title: Women's underrepresentation in science: sociocultural and biological considerations.
abstract: 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.
authors.affiliation: Department of Human Development, Cornell University, Ithaca, NY 14853, USA. sjc9@cornell.edu
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Ceci
authors.forename: Wendy M
authors.initials: WM
authors.lastname: Williams
authors.forename: Susan M
authors.initials: SM
authors.lastname: Barnett
mesh_terms: D000328:Adult; D001076:Aptitude; D001921:Brain / Q000502:physiology; D002321:Career Choice; D002648:Child; D002668:Child Rearing / Q000523:psychology; D004738:Engineering / Q000193:education; D005260:Female; D006801:Humans; D008019:Life Style; D008433:Mathematics; D011287:Prejudice; D012586:Science / Q000193:education; D012727:Sex Characteristics; D012945:Social Values; D013672:Technology / Q000193:education; D014930:Women / Q000193:education / Q000523:psychology; D000078329:Workforce