Is science still an old boys' network? A structural approach for assessing patterns of gender heterophily in a large research network

Jessica Thein^1*Karen Skinner¹Sara Malone²Mia T Vogel¹Bobbi Carothers¹Todd Combs¹Douglas A Luke¹

• ¹Brown School, Washington University in St. Louis, St. Louis, United States
• ²Division of Public Health Sciences, Department of Surgery, School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States

Abstract Modern social and health sciences are inherently collaborative through team science, scientific collaboration between at least two people with an interdependent relationship. Despite evidence supporting the case for team science, some groups experience limited collaborative opportunities. In 2006 the National Institutes of Health's Clinical and Translational Science Awards (CTSA) established programs with a goal of promoting translational science by facilitating collaborative research among diverse, multidisciplinary teams. We take advantage of 15 years of collaboration data from members of the Washington University CTSA, the Institute of Clinical and Translational Sciences (ICTS). We describe 1) characteristics of ICTS researchers and their collaboration networks, 2) differences in network positions by gender (male/female), 3) patterns of scientific collaboration by gender across 15 years, and 4) develop a multivariate statistical network model that identifies predictors of collaboration, including gender. We combined descriptive analyses with social network analysis (SNA) to describe collaboration patterns by gender of co-authorship networks across years. We also built statistical network models of collaboration ties (using exponential random graph models) to explore how gender homophily influences co-authorship collaboration. We found gender differences in productivity, number of collaborators, and researcher characteristics. The number of publications and collaborators were higher among males than females. Females were more represented in allied health and social sciences, while males were concentrated in clinical and basic sciences, with very few males in allied health. Females were more represented in lower academic ranks and less in higher ranks, whereas males were more represented in higher ranks and less in lower ranks. The ERGM results indicated collaboration was more likely in clinical and social science disciplines and at higher academic ranks. These differences are reflected in the ERGM results for the homophily terms, which showed collaboration was less likely when involving a female researcher compared to male-male collaborations. By pairing SNA with descriptive methodologies and statistical modeling, we gained a nuanced understanding complex interactions within a scientific collaboration network, providing insights into how relationships and collaboration patterns evolve, especially with respect to gender. This methodological approach offers a valuable framework for exploring similar questions in other contexts.