Exploring Gender Bias in Six Key Domains of Academic Science: An Adversarial Collaboration

Abstract

We synthesized the vast, contradictory scholarly literature on gender bias in academic science from 2000 to 2020. In the most prestigious journals and media outlets, which influence many people’s opinions about sexism, bias is frequently portrayed as an omnipresent factor limiting women’s progress in the tenure-track academy. Claims and counterclaims regarding the presence or absence of sexism span a range of evaluation contexts. Our approach relied on a combination of meta-analysis and analytic dissection. We evaluated the empirical evidence for gender bias in six key contexts in the tenure-track academy: (a) tenure-track hiring, (b) grant funding, (c) teaching ratings, (d) journal acceptances, (e) salaries, and (f) recommendation letters. We also explored the gender gap in a seventh area, journal productivity, because it can moderate bias in other contexts. We focused on these specific domains, in which sexism has most often been alleged to be pervasive, because they represent important types of evaluation, and the extensive research corpus within these domains provides sufficient quantitative data for comprehensive analysis. Contrary to the omnipresent claims of sexism in these domains appearing in top journals and the media, our findings show that tenure-track women are at parity with tenure-track men in three domains (grant funding, journal acceptances, and recommendation letters) and are advantaged over men in a fourth domain (hiring). For teaching ratings and salaries, we found evidence of bias against women; although gender gaps in salary were much smaller than often claimed, they were nevertheless concerning. Even in the four domains in which we failed to find evidence of sexism disadvantaging women, we nevertheless acknowledge that broad societal structural factors may still impede women’s advancement in academic science. Given the substantial resources directed toward reducing gender bias in academic science, it is imperative to develop a clear understanding of when and where such efforts are justified and of how resources can best be directed to mitigate sexism when and where it exists.

Masculine Defaults in Academic Science, Technology, Engineering, and Mathematics (STEM) Fields

“…If, as we suggest, masculine defaults that disadvantage women are present in academic STEM fields, why would Ceci et al (2023) find no or minimal evidence of discrimination against women in several domains within academic STEM fields (e.g., faculty hiring, funding decisions)? First, even domains with no ostensible gender discrimination may still have gender disparities in outcomes as a result of masculine defaults.…”

“…Many academic STEM fields still lack equal participation by women (National Science Foundation, 2021). First, there are areas within STEM where issues of differential treatment remain and women are disadvantaged relative to men (e.g., salary, teaching evaluations; Ceci et al, 2023). These inequalities still need to be addressed.…”

“…For example, women may not have a lower likelihood than men of being given a tenure-track offer once they are in the hiring pool, but masculine defaults, such as job ads that favor stereotypically masculine characteristics (e.g., competitiveness), may prevent women from entering these pools in the first place (Gaucher et al, 2011). Indeed, Ceci et al (2023) offer evidence that women PhDs are less likely than men PhDs to apply for tenure-track positions, resulting in a lower proportion of women entering these positions. Second, many of the studies that Ceci et al (2023) reviewed may have null effects because they controlled for effects of masculine defaults.…”

“…Indeed, Ceci et al (2023) offer evidence that women PhDs are less likely than men PhDs to apply for tenure-track positions, resulting in a lower proportion of women entering these positions. Second, many of the studies that Ceci et al (2023) reviewed may have null effects because they controlled for effects of masculine defaults. For example, Ceci et al (2023) found no gender bias or bias favoring women in grant funding.…”

“…Second, many of the studies that Ceci et al (2023) reviewed may have null effects because they controlled for effects of masculine defaults. For example, Ceci et al (2023) found no gender bias or bias favoring women in grant funding. However, some studies controlled for productivity, operationalized as number of publications.…”