Explanations for women's underrepresentation in math-intensive fields of science often focus on sex discrimination in grant and manuscript reviewing, interviewing, and hiring. Claims that women scientists suffer discrimination in these arenas rest on a set of studies undergirding policies and programs aimed at remediation. More recent and robust empiricism, however, fails to support assertions of discrimination in these domains. To better understand women's underrepresentation in math-intensive fields and its causes, we reprise claims of discrimination and their evidentiary bases. Based on a review of the past 20 y of data, we suggest that some of these claims are no longer valid and, if uncritically accepted as current causes of women's lack of progress, can delay or prevent understanding of contemporary determinants of women's underrepresentation. We conclude that differential gendered outcomes in the real world result from differences in resources attributable to choices, whether free or constrained, and that such choices could be influenced and better informed through education if resources were so directed. Thus, the ongoing focus on sex discrimination in reviewing, interviewing, and hiring represents costly, misplaced effort: Society is engaged in the present in solving problems of the past, rather than in addressing meaningful limitations deterring women's participation in science, technology, engineering, and mathematics careers today. Addressing today's causes of underrepresentation requires focusing on education and policy changes that will make institutions responsive to differing biological realities of the sexes. Finally, we suggest potential avenues of intervention to increase gender fairness that accord with current, as opposed to historical, findings.women in science | gender bias | child penalty | peer review S ince 1970, women have made dramatic gains in science. Today, half of all MD degrees and 52% of PhDs in life sciences are awarded to women, as are 57% of PhDs in social sciences, 71% of PhDs to psychologists, and 77% of DVMs to veterinarians.* Forty years ago, women's presence in most of these fields was several orders of magnitude less; e.g., in 1970 only 13% of PhDs in life sciences went to women (1). In the most mathintensive fields, however, women's growth has been less pronounced (2-4). Among the top 100 US universities, only 8.8-15.8% of tenure-track positions in many math-intensive fields (combined across ranks) are held by women, and female full professors number ≤10%. (SI Text, S1)These figures reveal a problem, but what is its cause? Here, we consider one of the most common alleged causes-discrimination against women in the domains of: (i) manuscript reviewing, (ii) grant funding, and (iii) interviewing/hiring. We reprise the evidence for each and describe counterevidence. We conclude that past initiatives to combat discrimination against women in science appear to have been highly successful. Women's current underrepresentation in math-intensive fields is not caused by discrimin...

The underrepresentation of women at the top of math-intensive fields is controversial, with competing claims of biological and sociocultural causation. The authors develop a framework to delineate possible causal pathways and evaluate evidence for each. Biological evidence is contradictory and inconclusive. Although cross-cultural and cross-cohort differences suggest a powerful effect of sociocultural context, evidence for specific factors is inconsistent and contradictory. Factors unique to underrepresentation in math-intensive fields include the following: (a) Math-proficient women disproportionately prefer careers in non-math-intensive fields and are more likely to leave math-intensive careers as they advance; (b) more men than women score in the extreme math-proficient range on gatekeeper tests, such as the SAT Mathematics and the Graduate Record Examinations Quantitative Reasoning sections; (c) women with high math competence are disproportionately more likely to have high verbal competence, allowing greater choice of professions; and (d) in some math-intensive fields, women with children are penalized in promotion rates. The evidence indicates that women's preferences, potentially representing both free and constrained choices, constitute the most powerful explanatory factor; a secondary factor is performance on gatekeeper tests, most likely resulting from sociocultural rather than biological causes.Keywords: sex differences, spatial ability, mathematics, family versus career trade-offs, women in science Supplemental materials: http://dx.doi.org/10.1037/a0014412.supp By 2001, women were earning 48% of bachelor's degrees (National Science Foundation, 2007) and 29% of PhD degrees (Hill & Johnson, 2004) in mathematics, representing enormous increases over the prior 30 years. Women's representation among editorial boards in science and awards panels similarly increased (Nelson & Brammer, 2008). These changes are evidence of the strength of cultural factors in determining such outcomes, because biology has not changed over this period. Despite this progress, women's representation among PhD degree holders has not coincided with proportional faculty appointments: Women earned 31.3% of chemistry PhD degrees between 1993 and 2003 but in 2002 were hired for only 21.5% of assistant professorships. Similar disparities exist for new faculty appointments in physics, engineering, and mathematics. In 1976 women represented only 7.5% of the faculty in physical sciences and less than 1% in engineering (Dearman & Plisko, 1979). By 2006 the percentage had increased to 16%-25%, but the hiring of assistant professors in these fields has not been proportional to female PhD pools. This hiring disparity extends beyond math-intensive fields.Even in less math-intensive fields, such as cellular and molecular biology, fields in which women obtain 46% of all PhD degrees, women disproportionately drop out at multiple points. The picture is the same across many science fields: Women are not being hired as assistant professors at the ra...

Much has been written in the past two decades about women in academic science careers, but this literature is contradictory. Many analyses have revealed a level playing field, with men and women faring equally, whereas other analyses have suggested numerous areas in which the playing field is not level. The only widely-agreed-upon conclusion is that women are underrepresented in college majors, graduate school programs, and the professoriate in those fields that are the most mathematically intensive, such as geoscience, engineering, economics, mathematics/computer science, and the physical sciences. In other scientific fields (psychology, life science, social science), women are found in much higher percentages. In this monograph, we undertake extensive life-course analyses comparing the trajectories of women and men in math-intensive fields with those of their counterparts in non-math-intensive fields in which women are close to parity with or even exceed the number of men. We begin by examining early-childhood differences in spatial processing and follow this through quantitative performance in middle childhood and adolescence, including high school coursework. We then focus on the transition of the sexes from high school to college major, then to graduate school, and, finally, to careers in academic science. The results of our myriad analyses reveal that early sex differences in spatial and mathematical reasoning need not stem from biological bases, that the gap between average female and male math ability is narrowing (suggesting strong environmental influences), and that sex differences in math ability at the right tail show variation over time and across nationalities, ethnicities, and other factors, indicating that the ratio of males to females at the right tail can and does change. We find that gender differences in attitudes toward and expectations about math careers and ability (controlling for actual ability) are evident by kindergarten and increase thereafter, leading to lower female propensities to major in math-intensive subjects in college but higher female propensities to major in non-math-intensive sciences, with overall science, technology, engineering, and mathematics (STEM) majors at 50% female for more than a decade. Post-college, although men with majors in math-intensive subjects have historically chosen and completed PhDs in these fields more often than women, the gap has recently narrowed by two thirds; among non-math-intensive STEM majors, women are more likely than men to go into health and other people-related occupations instead of pursuing PhDs. Importantly, of those who obtain doctorates in math-intensive fields, men and women entering the professoriate have equivalent access to tenure-track academic jobs in science, and they persist and are remunerated at comparable rates-with some caveats that we discuss. The transition from graduate programs to assistant professorships shows more pipeline leakage in the fields in which women are already very prevalent (psychology, life science, s...

National randomized experiments and validation studies were conducted on 873 tenure-track faculty (439 male, 434 female) from biology, engineering, economics, and psychology at 371 universities/colleges from 50 US states and the District of Columbia. In the main experiment, 363 faculty members evaluated narrative summaries describing hypothetical female and male applicants for tenure-track assistant professorships who shared the same lifestyle (e.g., single without children, married with children). Applicants' profiles were systematically varied to disguise identically rated scholarship; profiles were counterbalanced by gender across faculty to enable between-faculty comparisons of hiring preferences for identically qualified women versus men. Results revealed a 2:1 preference for women by faculty of both genders across both math-intensive and non-math-intensive fields, with the single exception of male economists, who showed no gender preference. Results were replicated using weighted analyses to control for national sample characteristics. In follow-up experiments, 144 faculty evaluated competing applicants with differing lifestyles (e.g., divorced mother vs. married father), and 204 faculty compared same-gender candidates with children, but differing in whether they took 1-y-parental leaves in graduate school. Women preferred divorced mothers to married fathers; men preferred mothers who took leaves to mothers who did not. In two validation studies, 35 engineering faculty provided rankings using full curricula vitae instead of narratives, and 127 faculty rated one applicant rather than choosing from a mixed-gender group; the same preference for women was shown by faculty of both genders. These results suggest it is a propitious time for women launching careers in academic science. Messages to the contrary may discourage women from applying for STEM (science, technology, engineering, mathematics) tenure-track assistant professorships.gender bias | hiring bias | underrepresentation of women | faculty hiring | women in science W omen considering careers in academic science confront stark portrayals of the treacherous journey to becoming professors. Well-publicized research depicts a thicket of obstacles standing between female graduate students and tenure-track positions, including inadequate mentoring and networking (1); a chilly social climate (2); downgrading of work products such as manuscripts (3), grant proposals (4), and lectures (5); and gender bias in interviewing and hiring (6-9). Numerous blue ribbon panels and national reports have concluded that implicit, and sometimes explicit, attitudes pervade the hiring process and negatively influence evaluations of female candidates and their scholarship, contributing to women's underrepresentation within the academy (e.g., refs. 10-13).Women's underrepresentation in academic science is hardly trivial. In life and social sciences, women now earn the majority of doctorates, but they make up a minority of assistant professors. In 1993In -1995.4% of assistant pr...

Predictors of success in school, such as conventional psychometric intelligence (e.g., IQ) tests, are less predictive of success out of school. Even the most charitable estimates of the relation between intelligence test scores and realworld criteria such as job performance indicate that approximately three fourths of the variance in real-world performance is not accounted for by intelligence test performance. Researchers have begun to explore new constructs in search of measures to supplement existing cognitive ability tests as predictors of real-world performance. Among the most promising constructs is practical intelligence, or common sense. Performance on measures of practical intelligence predicts real-world criteria such as job performance but is relatively unrelated to performance on intelligence tests and other common selection measures. Consequently, its contribution to prediction is largely independent of the-contributions of existing measures, including measures of cognitive ability.Editor's note. Joseph D. Matarazzo served as action editor for this article.

~o e word is out: The benefits of staying in school e pervasive. School attendance is associated with wer rates of teen pregnancy, welfare dependency, and criminality proneness, to name only a few of the myriad advantages of staying in school (Bronfenbrenner,

The authors consider the empirical validity of the Graduate Record Examination (GRE) as a predictor of various kinds of performance in a graduate psychology program, including 1st- and 2nd-year grades; professors' ratings of students' dissertations; and professors' ratings of students' analytical, creative, practical, research, and teaching abilities. On the basis of the triarchic theory of intelligence, the GRE was predicted to be of some use in predicting graduate grades but of limited or no use in predicting other aspects of performance. In fact, the test was found to be useful in predicting 1st-year grades but not other kinds of performance, with one exception--performance on the GRE Analytical test was predictive, but only for men. The authors conclude that there is a need to develop better theory-based tests.

Despite impressive employment gains in many fields of science, women remain underrepresented in fields requiring intensive use of mathematics. Here we discuss three potential explanations for women's underrepresentation: (a) male-female mathematical and spatial ability gaps, (b) sex discrimination, and (c) sex differences in career preferences and lifestyle choices. Synthesizing findings from psychology, endocrinology, sociology, economics, and education leads to the conclusion that, among a combination of interrelated factors, preferences and choices-both freely made and constrained-are the most significant cause of women's underrepresentation. Keywords sex differences; mathematic ability; spatial ability; discrimination; career aspirations Since 1970, there has been exponential growth in women's representation in scientific careers. Today, half of all MD degrees are earned by women, as are 48% to 52% of PhDs in life sciences and the majority of doctorates to new psychologists (71%) and veterinarians (77%). However, in the most mathematically intensive fields-engineering, physics, mathematics, chemistry, economics, and computer science-women's progress has been much less dramatic. In the top 100 U.S. universities, only 9% to 16% of tenure-track positions in math-intensive fields are occupied by women (Nelson & Brammer, 2010). Among full professors, women number around or fewer than 10%: computer science, 10.3%; chemistry, 9.7%;economics, 8.7%; chemical engineering, 7.3%; mathematics, 7.1%;civil engineering, 7.1%;electricalengineering, 5.7%;physics, 6.1%; and mechanical engineering, 4.4%. In contrast, women are much better represented in the rest of the sciences and humanities, often making up one third or more of professorial posts.Various explanations for the underrepresentation of women in math-intensive fields have been given. Here we review evidence for three: (a) sex differences in mathematical and spatial ability; (b) sex discrimination in publishing, funding, and hiring; and (c) occupational/lifestyle preferences and choices that reduce women's participation in mathintensive fields. The relevant data come from many areas of scholarship-endocrinology, economics, sociology, education, genetics, and psychology-and from different nations, age groups, and historical cohorts. (This evidence is reviewed in greater detail in