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Quantifying the dynamics of research teams' academic diversity

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  • Alex J. Yang
  • Star X. Zhao
  • Sanhong Deng
  • Meijun Liu
  • Yi Bu
  • Ying Ding

Abstract

The growing complexity of modern scientific challenges demands research teams that integrate diverse perspectives, yet the role of academic status diversity—variation in team members' scholarly achievements—remains insufficiently understood. This study aims to bridge this gap by examining the dynamics of academic diversity within research teams and its association with innovation, analyzing more than 17 million articles across 292 fields. We introduce new metrics—academic entropy, academic standard deviation, and academic disparity—to capture the heterogeneity of team members' academic backgrounds. Using a network null model to account for temporal and disciplinary differences, we uncover significant increases in academic diversity, particularly within STEM fields and developed regions, where diversity levels are notably overrepresented. While we find a positive correlation between academic diversity and interdisciplinarity, higher diversity is associated with lower levels of scientific disruption. Teams with greater academic diversity tend to be associated with consolidating existing knowledge rather than producing disruptive innovations that challenge prevailing frameworks. This trend is especially evident in larger teams, where diversity is linked to incremental progress rather than transformative breakthroughs. These findings underscore the need for a balanced approach to promoting diversity in relation to scientific advancement.

Suggested Citation

  • Alex J. Yang & Star X. Zhao & Sanhong Deng & Meijun Liu & Yi Bu & Ying Ding, 2025. "Quantifying the dynamics of research teams' academic diversity," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 76(12), pages 1719-1735, December.
  • Handle: RePEc:bla:jinfst:v:76:y:2025:i:12:p:1719-1735
    DOI: 10.1002/asi.70023
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    Cited by:

    1. Alex J. Yang & Star X. Zhao & Sanhong Deng, 2025. "Standing on the shoulder of data: data-driven research boosts scientific innovation," Scientometrics, Springer;Akadémiai Kiadó, vol. 130(10), pages 5613-5640, October.

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