“…The current underrepresentation of women in senior scientific positions will not be solved without proactive policies (Holman et al 2018;Grogan 2019). Pursuing potential factors driving biases (e.g., explicit, implicit, structural) that diminish evaluations of women's scientific work is necessary to achieve equity.…”
Women in science, technology, engineering, and math are not equally represented across tenure-track career stages, and this extends to grant funding, where women applicants often have lower success rates compared with men. While gender bias in reviewers has been documented, it is currently unknown whether written language in grant applications varies predictably with gender to elicit bias against women. Here we analyse the text of ∼2000 public research summaries from the 2016 Natural Sciences and Engineering Research Council (NSERC) individual Discovery Grant (DG) program. We explore the relationship between language variables, inferred gender and career stage, and funding levels. We also analyse aggregated data from the 2012–2018 NSERC DG competitions to determine whether gender impacted the probability of receiving a grant for early-career researchers. We document a marginally significant gender difference in funding levels for successful grants, with women receiving $1756 less than men, and a large and significant difference in rejection rates among early-career applicants (women: 40.4% rejection; men: 33.0% rejection rate). Language variables had little ability to predict gender or funding level using predictive modelling. Our results indicate that NSERC funding levels and success rates differ between men and women, but we find no evidence that gendered language use affected funding outcomes.
“…The current underrepresentation of women in senior scientific positions will not be solved without proactive policies (Holman et al 2018;Grogan 2019). Pursuing potential factors driving biases (e.g., explicit, implicit, structural) that diminish evaluations of women's scientific work is necessary to achieve equity.…”
Women in science, technology, engineering, and math are not equally represented across tenure-track career stages, and this extends to grant funding, where women applicants often have lower success rates compared with men. While gender bias in reviewers has been documented, it is currently unknown whether written language in grant applications varies predictably with gender to elicit bias against women. Here we analyse the text of ∼2000 public research summaries from the 2016 Natural Sciences and Engineering Research Council (NSERC) individual Discovery Grant (DG) program. We explore the relationship between language variables, inferred gender and career stage, and funding levels. We also analyse aggregated data from the 2012–2018 NSERC DG competitions to determine whether gender impacted the probability of receiving a grant for early-career researchers. We document a marginally significant gender difference in funding levels for successful grants, with women receiving $1756 less than men, and a large and significant difference in rejection rates among early-career applicants (women: 40.4% rejection; men: 33.0% rejection rate). Language variables had little ability to predict gender or funding level using predictive modelling. Our results indicate that NSERC funding levels and success rates differ between men and women, but we find no evidence that gendered language use affected funding outcomes.
“…In order to address serious issues and problems, the first key step is to admit they exist. The data regarding gender inequities in science are simply incontrovertible (Grogan, ). Once the problem is identified, the next step is transparency—an open dialogue, where arguments are aired and the facts are embraced.…”
“…Yet despite much effort to understand the underlying causes (summarised in Fig. 1 of 21 ), disparities between the genders show discouragingly few signs of reducing 8,9,13,22–25 . Given these obstacles to career attainment and progression, what lessons can we learn from scientists that have survived in science and carved out long careers for themselves?…”
Intense competition for limited opportunities means the career path of a scientist is a challenging one, and female scientists in particular are less likely to survive in academia. Collaboration is a key factor in scientific advances, and in social species enhanced sociality improves fitness and longevity. Yet whether sociality influences career progression and survival in science, and how this might differ between genders, is largely unknown. We built authorship social networks from publication records to test how sociality predicts career progression and survival in a cohort of biologists contributing to three international conferences in the 1990s. We show that sociality has the strongest effect for female researchers but, regardless of gender, publishing with many diverse co-authors significantly reduces time to become a principal investigator and increases career duration. Publishing repeatedly with co-authors also enhances career progression in both genders, but reduces career length for men. These findings demonstrate that the value of collaboration extends beyond scientific advances, and can directly benefit the career progression and longevity of research scientists themselves. Efforts to encourage researchers at all levels to invest in collaborations, particularly with female researchers, will help to close the gender gap in science and academia.
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