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The Diversity-Innovation Paradox in Science

arXiv 1909.02063 ↗First posted 4 Sep 2019cs.SI cs.CL stat.APcited by 21

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Abstract (arXiv)

Prior work finds a diversity paradox: diversity breeds innovation, and yet, underrepresented groups that diversify organizations have less successful careers within them. Does the diversity paradox hold for scientists as well? We study this by utilizing a near-population of ~1.2 million US doctoral recipients from 1977-2015 and following their careers into publishing and faculty positions. We use text analysis and machine learning to answer a series of questions: How do we detect scientific innovations? Are underrepresented groups more likely to generate scientific innovations? And are the innovations of underrepresented groups adopted and rewarded? Our analyses show that underrepresented groups produce higher rates of scientific novelty. However, their novel contributions are devalued and discounted: e.g., novel contributions by gender and racial minorities are taken up by other scholars at lower rates than novel contributions by gender and racial majorities, and equally impactful contributions of gender and racial minorities are less likely to result in successful scientific careers than for majority groups. These results suggest there may be unwarranted reproduction of stratification in academic careers that discounts diversity's role in innovation and partly explains the underrepresentation of some groups in academia.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Sep 2019.

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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 7; 2025: 6; 2026: 4.

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  1. 2024OpenReviewer: A Specialized Large Language Model for Generating Critical Scientific Paper Reviewscited by 63
  2. 2024What Can Natural Language Processing Do for Peer Review?cited by 24
  3. 2021When Fair Ranking Meets Uncertain Inferencecited by 22
  4. 2022Words as Gatekeepers: Measuring Discipline-specific Terms and Meanings in Scholarly Publicationscited by 14
  5. 2025A review on the novelty measurements of academic paperscited by 12
  6. 2023PubGraph: A Large-Scale Scientific Knowledge Graphcited by 6
  7. 2024Navigating the Landscape of Hint Generation Research: From the Past to the Futurecited by 6
  8. 2025Harnessing Large Language Models for Scientific Novelty Detectioncited by 5
  9. 2025AI-Driven Automation Can Become the Foundation of Next-Era Science of Science Researchcited by 3
  10. 2024AI Can Enhance Creativity in Social Networkscited by 2
  11. 2025Mapping the Evolution of Research Contributions using KnoVocited by 2
  12. 2026AI Research Agents Narrow Scientific Explorationcited by 2
9 more
  1. 2021Identifying Causal Influences on Publication Trends and Behavior: A Case Study of the Computational Linguistics Communitycited by 1
  2. 2025Identifying Emerging Concepts in Large Corporacited by 1
  3. 2026The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safetycited by 1
  4. 2024A Moonshot for AI Oracles in the Sciencescited by 0
  5. 2024Decoding Digital Influence: The Role of Social Media Behavior in Scientific Stratification Through Logistic Attribution Methodcited by 0
  6. 2024Causal Effect of Group Diversity on Redundancy and Coverage in Peer-Reviewingcited by 0
  7. 2025Big Data and the Computational Social Science of Entrepreneurship and Innovationcited by 0
  8. 2026Where Do Your Citations Come From? Citation-Constellation: A Free, Open-Source, No-Code, and Auditable Tool for Citation Network Decomposition with Complementary BARON and HEROCON Scorescited by 0
  9. 2026Discovery by Dreaming: Cross-Domain Recombination in Artificial Memorycited by 0