The Effect of Gender Diversity on Scientific Team Impact: A Team Roles Perspective

2025-12-29

AI Summary

This study investigates the differential effects of gender diversity in leadership versus support roles within scientific teams on five-year citation counts. Drawing on over 130,000 PLOS publications and their CRediT author contribution statements, we apply contribution semantic parsing, multivariate regression, and threshold regression models—first disentangling diversity effects through the lens of functional role differentiation. Results reveal inverted-U relationships for both leadership- and support-role diversity. Team size significantly moderates the leadership-diversity effect: negative and significant in small teams, but negligible in large teams; support-role diversity consistently exhibits a positive, significant association with citations. Notably, teams with all-female leadership and all-male support roles achieve the highest citation performance. Moving beyond aggregate diversity metrics, this work uncovers role-specific mechanisms, offering empirical guidance for optimizing research team composition.

Technology Category

• Humans and AI: Teamwork, Team formation
• Application Domains: Humanities & Computational Social Science
• Reasoning under Uncertainty: Causality

Application Category

• Web Mining and Content Analysis: Interdisciplinary science discovery with web data mining
• Security and Privacy: Data transparency and provenance
• Semantics and Knowledge: Methods to enhance, augment, integrate or synergize semantic models such as knowledge graphs and LLMs

Abstract

The influence of gender diversity on the success of scientific teams is of great interest to academia. However, prior findings remain inconsistent, and most studies operationalize diversity in aggregate terms, overlooking internal role differentiation. This limitation obscures a more nuanced understanding of how gender diversity shapes team impact. In particular, the effect of gender diversity across different team roles remains poorly understood. To this end, we define a scientific team as all coauthors of a paper and measure team impact through five-year citation counts. Using author contribution statements, we classified members into leadership and support roles. Drawing on more than 130,000 papers from PLOS journals, most of which are in biomedical-related disciplines, we employed multivariable regression to examine the association between gender diversity in these roles and team impact. Furthermore, we apply a threshold regression model to investigate how team size moderates this relationship. The results show that (1) the relationship between gender diversity and team impact follows an inverted U-shape for both leadership and support groups; (2) teams with an all-female leadership group and an all-male support group achieve higher impact than other team types. Interestingly, (3) the effect of leadership-group gender diversity is significantly negative for small teams but becomes positive and statistically insignificant in large teams. In contrast, the estimates for support-group gender diversity remain significant and positive, regardless of team size.

Problem

• Examines gender diversity's effect on scientific team impact
• Investigates role differentiation within teams using contribution statements
• Analyzes how team size moderates gender diversity's influence

Innovation

• Classified team roles using author contribution statements
• Applied multivariable regression on 130,000+ PLOS papers
• Used threshold regression to analyze team size moderation