Gender productivity gap among star performers in STEM and other scientific fields.

We examined the gender productivity gap in science, technology, engineering, mathematics, and other scientific fields (i.e., applied psychology, mathematical psychology), specifically among star performers. Study 1 included 3,853 researchers who published 3,161 articles in mathematics. Study 2 included 45,007 researchers who published 7,746 articles in genetics. Study 3 included 4,081 researchers who published 2,807 articles in applied psychology and 6,337 researchers who published 3,796 articles in mathematical psychology. Results showed that (a) the power law with exponential cutoff is the best-fitting distribution of research productivity across fields and gender groups and (b) there is a considerable gender productivity gap among stars in favor of men across fields. Specifically, the underrepresentation of women is more extreme as we consider more elite ranges of performance (i.e., top 10%, 5%, and 1% of performers). Conceptually, results suggest that individuals vary in research productivity predominantly because of the generative mechanism of incremental differentiation, which is the mechanism that produces power laws with exponential cutoffs. Also, results suggest that incremental differentiation occurs to a greater degree among men and certain forms of discrimination may disproportionately constrain women's output increments. Practically, results suggest that women may have to accumulate more scientific knowledge, resources, and social capital to achieve the same level of increase in total outputs as their male counterparts. Finally, we offer recommendations on interventions aimed at reducing constraints for incremental differentiation among women that could be useful for narrowing the gender productivity gap specifically among star performers. (PsycINFO Database Record