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The Diversity–Innovation Paradox in Science

Author

Listed:
  • Bas Hofstra

    (Graduate School of Education, Stanford University, Stanford, CA 94305)

  • Vivek V. Kulkarni

    (Department of Computer Science, Stanford University, Stanford, CA 94305)

  • Sebastian Munoz-Najar Galvez

    (Graduate School of Education, Stanford University, Stanford, CA 94305)

  • Bryan He

    (Department of Computer Science, Stanford University, Stanford, CA 94305)

  • Dan Jurafsky

    (Department of Computer Science, Stanford University, Stanford, CA 94305; Department of Linguistics, Stanford University, Stanford, CA 94305)

  • Daniel A. McFarland

    (Graduate School of Education, Stanford University, Stanford, CA 94305)

Abstract

Prior work finds a diversity paradox: Diversity breeds innovation, 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-complete population of ∼1.2 million US doctoral recipients from 1977 to 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: For example, 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.

Suggested Citation

  • Bas Hofstra & Vivek V. Kulkarni & Sebastian Munoz-Najar Galvez & Bryan He & Dan Jurafsky & Daniel A. McFarland, 2020. "The Diversity–Innovation Paradox in Science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(17), pages 9284-9291, April.
    • Handle: RePEc:nas:journl:v:117:y:2020:p:9284-9291
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    Citations

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    Cited by:

    1. Jayakumar , Uma, 2023. "On "Putting Lipstick on A Pig": Beware "Moderate" Critiques of DEI Statements Dressed as Concern for Academic Freedom," University of California at Berkeley, Center for Studies in Higher Education qt95g888hc, Center for Studies in Higher Education, UC Berkeley.
    2. Kim, Lanu & Smith, Daniel Scott & Hofstra, Bas & McFarland, Daniel A., 2022. "Gendered knowledge in fields and academic careers," Research Policy, Elsevier, vol. 51(1).
    3. Zhou, Sifan & Chai, Sen & Freeman, Richard B., 2024. "Gender homophily: In-group citation preferences and the gender disadvantage," Research Policy, Elsevier, vol. 53(1).
    4. Lin, Yiling & Evans, James A. & Wu, Lingfei, 2022. "New directions in science emerge from disconnection and discord," Journal of Informetrics, Elsevier, vol. 16(1).
    5. Cao, Dongqin & Peng, Can & Yang, Guanglei & Zhang, Wei, 2022. "How does the pressure of political promotion affect renewable energy technological innovation? Evidence from 30 Chinese provinces," Energy, Elsevier, vol. 254(PA).
    6. Martín de Diego, Isaac & González-Fernández, César & Fernández-Isabel, Alberto & Fernández, Rubén R. & Cabezas, Javier, 2021. "System for evaluating the reliability and novelty of medical scientific papers," Journal of Informetrics, Elsevier, vol. 15(4).
    7. McGuire, Erin & Rietveld, Anne M. & Crump, Amanda & Leeuwis, Cees, 2022. "Anticipating gender impacts in scaling innovations for agriculture: Insights from the literature," World Development Perspectives, Elsevier, vol. 25(C).
    8. Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
    9. Zhang, Ning & He, Guangye & Shi, Dongbo & Zhao, Zhenyue & Li, Jiang, 2022. "Does a gender-neutral name associate with the research impact of a scientist?," Journal of Informetrics, Elsevier, vol. 16(1).
    10. Nicole A. Cooke & Vanessa L. Kitzie, 2021. "Outsiders‐within‐Library and Information Science: Reprioritizing the marginalized in critical sociocultural work," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(10), pages 1285-1294, October.
    11. Nørskov, Sladjana & Damholdt, Malene F. & Ulhøi, John P. & Jensen, Morten Berg & Mathiasen, Mia Krogager & Ess, Charles M. & Seibt, Johanna, 2022. "Employers’ and applicants’ fairness perceptions in job interviews: using a teleoperated robot as a fair proxy," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    12. Yang, Alex J., 2024. "Unveiling the impact and dual innovation of funded research," Journal of Informetrics, Elsevier, vol. 18(1).
    13. Akbaritabar, Aliakbar & Stephen, Dimity & Squazzoni, Flaminio, 2022. "A study of referencing changes in preprint-publication pairs across multiple fields," Journal of Informetrics, Elsevier, vol. 16(2).

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