTENSIVE FIELDS?
That women are underrepresented in math-intensive fields is not
controversial—all who are familiar with the data have been aware of
the dearth of women in mathematics-based fields for many decades:
There is agreement that women are underrepresented in all math-intensive fields
in the academy: in geoscience, engineering, economics, math and computer science,
and physical science (so-called GEMP) in 2010, women comprised only 25–44% of
tenure-track assistant professors and 7–16% of full professors (authors’ calculations
based on the NSF 2010 Survey of Doctorate Recipients). But there is heated debate
over why women are so conspicuously absent in these fields compared to social and
life sciences, where the comparable figures are 66% of assistant professorships in
psychology, 45% in social science (excluding economics), and 38% in biology; for
full professors, the figures are 35%, 23%, and 24%, respectively. (Ceci, Ginther,
Kahn, & Williams, 2014)

Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

2

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In this Emerging Trends essay, we review and analyze reasons for the
shortage of women in math-intensive fields, beginning with the claim that
women’s underrepresentation can be explained by sex differences in mathematical and spatial ability favoring males, coupled with bias against females
in myriad forms. Following our presentation of the argument and evidence
in favor of these alleged causes, we present evidence suggesting that they
cannot explain women’s underrepresentation in math-intensive careers and
that other causes are more consistent with the data. We begin, however,
with an acknowledgment that despite their current underrepresentation in
math-based fields, women have made tremendous progress over the past
four decades, sometimes quadrupling their presence (Ceci et al., 2014).
WHAT ARE THE CAUSES OF WOMEN’S CURRENT
UNDERREPRESENTATION IN MATH-INTENSIVE FIELDS?
If we had written this essay many years ago, our answer would differ from
what we provide here. This is because the trends are changing fast, and
today they look very different from the past. Even a decade ago, the data
looked somewhat different, and data more than a decade old are rapidly
becoming obsolete. Below, we address three broad claims for women’s
underrepresentation in mathematically intensive careers: (i) males outperforming females in spatial and mathematical domains, resulting in fewer
females in the extremely highly math-talented level needed for admission to
graduate programs and beyond; (ii) biases against hiring of mathematically
capable female applicants and bias in evaluating their work-products (e.g.,
journal submissions and grant applications), and (iii) sex differences in
preferences and choices that lead men and women down different career
paths even when they have comparable mathematical talent. Our analysis is
based on the most current findings.
SEX DIFFERENCES IN MATHEMATICAL AND SPATIAL APTITUDE
Some have suggested that the shortage of women in math-intensive fields is
rooted in aptitude differences that are visible among males and females very
early in life and which accumulate over the lifecourse. We have reviewed
this argument in detail elsewhere, and the interested reader can find the
relevant references and findings there (Ceci, Williams, & Barnett, 2009;
Ceci et al., 2014). In short, the argument is that males already exhibit better
three-dimensional spatial-rotation ability by 3–4 months of age, and this spatial superiority grows over time to give them an advantage in mathematics
(e.g., geometry) and spatial cognition, two key aptitudes involved in fields
such as engineering, computer science, and physics. There have been over

Why So Few Women in Mathematically Intensive Fields?

3

100 analyses showing substantial male superiority in three-dimensional
mental rotation, with effect sizes favoring men that are large, on the order
of 0.5–1.0 standard deviations (Voyer, Boyer, & Bryden, 1995). The male
superiority for spatial 3D rotation is found across the life span (in infants
through the elderly) and across many nations (Ceci et al., 2009).
There are three main reasons why we were led to reject this hypothesis
as a major explanation of women’s underrepresentation in math-intensive
careers. First, the picture is more complicated than the infant studies suggest,
with some failures to replicate and some studies finding no sex differences by
9 months of age. Generally, sex differences at this early age are also dependent
on whether the mental-rotation task requires a rigid surface transformation
or a nonrigid one (a shape that is rigid is one in which the distance and orientation of points within it remain unchanged when the shape is transformed or
rotated; sex differences are often pronounced on such rigid surface rotations)
and whether the task is speeded or not (see Ceci et al., 2014 for review).
Thus, it is not a simple matter of males being better than females. Second, on average, girls and women do as well as boys and men in mathematics from the early grades through college; on average, females earn 0.1–0.2
grade points higher than males in math courses. In other words, there are
few persuasive causal connections between early spatial ability and subsequent mathematical ability. If women comprise nearly half of the bachelor
degrees in mathematics, and on average they earn better grades in mathematics classes throughout high school and college, then how can early spatial differences be responsible for their underrepresentation in mathematical
fields? Thus, whatever native ability advantage males have in mathematics
and spatial cognition, it does not seem to preclude females from achieving at
high levels in mathematics.
However, the above evidence of sex differences in spatial and mathematical ability is based on average performance, not on stellar performance, which
some might argue is needed to be successful in math and engineering fields.
Specifically, although there are no sex differences in average math scores,
males are overrepresented among the top 1% on math aptitude tests such
as the SAT-M and GRE-Q (both by ratios of approximately 2 to 1). So, can
this 2–1 asymmetry at the right tail of the math-ability distribution explain
the shortage of women in math-intensive fields? Perhaps, to get accepted into
doctoral programs in highly quantitative fields, there will be two male applicants admitted for every one female applicant admitted. Although this could
contribute to women’s shortage in math-intensive fields, we concluded that
the 2:1 ratio among the top 1% of math scorers would predict many more
women in these fields, if mathematics was the controlling reason for their
shortage. Depending on the math-based field under analysis, women today
occupy fewer than 16% of full professorships (and sometimes even fewer

4

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

than 5%). Thus, if the dearth of women in these professions was the result
of a 2:1 ratio in mathematics aptitude alone, then there should be at least
one-third women in them, but fewer than half that percentage of women
occupy top positions.
As a side note, there are many examples of cultural and ethnic reversals of
male superiority among high math scorers. In the United States, for example,
female Latino kindergartners outperform male Latino kindergartners, and
across the globe, there are other instances in which females excel over males
at the right tail of the math distribution (Ceci, Ginther, et al., 2014; Ceci,
Williams, et al., 2009). This does not gainsay the very real overrepresentation
of males among the top 1% or beyond (e.g., males outnumber females at
the extreme right tail, i.e., the top 0.01%—1 in 10,000—roughly 3.8:1). But,
it does argue that such sex differences are not carved in stone and that
elsewhere females have achieved parity or superiority, suggesting that the
sociocultural environment plays an important role in bringing latent talent
to fruition.
BIAS AGAINST WOMEN AND THEIR WORK-PRODUCTS
If math and spatial advantages enjoyed by males cannot account for the relatively lower percentage of women engineers, physicists, computer scientists,
economists, and mathematicians, then what factor can? One common argument is that it results from bias against women and their work-products,
affecting interviewing and hiring and evaluations of lectures, manuscripts,
and grant applications. This is a common claim in gender-equity reports and
in the media, and we have documented many recent such claims (Ceci et al.,
2014). A frequent claim is that women are in short supply, because they have
to be better than men to be interviewed and hired. In short, the claim of
biases against women scientists and engineers by search committees that
prefer to hire males over equally (or more) qualified females, by grant panels that downgrade proposals from women scientists, and by journal editors
and reviewers who rate papers higher when a male name is on it, is pervasive. Consider a few of the many such claims, which we have catalogued
elsewhere (Ceci et al., 2014):
“It is now recognized that (sex) biases functional many levels within science
including funding, allocation, employment, publication, and general research
directions”
(Lortie et al., 2007, p. 1247).
“These experimental findings suggest that, contrary to some assertions, gender discrimination in science is not a myth. Specifically, when presented with

Why So Few Women in Mathematically Intensive Fields?

5

identical applicants who differed only by their gender, science faculty members
evaluated the male student as superior, were more likely to hire him, paid him
more money, and offered him more career mentoring”
(Moss-Racusin, C. Commentary and Analysis from SPSP.org September 21, 2012
http://spsptalks.wordpress.com/2012/09/21/are-science-faculty-biased).
“Research has pointed to (sex) bias in peer review and hiring. For example, a
female postdoctoral applicant had to … publish at least three more papers in
a prestigious science journal or an additional 20 papers in lesser-known specialty journals to be judged as productive as a male applicant … . The systematic
underrating of female applicants could help explain the lower success rate of
female scientists in achieving high academic ranks”
(American Association of University Women: Hill, Corbett, & Rose, 2010, p. 24).
“Psychological research has shown that most people– even those who explicitly and sincerely avow egalitarian views– hold what have been described as
implicit biases … There are countless situations in which such mechanisms
are triggered: classroom situations, hiring committees, refereeing of papers for
journals, distribution of departmental tasks (research, teaching, admin.) etc.”
(Oct. 2, 2010 at http://www.newappsblog.com/2010/10/implicit-biases1.html).
“Women and minorities must both deal with implicit bias, a problem that is
well-documented in the social science literature … Donna Dean (President of
the Association for Women in Science) describes the problem of implicit bias in
these terms: ‘People are most comfortable with people who think and look like
themselves.”
(Powell, K. (2007). Beyond the glass ceiling. Nature, 448, p. 99)

October 8, 2013 issue of US News & World Report; the headline reads:
STEM Roundup: Bias, Not Babies, Hamper Women in STEM (http://www.
usnews.com/news/stem-solutions/articles/2013/10/08/stem-roundup-biasnot-babies-hamper-women-in-stem?s_cid=rss:stem-roundup-bias-not-babieshamper-women-in-stem)

Another recent illustration of the bias claim can be seen in the New York
Times Sunday Magazine article by Pollack, October 2013, who writes that the
underrepresentation of women in math-intensive fields is due—at least in
part—to male underestimations of women’s competence and that this is
why women are not hired for tenure-track jobs. Her essay is replete with
such claims, for example, when she quotes a male mathematics professor at
Yale about his explanation for the shortage of female math professors there:

6

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

“I guess I just haven’t seen that many women whose work I’m excited about.”
(http://www.nytimes.com/2013/10/06/magazine/why-are-there-still-sofew-women-in-science.html)
An even more recent version of this claim appears in an article in the journal
Nature and the myriad blogs that it spawned, for example,
“In the past, fewer women worked outside the home and as that gradually
shifted, there was hiring bias, which means historically women have had fewer
science citations than men. That’s simple numbers, just like fewer handicapped
people and conservatives get citations in modern academia. But is that bias?
The authors (in Nature) say it is.”
(Science 2.0 http://www.science20.com/news_articles/are_journal_citations_
biased_against_women-126192)

Given the ubiquity of such claims of bias in evaluating and hiring women,
one might imagine that the evidentiary base of these claims is sound. On one
level, it is––each of the above claims is supported by studies demonstrating
that women or their work-products (e.g., papers, grants, lectures) are downgraded vis-à-vis comparable work-products of men. Over a hundred such
studies exist, dating back nearly four decades. However, there is a disconnect
between these studies and the source of women’s current underrepresentation in math-intensive fields. None of these showings of bias can be causally
tied to the current shortage of women in the math-intensive fields—the very
fields where they are most underrepresented. We have reviewed the evidence
for the claim that grant and journal reviewers are biased against women and
found it lacking. We have also reviewed the evidence regarding biased hiring and have found it lacking as well—in fact, real-world hiring data show
that actual hiring decisions in STEM fields favor women (Ceci et al., 2014).
Taken as a whole, this large literature provides no support for the claim of
bias against women by journal and grant reviewers or by search committees,
notwithstanding assertions to the contrary. Our conclusion stated:
“We find the evidence for recent sex discrimination–when it exists–is aberrant,
of small magnitude, and is superseded by larger, more sophisticated analyses
showing no bias or occasionally bias in favor of women. Although real barriers are still faced by women in science, especially mathematical sciences, our
findings suggest that historic forms of discrimination cannot explain current
UNDERREPRESENTATION”
(Ceci & Williams, 2011, p. 3157).

Why So Few Women in Mathematically Intensive Fields?

7

SEX DIFFERENCES IN CAREER INTERESTS
If neither female inferiority in mathematical aptitude nor bias against hiring
female applicants or rating their work-products is the primary cause of the
dearth of women in math-intensive fields, then what is? Part of the answer
to this question begins long before women apply for tenure-track careers in
science and engineering departments––even before they decide on their college major. The other part of the answer occurs much later and is rooted in
the decision to become a mother. We begin with the first of these causes.
Sex differences in career interests and aspirations are evident long before
college students declare their major. By early adolescence, surveys reveal that
few girls aspire to be engineers, physicists, or computer scientists; in contrast,
about a quarter of boys do aspire to working in these fields. Instead, girls
profess to be interested in biology, law, and medicine, both human and animal. Generally, there is a so-called “people-thing” dimension along which
males and female differ, with females tilting toward activities and careers
that involve living things (nursing, social work, education, medicine, biology, animal science), whereas males are more likely to lean toward symbol manipulation and inanimate objects, hence engineering, computer science, and physics. This “people-thing” dimension has been amply demonstrated in surveys of over hundreds of thousands of people and suggests
an important source of gendered differences in careers. In one meta-analysis
of the people-versus-things dimension, Sue, Rounds, and Armstrong (2009)
revealed large sex differences in vocational and educational choices; Lippa
(2010) analyzed more than 200,000 people in 53 nations as part of a BBC Internet survey and reported a large effect size (1.40) in gendered occupations.
Adolescent girls appear less certain than boys that science has a positive
societal influence, and they report being less certain that science can help
solve environmental and social problems. They are also more likely to think
scientists are “uncaring”; they are more unsure of their interest in STEM
careers, and they have significantly greater interest in biology, whereas boys
have greater interest in chemistry and physics (Bennett & Hogarth, 2009).
Throughout high school, females maintain interests in medicine, biology,
law, humanities, and social sciences, whereas males are more likely to prefer
science and math careers. These early preferences are reflected in college
majors, with roughly only 21% of physics majors being females, 22% of
computer science majors being females, and 24% of civil engineers being
females (electrical engineering and mechanical engineering each having
around 13% females, and chemical engineering 17%).
None of these sex differences is immutable, however, and there have been
dramatic increases in the percentage of females declaring math-intensive
majors over the past 40 years; so, it is very possible that women’s fraction

8

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

of these majors will continue to increase. But, as far as the current dearth
of women is concerned, these figures mimic the professed aspirations of
boys and girls in adolescent and high school surveys and are therefore
unsurprising. In fact, were it the case that women suddenly comprised
half or more of engineering majors after claiming to be uninterested in the
subject a few years earlier, this would be surprising. Of course, initial interest
is not the entire story; for example, even among those females who aspire
to science careers, more of them switch out of a science major than do their
male counterparts (Ceci et al., 2014).
It is also the case that many more females have symmetrical ability
patterns (high in both math and verbal ability) than males, who tend to
be asymmetric, with high math ability coupled with unremarkable verbal
ability. Research has shown that an asymmetric ability profile is associated
with ability self-concepts that lead to entry into science fields. Wang, Eccles,
and Kenny (2013) demonstrated that the decision to pursue a STEM career
hinges on two things: (i) it presupposes a high level of math ability, and (ii)
STEM entry is most likely to occur when high math ability is accompanied
by relatively lower verbal ability, a condition more likely to be true of males.
It is as if having only strong math ability leads one to think of herself or
himself in terms, such as “I am good at math,” whereas being strong at math
and verbal leads to greater ambivalence about career goals. And, bear in
mind that this finding occurs even when math ability is comparable between
males and females.
Thus, sex differences in ability self-concepts and career interests are likely
contributors to women’s underrepresentation in math-intensive fields. Gendered preferences among adolescents and young adults lead to the shortage of women in fields that they rate as less desirable. A related gendered
preference has to do with lifestyle choices made later in life, particularly,
the choice to pursue motherhood (Williams & Ceci, 2012). Although among
high school students sex differences in family formation are not pronounced,
later in life the decision to have children becomes quite a significant factor in
women’s exit from tenure-track science careers. Women, and to a lesser extent
men, increasingly express dissatisfaction with the work-obsessed lives of academics at research-intensive institutions, as opposed to teaching-intensive
colleges. Surveys indicate that both women and men desire greater work–life
balance. Women especially desire balance between the demands of a family
and a job, something that surveys indicate men are somewhat less concerned
about. A manifestation of this is that many more women PhDs than men
PhDs opt not to apply for tenure-track positions or postdocs on finishing graduate school (Mason, Goulden, & Frasch, 2009; Williams & Ceci, 2012). The
mere plan to have children in the future is sufficient to dissuade more women

Why So Few Women in Mathematically Intensive Fields?

9

postdocs than men from pursuing fast-track research positions (Mason et al.,
2009).
In sum, in explaining women’s current underrepresentation in mathintensive fields, we are left with two explanations that are compelling—sex
differences in career interests and preferences, and sex differences in the
choice to be a parent and in lifecourse planning related to parental roles.
Men’s superior ability in very high-level mathematics also probably contributes to women’s choices to pursue other fields relative to men’s choices
to pursue math-based fields. And, outright bias and discrimination, while
extremely important as a historical factor, has receded greatly in importance
over the past four decades.
FUTURE DIRECTIONS
Research on women’s underrepresentation in science is being conducted in
numerous disciplines—psychology, economics, sociology, and beyond—and
the body of literature grows daily. Our understandings of the critical factors in underrepresentation today must evolve quickly to keep pace with the
growing body of knowledge on the topic. The most fruitful new analyses are
likely to be the ones that disentangle the complexities that mark key decision points in women’s lives—decisions about what subjects are interesting
and whether to take math- and science-focused programming in middle and
high school, decisions about college majors and auxiliary coursework, and
later about potentially applying to graduate school in STEM fields, decisions
about whether to apply for tenure-track academic jobs, or to follow a partner’s career, or to delay children, or to have them earlier in life. We also need
research on why women choose to leave the academy, and to what extent
they are pushed out versus simply wanting another life with more time for
children and nonwork pursuits. Our understandings would be informed by
lifecourse analyses that remain open to the possibilities that discrimination so
characteristic of older women’s experiences has been greatly reduced in the
lives of younger women, and that these younger women may face very different challenges today. The most informative future directions for research on
the women in science debate will explore the challenges of choosing motherhood for STEM scientists, and hopefully will open a discussion of how these
challenges can be softened so that women are not forced to leave a potentially fruitful 40-year career because of the needs of their children during a
single 5-year span of time. In sum, the best tools for researchers interested
in helping women maximize their well-being and success are surely an open
mind about what exactly limits women today and an awareness of the huge
corpus of high-quality, empirical work across many fields of inquiry that can
inform the debate.

10

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

REFERENCES
Bennett, J., & Hogarth, S. (2009). Would you want to talk to a scientist at a party? High
school students’ attitudes to school science and to science. International Journal of
Science Education, 31, 1975–1998.
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation
in science: Sociocultural and biological considerations. Psychological Bulletin, 135,
218–261.
Ceci, S. J., & Williams, W. M. (2011). Understanding Current Causes of Women’s
Underrepresentation in Science. Proceedings of the National Academy of Sciences, 108,
3157–3162.
Ceci, S. J., Ginther, D., Kahn, S., & Williams, W. M. (2014). Women in Academic Science:
A Changing Landscape (Vol. 15, pp. 75–141). Psychological Science in the Public Interest.
Lippa, R. A. (2010). Sex differences in personality traits and gender-related
occupational preferences across 53 nations: Testing evolutionary and socialenvironmental theories. Archives of Sexual Behavior, 39, 619–636.
Mason, M. A., Goulden, M., & Frasch, K. (2009). Why graduate students reject the
fast track. Academe, 95, 11–16.
Sue, R., Rounds, J., & Armstrong, P. (2009). Men and things, women and people: A
meta-analysis of sex differences in interests. Psychological Bulletin, 135, 859–884.
Voyer, D., Boyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological
Bulletin, 117, 250–270.
Wang, M., Eccles, J., & Kenny, S. (2013). Not lack of ability but more choice: Individual and
gender differences in STEM career choice (Vol. 24, pp. 770–775). Psychological Science.
doi:10.1177/0956797612458937
Williams, W. M., & Ceci, S. J. (2012). When scientists choose motherhood. American
Scientist, 100, 138–145.

STEPHEN J. CECI SHORT BIOGRAPHY
Stephen J. Ceci is the H. L. Carr Chaired Professor of Developmental
Psychology at Cornell University. He is the author of over 350 publications
and the recipient of numerous scientific awards, including APA’s Thorndike
Award for Lifetime Contribution to Theoretical and Empirical Research;
The Society for Research in Child Development’s (SRCD) Award for Distinguished Contributions to Public Policy for Children; The Society for
Research in Child Development’s (SRCD) Lifetime Distinguished Scientific
Contribution; the American Psychological Association’s Distinguished
Scientific Award for the Applications of Psychology; and the Association
for Psychological Science’s James McKeen Cattell Award for Lifetime
Contribution to Scientific Psychology. He is listed among Diener et al.’s most
eminent psychologists of the modern era.

Why So Few Women in Mathematically Intensive Fields?

11

WENDY M. WILLIAMS SHORT BIOGRAPHY
Wendy M. Williams is Professor in the Department of Human Development
at Cornell University, where she studies development, assessment, training,
and societal implications of intelligence. Williams founded, and now directs,
the Cornell Institute for Women in Science (CIWS), a National Institutes of
Health––funded research and outreach center that studies and promotes the
careers of women scientists. In addition to dozens of articles and chapters on
her research, Williams has authored nine books and edited five volumes. Her
research has been featured in Nature, American Scientist, Newsweek, Business
Week, Science, Scientific American, The New York Times, The Washington Post,
USA Today, The Philadelphia Inquirer, The Chronicle of Higher Education, and
Child Magazine. She is a Fellow of the Association for Psychological Science
(APS) and four divisions of the American Psychological Association (APA),
and she has received two early career awards from APA and an award for
her work on women in science. She holds PhD and Master’s degrees in psychology from Yale University, a Master’s in physical anthropology from Yale,
and a BA in English and Biology from Columbia University, awarded cum
laude with special distinction.
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Why So Few Women in
Mathematically Intensive Fields?
STEPHEN J. CECI and WENDY M. WILLIAMS

Abstract
Women have made huge gains in all fields of science over the past four decades,
greatly increasing their presence in PhD programs and in postdoctoral positions.
But, their progress has been greater in some fields than others. Although women
constitute a critical mass of faculty in fields such as biology, medicine, psychology,
veterinary science, and sociology, they continue to be underrepresented in mathematically intensive fields such as engineering, physics, chemistry, economics, computer science, and mathematics. In this essay, we describe both data and argument
pertinent to women’s underrepresentation, organized around three alleged causes.
After reviewing these three causes, we conclude that neither sex differences in mathematical and spatial ability, nor the often-alleged bias against women in science, can
explain their dearth, whereas choices and family formation plans go a long way
toward doing so.

WHY SO FEW WOMEN IN MATHEMATICALLY INTENSIVE FIELDS?
That women are underrepresented in math-intensive fields is not
controversial—all who are familiar with the data have been aware of
the dearth of women in mathematics-based fields for many decades:
There is agreement that women are underrepresented in all math-intensive fields
in the academy: in geoscience, engineering, economics, math and computer science,
and physical science (so-called GEMP) in 2010, women comprised only 25–44% of
tenure-track assistant professors and 7–16% of full professors (authors’ calculations
based on the NSF 2010 Survey of Doctorate Recipients). But there is heated debate
over why women are so conspicuously absent in these fields compared to social and
life sciences, where the comparable figures are 66% of assistant professorships in
psychology, 45% in social science (excluding economics), and 38% in biology; for
full professors, the figures are 35%, 23%, and 24%, respectively. (Ceci, Ginther,
Kahn, & Williams, 2014)

Emerging Trends in the Social and Behavioral Sciences. Edited by Robert Scott and Stephen Kosslyn.
© 2015 John Wiley & Sons, Inc. ISBN 978-1-118-90077-2.

1

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

In this Emerging Trends essay, we review and analyze reasons for the
shortage of women in math-intensive fields, beginning with the claim that
women’s underrepresentation can be explained by sex differences in mathematical and spatial ability favoring males, coupled with bias against females
in myriad forms. Following our presentation of the argument and evidence
in favor of these alleged causes, we present evidence suggesting that they
cannot explain women’s underrepresentation in math-intensive careers and
that other causes are more consistent with the data. We begin, however,
with an acknowledgment that despite their current underrepresentation in
math-based fields, women have made tremendous progress over the past
four decades, sometimes quadrupling their presence (Ceci et al., 2014).
WHAT ARE THE CAUSES OF WOMEN’S CURRENT
UNDERREPRESENTATION IN MATH-INTENSIVE FIELDS?
If we had written this essay many years ago, our answer would differ from
what we provide here. This is because the trends are changing fast, and
today they look very different from the past. Even a decade ago, the data
looked somewhat different, and data more than a decade old are rapidly
becoming obsolete. Below, we address three broad claims for women’s
underrepresentation in mathematically intensive careers: (i) males outperforming females in spatial and mathematical domains, resulting in fewer
females in the extremely highly math-talented level needed for admission to
graduate programs and beyond; (ii) biases against hiring of mathematically
capable female applicants and bias in evaluating their work-products (e.g.,
journal submissions and grant applications), and (iii) sex differences in
preferences and choices that lead men and women down different career
paths even when they have comparable mathematical talent. Our analysis is
based on the most current findings.
SEX DIFFERENCES IN MATHEMATICAL AND SPATIAL APTITUDE
Some have suggested that the shortage of women in math-intensive fields is
rooted in aptitude differences that are visible among males and females very
early in life and which accumulate over the lifecourse. We have reviewed
this argument in detail elsewhere, and the interested reader can find the
relevant references and findings there (Ceci, Williams, & Barnett, 2009;
Ceci et al., 2014). In short, the argument is that males already exhibit better
three-dimensional spatial-rotation ability by 3–4 months of age, and this spatial superiority grows over time to give them an advantage in mathematics
(e.g., geometry) and spatial cognition, two key aptitudes involved in fields
such as engineering, computer science, and physics. There have been over

Why So Few Women in Mathematically Intensive Fields?

3

100 analyses showing substantial male superiority in three-dimensional
mental rotation, with effect sizes favoring men that are large, on the order
of 0.5–1.0 standard deviations (Voyer, Boyer, & Bryden, 1995). The male
superiority for spatial 3D rotation is found across the life span (in infants
through the elderly) and across many nations (Ceci et al., 2009).
There are three main reasons why we were led to reject this hypothesis
as a major explanation of women’s underrepresentation in math-intensive
careers. First, the picture is more complicated than the infant studies suggest,
with some failures to replicate and some studies finding no sex differences by
9 months of age. Generally, sex differences at this early age are also dependent
on whether the mental-rotation task requires a rigid surface transformation
or a nonrigid one (a shape that is rigid is one in which the distance and orientation of points within it remain unchanged when the shape is transformed or
rotated; sex differences are often pronounced on such rigid surface rotations)
and whether the task is speeded or not (see Ceci et al., 2014 for review).
Thus, it is not a simple matter of males being better than females. Second, on average, girls and women do as well as boys and men in mathematics from the early grades through college; on average, females earn 0.1–0.2
grade points higher than males in math courses. In other words, there are
few persuasive causal connections between early spatial ability and subsequent mathematical ability. If women comprise nearly half of the bachelor
degrees in mathematics, and on average they earn better grades in mathematics classes throughout high school and college, then how can early spatial differences be responsible for their underrepresentation in mathematical
fields? Thus, whatever native ability advantage males have in mathematics
and spatial cognition, it does not seem to preclude females from achieving at
high levels in mathematics.
However, the above evidence of sex differences in spatial and mathematical ability is based on average performance, not on stellar performance, which
some might argue is needed to be successful in math and engineering fields.
Specifically, although there are no sex differences in average math scores,
males are overrepresented among the top 1% on math aptitude tests such
as the SAT-M and GRE-Q (both by ratios of approximately 2 to 1). So, can
this 2–1 asymmetry at the right tail of the math-ability distribution explain
the shortage of women in math-intensive fields? Perhaps, to get accepted into
doctoral programs in highly quantitative fields, there will be two male applicants admitted for every one female applicant admitted. Although this could
contribute to women’s shortage in math-intensive fields, we concluded that
the 2:1 ratio among the top 1% of math scorers would predict many more
women in these fields, if mathematics was the controlling reason for their
shortage. Depending on the math-based field under analysis, women today
occupy fewer than 16% of full professorships (and sometimes even fewer

4

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

than 5%). Thus, if the dearth of women in these professions was the result
of a 2:1 ratio in mathematics aptitude alone, then there should be at least
one-third women in them, but fewer than half that percentage of women
occupy top positions.
As a side note, there are many examples of cultural and ethnic reversals of
male superiority among high math scorers. In the United States, for example,
female Latino kindergartners outperform male Latino kindergartners, and
across the globe, there are other instances in which females excel over males
at the right tail of the math distribution (Ceci, Ginther, et al., 2014; Ceci,
Williams, et al., 2009). This does not gainsay the very real overrepresentation
of males among the top 1% or beyond (e.g., males outnumber females at
the extreme right tail, i.e., the top 0.01%—1 in 10,000—roughly 3.8:1). But,
it does argue that such sex differences are not carved in stone and that
elsewhere females have achieved parity or superiority, suggesting that the
sociocultural environment plays an important role in bringing latent talent
to fruition.
BIAS AGAINST WOMEN AND THEIR WORK-PRODUCTS
If math and spatial advantages enjoyed by males cannot account for the relatively lower percentage of women engineers, physicists, computer scientists,
economists, and mathematicians, then what factor can? One common argument is that it results from bias against women and their work-products,
affecting interviewing and hiring and evaluations of lectures, manuscripts,
and grant applications. This is a common claim in gender-equity reports and
in the media, and we have documented many recent such claims (Ceci et al.,
2014). A frequent claim is that women are in short supply, because they have
to be better than men to be interviewed and hired. In short, the claim of
biases against women scientists and engineers by search committees that
prefer to hire males over equally (or more) qualified females, by grant panels that downgrade proposals from women scientists, and by journal editors
and reviewers who rate papers higher when a male name is on it, is pervasive. Consider a few of the many such claims, which we have catalogued
elsewhere (Ceci et al., 2014):
“It is now recognized that (sex) biases functional many levels within science
including funding, allocation, employment, publication, and general research
directions”
(Lortie et al., 2007, p. 1247).
“These experimental findings suggest that, contrary to some assertions, gender discrimination in science is not a myth. Specifically, when presented with

Why So Few Women in Mathematically Intensive Fields?

5

identical applicants who differed only by their gender, science faculty members
evaluated the male student as superior, were more likely to hire him, paid him
more money, and offered him more career mentoring”
(Moss-Racusin, C. Commentary and Analysis from SPSP.org September 21, 2012
http://spsptalks.wordpress.com/2012/09/21/are-science-faculty-biased).
“Research has pointed to (sex) bias in peer review and hiring. For example, a
female postdoctoral applicant had to … publish at least three more papers in
a prestigious science journal or an additional 20 papers in lesser-known specialty journals to be judged as productive as a male applicant … . The systematic
underrating of female applicants could help explain the lower success rate of
female scientists in achieving high academic ranks”
(American Association of University Women: Hill, Corbett, & Rose, 2010, p. 24).
“Psychological research has shown that most people– even those who explicitly and sincerely avow egalitarian views– hold what have been described as
implicit biases … There are countless situations in which such mechanisms
are triggered: classroom situations, hiring committees, refereeing of papers for
journals, distribution of departmental tasks (research, teaching, admin.) etc.”
(Oct. 2, 2010 at http://www.newappsblog.com/2010/10/implicit-biases1.html).
“Women and minorities must both deal with implicit bias, a problem that is
well-documented in the social science literature … Donna Dean (President of
the Association for Women in Science) describes the problem of implicit bias in
these terms: ‘People are most comfortable with people who think and look like
themselves.”
(Powell, K. (2007). Beyond the glass ceiling. Nature, 448, p. 99)

October 8, 2013 issue of US News & World Report; the headline reads:
STEM Roundup: Bias, Not Babies, Hamper Women in STEM (http://www.
usnews.com/news/stem-solutions/articles/2013/10/08/stem-roundup-biasnot-babies-hamper-women-in-stem?s_cid=rss:stem-roundup-bias-not-babieshamper-women-in-stem)

Another recent illustration of the bias claim can be seen in the New York
Times Sunday Magazine article by Pollack, October 2013, who writes that the
underrepresentation of women in math-intensive fields is due—at least in
part—to male underestimations of women’s competence and that this is
why women are not hired for tenure-track jobs. Her essay is replete with
such claims, for example, when she quotes a male mathematics professor at
Yale about his explanation for the shortage of female math professors there:

6

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

“I guess I just haven’t seen that many women whose work I’m excited about.”
(http://www.nytimes.com/2013/10/06/magazine/why-are-there-still-sofew-women-in-science.html)
An even more recent version of this claim appears in an article in the journal
Nature and the myriad blogs that it spawned, for example,
“In the past, fewer women worked outside the home and as that gradually
shifted, there was hiring bias, which means historically women have had fewer
science citations than men. That’s simple numbers, just like fewer handicapped
people and conservatives get citations in modern academia. But is that bias?
The authors (in Nature) say it is.”
(Science 2.0 http://www.science20.com/news_articles/are_journal_citations_
biased_against_women-126192)

Given the ubiquity of such claims of bias in evaluating and hiring women,
one might imagine that the evidentiary base of these claims is sound. On one
level, it is––each of the above claims is supported by studies demonstrating
that women or their work-products (e.g., papers, grants, lectures) are downgraded vis-à-vis comparable work-products of men. Over a hundred such
studies exist, dating back nearly four decades. However, there is a disconnect
between these studies and the source of women’s current underrepresentation in math-intensive fields. None of these showings of bias can be causally
tied to the current shortage of women in the math-intensive fields—the very
fields where they are most underrepresented. We have reviewed the evidence
for the claim that grant and journal reviewers are biased against women and
found it lacking. We have also reviewed the evidence regarding biased hiring and have found it lacking as well—in fact, real-world hiring data show
that actual hiring decisions in STEM fields favor women (Ceci et al., 2014).
Taken as a whole, this large literature provides no support for the claim of
bias against women by journal and grant reviewers or by search committees,
notwithstanding assertions to the contrary. Our conclusion stated:
“We find the evidence for recent sex discrimination–when it exists–is aberrant,
of small magnitude, and is superseded by larger, more sophisticated analyses
showing no bias or occasionally bias in favor of women. Although real barriers are still faced by women in science, especially mathematical sciences, our
findings suggest that historic forms of discrimination cannot explain current
UNDERREPRESENTATION”
(Ceci & Williams, 2011, p. 3157).

Why So Few Women in Mathematically Intensive Fields?

7

SEX DIFFERENCES IN CAREER INTERESTS
If neither female inferiority in mathematical aptitude nor bias against hiring
female applicants or rating their work-products is the primary cause of the
dearth of women in math-intensive fields, then what is? Part of the answer
to this question begins long before women apply for tenure-track careers in
science and engineering departments––even before they decide on their college major. The other part of the answer occurs much later and is rooted in
the decision to become a mother. We begin with the first of these causes.
Sex differences in career interests and aspirations are evident long before
college students declare their major. By early adolescence, surveys reveal that
few girls aspire to be engineers, physicists, or computer scientists; in contrast,
about a quarter of boys do aspire to working in these fields. Instead, girls
profess to be interested in biology, law, and medicine, both human and animal. Generally, there is a so-called “people-thing” dimension along which
males and female differ, with females tilting toward activities and careers
that involve living things (nursing, social work, education, medicine, biology, animal science), whereas males are more likely to lean toward symbol manipulation and inanimate objects, hence engineering, computer science, and physics. This “people-thing” dimension has been amply demonstrated in surveys of over hundreds of thousands of people and suggests
an important source of gendered differences in careers. In one meta-analysis
of the people-versus-things dimension, Sue, Rounds, and Armstrong (2009)
revealed large sex differences in vocational and educational choices; Lippa
(2010) analyzed more than 200,000 people in 53 nations as part of a BBC Internet survey and reported a large effect size (1.40) in gendered occupations.
Adolescent girls appear less certain than boys that science has a positive
societal influence, and they report being less certain that science can help
solve environmental and social problems. They are also more likely to think
scientists are “uncaring”; they are more unsure of their interest in STEM
careers, and they have significantly greater interest in biology, whereas boys
have greater interest in chemistry and physics (Bennett & Hogarth, 2009).
Throughout high school, females maintain interests in medicine, biology,
law, humanities, and social sciences, whereas males are more likely to prefer
science and math careers. These early preferences are reflected in college
majors, with roughly only 21% of physics majors being females, 22% of
computer science majors being females, and 24% of civil engineers being
females (electrical engineering and mechanical engineering each having
around 13% females, and chemical engineering 17%).
None of these sex differences is immutable, however, and there have been
dramatic increases in the percentage of females declaring math-intensive
majors over the past 40 years; so, it is very possible that women’s fraction

8

EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

of these majors will continue to increase. But, as far as the current dearth
of women is concerned, these figures mimic the professed aspirations of
boys and girls in adolescent and high school surveys and are therefore
unsurprising. In fact, were it the case that women suddenly comprised
half or more of engineering majors after claiming to be uninterested in the
subject a few years earlier, this would be surprising. Of course, initial interest
is not the entire story; for example, even among those females who aspire
to science careers, more of them switch out of a science major than do their
male counterparts (Ceci et al., 2014).
It is also the case that many more females have symmetrical ability
patterns (high in both math and verbal ability) than males, who tend to
be asymmetric, with high math ability coupled with unremarkable verbal
ability. Research has shown that an asymmetric ability profile is associated
with ability self-concepts that lead to entry into science fields. Wang, Eccles,
and Kenny (2013) demonstrated that the decision to pursue a STEM career
hinges on two things: (i) it presupposes a high level of math ability, and (ii)
STEM entry is most likely to occur when high math ability is accompanied
by relatively lower verbal ability, a condition more likely to be true of males.
It is as if having only strong math ability leads one to think of herself or
himself in terms, such as “I am good at math,” whereas being strong at math
and verbal leads to greater ambivalence about career goals. And, bear in
mind that this finding occurs even when math ability is comparable between
males and females.
Thus, sex differences in ability self-concepts and career interests are likely
contributors to women’s underrepresentation in math-intensive fields. Gendered preferences among adolescents and young adults lead to the shortage of women in fields that they rate as less desirable. A related gendered
preference has to do with lifestyle choices made later in life, particularly,
the choice to pursue motherhood (Williams & Ceci, 2012). Although among
high school students sex differences in family formation are not pronounced,
later in life the decision to have children becomes quite a significant factor in
women’s exit from tenure-track science careers. Women, and to a lesser extent
men, increasingly express dissatisfaction with the work-obsessed lives of academics at research-intensive institutions, as opposed to teaching-intensive
colleges. Surveys indicate that both women and men desire greater work–life
balance. Women especially desire balance between the demands of a family
and a job, something that surveys indicate men are somewhat less concerned
about. A manifestation of this is that many more women PhDs than men
PhDs opt not to apply for tenure-track positions or postdocs on finishing graduate school (Mason, Goulden, & Frasch, 2009; Williams & Ceci, 2012). The
mere plan to have children in the future is sufficient to dissuade more women

Why So Few Women in Mathematically Intensive Fields?

9

postdocs than men from pursuing fast-track research positions (Mason et al.,
2009).
In sum, in explaining women’s current underrepresentation in mathintensive fields, we are left with two explanations that are compelling—sex
differences in career interests and preferences, and sex differences in the
choice to be a parent and in lifecourse planning related to parental roles.
Men’s superior ability in very high-level mathematics also probably contributes to women’s choices to pursue other fields relative to men’s choices
to pursue math-based fields. And, outright bias and discrimination, while
extremely important as a historical factor, has receded greatly in importance
over the past four decades.
FUTURE DIRECTIONS
Research on women’s underrepresentation in science is being conducted in
numerous disciplines—psychology, economics, sociology, and beyond—and
the body of literature grows daily. Our understandings of the critical factors in underrepresentation today must evolve quickly to keep pace with the
growing body of knowledge on the topic. The most fruitful new analyses are
likely to be the ones that disentangle the complexities that mark key decision points in women’s lives—decisions about what subjects are interesting
and whether to take math- and science-focused programming in middle and
high school, decisions about college majors and auxiliary coursework, and
later about potentially applying to graduate school in STEM fields, decisions
about whether to apply for tenure-track academic jobs, or to follow a partner’s career, or to delay children, or to have them earlier in life. We also need
research on why women choose to leave the academy, and to what extent
they are pushed out versus simply wanting another life with more time for
children and nonwork pursuits. Our understandings would be informed by
lifecourse analyses that remain open to the possibilities that discrimination so
characteristic of older women’s experiences has been greatly reduced in the
lives of younger women, and that these younger women may face very different challenges today. The most informative future directions for research on
the women in science debate will explore the challenges of choosing motherhood for STEM scientists, and hopefully will open a discussion of how these
challenges can be softened so that women are not forced to leave a potentially fruitful 40-year career because of the needs of their children during a
single 5-year span of time. In sum, the best tools for researchers interested
in helping women maximize their well-being and success are surely an open
mind about what exactly limits women today and an awareness of the huge
corpus of high-quality, empirical work across many fields of inquiry that can
inform the debate.

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EMERGING TRENDS IN THE SOCIAL AND BEHAVIORAL SCIENCES

REFERENCES
Bennett, J., & Hogarth, S. (2009). Would you want to talk to a scientist at a party? High
school students’ attitudes to school science and to science. International Journal of
Science Education, 31, 1975–1998.
Ceci, S. J., Williams, W. M., & Barnett, S. M. (2009). Women’s underrepresentation
in science: Sociocultural and biological considerations. Psychological Bulletin, 135,
218–261.
Ceci, S. J., & Williams, W. M. (2011). Understanding Current Causes of Women’s
Underrepresentation in Science. Proceedings of the National Academy of Sciences, 108,
3157–3162.
Ceci, S. J., Ginther, D., Kahn, S., & Williams, W. M. (2014). Women in Academic Science:
A Changing Landscape (Vol. 15, pp. 75–141). Psychological Science in the Public Interest.
Lippa, R. A. (2010). Sex differences in personality traits and gender-related
occupational preferences across 53 nations: Testing evolutionary and socialenvironmental theories. Archives of Sexual Behavior, 39, 619–636.
Mason, M. A., Goulden, M., & Frasch, K. (2009). Why graduate students reject the
fast track. Academe, 95, 11–16.
Sue, R., Rounds, J., & Armstrong, P. (2009). Men and things, women and people: A
meta-analysis of sex differences in interests. Psychological Bulletin, 135, 859–884.
Voyer, D., Boyer, S., & Bryden, M. P. (1995). Magnitude of sex differences in spatial abilities: A meta-analysis and consideration of critical variables. Psychological
Bulletin, 117, 250–270.
Wang, M., Eccles, J., & Kenny, S. (2013). Not lack of ability but more choice: Individual and
gender differences in STEM career choice (Vol. 24, pp. 770–775). Psychological Science.
doi:10.1177/0956797612458937
Williams, W. M., & Ceci, S. J. (2012). When scientists choose motherhood. American
Scientist, 100, 138–145.

STEPHEN J. CECI SHORT BIOGRAPHY
Stephen J. Ceci is the H. L. Carr Chaired Professor of Developmental
Psychology at Cornell University. He is the author of over 350 publications
and the recipient of numerous scientific awards, including APA’s Thorndike
Award for Lifetime Contribution to Theoretical and Empirical Research;
The Society for Research in Child Development’s (SRCD) Award for Distinguished Contributions to Public Policy for Children; The Society for
Research in Child Development’s (SRCD) Lifetime Distinguished Scientific
Contribution; the American Psychological Association’s Distinguished
Scientific Award for the Applications of Psychology; and the Association
for Psychological Science’s James McKeen Cattell Award for Lifetime
Contribution to Scientific Psychology. He is listed among Diener et al.’s most
eminent psychologists of the modern era.

Why So Few Women in Mathematically Intensive Fields?

11

WENDY M. WILLIAMS SHORT BIOGRAPHY
Wendy M. Williams is Professor in the Department of Human Development
at Cornell University, where she studies development, assessment, training,
and societal implications of intelligence. Williams founded, and now directs,
the Cornell Institute for Women in Science (CIWS), a National Institutes of
Health––funded research and outreach center that studies and promotes the
careers of women scientists. In addition to dozens of articles and chapters on
her research, Williams has authored nine books and edited five volumes. Her
research has been featured in Nature, American Scientist, Newsweek, Business
Week, Science, Scientific American, The New York Times, The Washington Post,
USA Today, The Philadelphia Inquirer, The Chronicle of Higher Education, and
Child Magazine. She is a Fellow of the Association for Psychological Science
(APS) and four divisions of the American Psychological Association (APA),
and she has received two early career awards from APA and an award for
her work on women in science. She holds PhD and Master’s degrees in psychology from Yale University, a Master’s in physical anthropology from Yale,
and a BA in English and Biology from Columbia University, awarded cum
laude with special distinction.
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Why So Few Women in Mathematically Intensive Fields?