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Race to the Big Lab: Gender Disparities in Large Team Collaboration and Its Impact on Early Academic Careers
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Informatics and Media. Aalto Univ, Dept Comp Sci, Espoo, Finland..
Aalto Univ, Comp Sci, Espoo, Finland..
2026 (English)In: Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems, CHI 2026, Association for Computing Machinery (ACM), 2026, article id 681Conference paper, Published paper (Refereed)
Abstract [en]

This study investigates the role of large-team collaboration in shaping early-career scholars' career development, with a focus on gender disparities. Using publication and collaboration data from SciSciNet in Computer Science, we capture the social capital accumulation process in academia with a neighborhood-based centrality metric and publication counts. Synthetic difference-in-differences (SDID) is applied to estimate the impact of early experience in large-team collaboration on subsequent research careers. Results indicate that junior scholars participating in large-team research significantly improve their network centrality, indicating more frequent collaborations with influential scholars, and produce approximately 0.75 more publications per year. Meanwhile, we document persistent gender gaps: men are 16% more likely to access large-team collaborations. These findings highlight large-team collaboration as both a source of career acceleration and a mechanism of gender inequality. We conclude with implications for equity promotion and strategies enabling more inclusive collaboration.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2026. article id 681
Keywords [en]
Team Science, Large Team Collaboration, Social Capital, Early-Career Scholars, Gender Disparities, Scientific Capital, Collaboration Network, Co-Author Network, Network Analysis, Causal Inference, Scientometrics, Network Centrality, Synthetic Difference-in-Differences, Survival Analysis
National Category
Business Administration
Identifiers
URN: urn:nbn:se:uu:diva-595090DOI: 10.1145/3772318.3791205ISI: 001795712700068Scopus ID: 2-s2.0-105038712682ISBN: 979-8-4007-2278-3 (print)OAI: oai:DiVA.org:uu-595090DiVA, id: diva2:2092120
Conference
2026 Conference on Human Factors in Computing Systems-CHI, April 13-17, 2026, Barcelona, Spain
Available from: 2026-08-13 Created: 2026-08-13 Last updated: 2026-08-13Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
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Language
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  • en-GB
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More languages
Output format
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