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Background: Female scientists, who are more likely than their male counterparts to study women and report findings by sex/gender, fare worse in the article peer review process. It is unknown whether the gender of research participants influences the recommendation to publish an article describing the study. Materials and Methods: Reviewers were randomly assigned to evaluate one of three versions of an article abstract describing a clinical study conducted in men, women, or individuals. Reviewers assessed the study's scientific rigor, its level of contribution to medical science, and whether they would recommend publishing the full article. Responses were analyzed with logistic regression controlling for reviewer background variables, including sex and experience level. Results: There was no significant difference in perceived research rigor by abstract condition; contribution to medical science was perceived to be greater for research conducted in women than men (odds ratio = 1.7; p = 0.030). Nevertheless, reviewers were almost twice as likely to recommend publication for research conducted in men than the same research conducted in women (predicted probability 0.606 vs. 0.322; p = 0.000). Conclusions: These results are consistent with abundant data from multiple sources showing a lower societal value placed on women than men. Because female investigators are more likely than male investigators to study women, our findings suggest a previously unrecognized bias that could contribute to gender asymmetries in the publication outcomes of peer review. This pro-male publication bias could be an additional barrier to leadership attainment for women in academic medicine and the advancement of women's health.

Women are less successful than men in renewing R01 grants from the National Institutes of Health. Continuing to probe text mining as a tool to identify gender bias in peer review, we used algorithmic text mining and qualitative analysis to examine a sample of critiques from men's and women's R01 renewal applications previously analyzed by counting and comparing word categories.We analyzed 241 critiques from 79 Summary Statements for 51 R01 renewals awarded to 45 investigators (64% male, 89% white, 80% PhD) at the University of Wisconsin-Madison between 2010 and 2014. We used latent Dirichlet allocation to discover evaluative "topics" (i.e., words that co-occur with high probability). We then qualitatively examined the context in which evaluative words occurred for male and female investigators. We also examined sex differences in assigned scores controlling for investigator productivity.Text analysis results showed that male investigators were described as "leaders" and "pioneers" in their "fields," with "highly innovative" and "highly significant research." By comparison, female investigators were characterized as having "expertise" and working in "excellent" environments. Applications from men received significantly better priority, approach, and significance scores, which could not be accounted for by differences in productivity.Results confirm our previous analyses suggesting that gender stereotypes operate in R01 grant peer review. Reviewers may more easily view male than female investigators as scientific leaders with significant and innovative research, and score their applications more competitively. Such implicit bias may contribute to sex differences in award rates for R01 renewals.

Many studies find that female faculty in academic medicine, science, and engineering experience adverse workplace climates. This study longitudinally investigates whether department climate is associated with future research productivity and whether the associations are stronger for female than male faculty.Two waves of a faculty climate survey, institutional grant records, and publication records were collected for 789 faculties in academic medicine, science, and engineering at the University of Wisconsin-Madison between 2000 and 2010. Research productivity was measured as Number of Publications and Number of Grants awarded, and department climate was measured with scales for professional interactions, department decision-making practices, climate for underrepresented groups, and work/life balance. Ordinary least squares and negative binomial regression methods were used to assess gender differences in productivity, influences of department climate on productivity, and gender differences in effects of climate on productivity.Female faculty published fewer articles and were awarded fewer grants in the baseline period, but their productivity did not differ from male faculty on these measures in subsequent years. Number of Publications was positively affected by professional interactions, but negatively affected by positive work/life balance. Number of Grants awarded was positively affected by climate for underrepresented groups. These main effects did not differ by gender; however, some three-way interactions illuminated how different aspects of department climate affected productivity differently for men and women in specific situations.In perhaps the first study to assess the longitudinal impact of department climate on faculty research productivity, positive department climate is associated with significantly greater productivity for all faculty-women and men. However, some positive aspects of climate (specifically, work/life balance) may be associated with lower productivity for some female faculty at specific career periods. These findings suggest that departments that wish to increase grants and publications would be wise to foster a positive workplace climate.

Prior text analysis of R01 critiques suggested that female applicants may be disadvantaged in National Institutes of Health (NIH) peer review, particularly for renewals. NIH altered its review format in 2009. The authors examined R01 critiques and scoring in the new format for differences due to principal investigator (PI) sex.The authors analyzed 739 critiques-268 from 88 unfunded and 471 from 153 funded applications for grants awarded to 125 PIs (76 males, 49 females) at the University of Wisconsin-Madison between 2010 and 2014. The authors used seven word categories for text analysis: ability, achievement, agentic, negative evaluation, positive evaluation, research, and standout adjectives. The authors used regression models to compare priority and criteria scores, and results from text analysis for differences due to PI sex and whether the application was for a new (Type 1) or renewal (Type 2) R01.Approach scores predicted priority scores for all PIs' applications (P.001), but scores and critiques differed significantly for male and female PIs' Type 2 applications. Reviewers assigned significantly worse priority, approach, and significance scores to female than male PIs' Type 2 applications, despite using standout adjectives (e.g., "outstanding," "excellent") and making references to ability in more critiques (P.05 for all comparisons).The authors' analyses suggest that subtle gender bias may continue to operate in the post-2009 NIH review format in ways that could lead reviewers to implicitly hold male and female applicants to different standards of evaluation, particularly for R01 renewals.

Network analysis has widespread applications for studying many social phenomena. Our research is focused on investigating why highly qualified women and racial/ethnic minorities tend to fare worse in peer review processes, such as for scientific grants, which limits their participation in research careers. Our prior work shows that gender and racial bias can be detected in reviewers' narrative critiques, but our work has yet to harness the power of varied learning algorithms for text analysis. To this end, we show preliminary evidence of the usefulness of network algorithms to study reviewers' written critiques of grant applications submitted to the U.S. National Institutes of Health (NIH). We construct word co-occurrence networks and show that network measures vary by applicant sex.

To help prepare future faculty in science, technology, engineering, and mathematics fields to teach undergraduates, more research universities are offering teaching development (TD) programs to doctoral students who aspire to academic careers. This study found that participation in TD programs is positively associated with college teaching self-efficacy., To help prepare future faculty in science, technology, engineering, and mathematics (STEM) to teach undergraduates, more research universities are offering teaching development (TD) programs to doctoral students who aspire to academic careers. Using social cognitive career theory, we examine the effects of TD programs on early-career STEM scholars’ sense of self-efficacy as postsecondary teachers. In 2011, a survey questionnaire was administered to 2156 people who in 2009 were doctoral students in STEM departments at three U.S. research universities; 1445 responded (67%). Regression analysis revealed positive relationships between TD participation and participants’ college teaching self-efficacy and positive interaction effects for women. These findings may be used to improve the quality and quantity of TD offerings and help them gain wider acceptance.