Seeking Congruity Between Goals and Roles: A New Look at Why Women Opt Out of Science, Technology, Engineering, and Mathematics Careers

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Abstract

Although women have nearly attained equality with men in several formerly male-dominated fields, they remain underrepresented in the fields of science, technology, engineering, and mathematics (STEM). We argue that one important reason for this discrepancy is that STEM careers are perceived as less likely than careers in other fields to fulfill communal goals (e.g., working with or helping other people). Such perceptions might disproportionately affect women's career decisions, because women tend to endorse communal goals more than men. As predicted, we found that STEM careers, relative to other careers, were perceived to impede communal goals. Moreover, communal-goal endorsement negatively predicted interest in STEM careers, even when controlling for past experience and self-efficacy in science and mathematics. Understanding how communal goals influence people's interest in STEM fields thus provides a new perspective on the issue of women's representation in STEM careers.

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Recommended effect size statistics for repeated measures designs.

Roger Bakeman (2005)

Investigators, who are increasingly implored to present and discuss effect size statistics, might comply more often if they understood more clearly what is required. When investigators wish to report effect sizes derived from analyses of variance that include repeated measures, past advice has been problematic. Only recently has a generally useful effect size statistic been proposed for such designs: generalized eta squared (eta2G; Olejnik & Algina, 2003). Here, we present this method, explain that eta2G preferred to eta squared and partial eta squared because it provides comparability across between-subjects and within-subjects designs, show that it can easily be computed from information provided by standard statistical packages, and recommend that investigators provide it routinely in their research reports when appropriate.

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Sex differences in value priorities: cross-cultural and multimethod studies.

Shalom Schwartz, Tammy Rubel (2005)

The authors assess sex differences in the importance of 10 basic values as guiding principles. Findings from 127 samples in 70 countries (N = 77,528) reveal that men attribute consistently more importance than women do to power, stimulation, hedonism, achievement, and self-direction values; the reverse is true for benevolence and universalism values and less consistently for security values. The sexes do not differ on tradition and conformity values. Sex differences are small (median d = .15; maximum d = .32 [power]) and typically explain less variance than age and much less than culture. Culture moderates all sex differences and sample type and measurement instrument have minor influences. The authors discuss compatibility of findings with evolutionary psychology and sex role theory and propose an agenda for future research. Copyright 2006 APA, all rights reserved.

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The Science of Sex Differences in Science and Mathematics.

Diane F Halpern, Camilla P Benbow, David Geary … (2007)

Amid ongoing public speculation about the reasons for sex differences in careers in science and mathematics, we present a consensus statement that is based on the best available scientific evidence. Sex differences in science and math achievement and ability are smaller for the mid-range of the abilities distribution than they are for those with the highest levels of achievement and ability. Males are more variable on most measures of quantitative and visuospatial ability, which necessarily results in more males at both high- and low-ability extremes; the reasons why males are often more variable remain elusive. Successful careers in math and science require many types of cognitive abilities. Females tend to excel in verbal abilities, with large differences between females and males found when assessments include writing samples. High-level achievement in science and math requires the ability to communicate effectively and comprehend abstract ideas, so the female advantage in writing should be helpful in all academic domains. Males outperform females on most measures of visuospatial abilities, which have been implicated as contributing to sex differences on standardized exams in mathematics and science. An evolutionary account of sex differences in mathematics and science supports the conclusion that, although sex differences in math and science performance have not directly evolved, they could be indirectly related to differences in interests and specific brain and cognitive systems. We review the brain basis for sex differences in science and mathematics, describe consistent effects, and identify numerous possible correlates. Experience alters brain structures and functioning, so causal statements about brain differences and success in math and science are circular. A wide range of sociocultural forces contribute to sex differences in mathematics and science achievement and ability-including the effects of family, neighborhood, peer, and school influences; training and experience; and cultural practices. We conclude that early experience, biological factors, educational policy, and cultural context affect the number of women and men who pursue advanced study in science and math and that these effects add and interact in complex ways. There are no single or simple answers to the complex questions about sex differences in science and mathematics.