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Scientific prize network predicts who pushes the boundaries of science

Author

Listed:
  • Yifang Ma

    (Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208; Kellogg School of Management, Northwestern University, Evanston, IL 60208)

  • Brian Uzzi

    (Northwestern Institute on Complex Systems, Northwestern University, Evanston, IL 60208; Kellogg School of Management, Northwestern University, Evanston, IL 60208; McCormick School of Engineering, Northwestern University, Evanston, IL 60208)

Abstract

Scientific prizes confer credibility to persons, ideas, and disciplines, provide financial incentives, and promote community-building celebrations. We examine the growth dynamics and interlocking relationships found in the worldwide scientific prize network. We focus on understanding how the knowledge linkages among prizes and scientists’ propensities for prizewinning relate to knowledge pathways between disciplines and stratification within disciplines. Our data cover more than 3,000 different scientific prizes in diverse disciplines and the career histories of 10,455 prizewinners worldwide for over 100 years. We find several key links between prizes and scientific advances. First, despite an explosive proliferation of prizes over time and across the globe, prizes are more concentrated within a relatively small group of scientific elites, and ties among elites are highly clustered, suggesting that a relatively constrained number of ideas and scholars push the boundaries of science. For example, 64.1% of prizewinners have won two prizes and 13.7% have won five or more prizes. Second, certain prizes strongly interlock disciplines and subdisciplines, creating key pathways by which knowledge spreads and is recognized across science. Third, genealogical and coauthorship networks predict who wins multiple prizes, which helps to explain the interconnectedness among celebrated scientists and their pathbreaking ideas.

Suggested Citation

  • Yifang Ma & Brian Uzzi, 2018. "Scientific prize network predicts who pushes the boundaries of science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(50), pages 12608-12615, December.
    • Handle: RePEc:nas:journl:v:115:y:2018:p:12608-12615
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    Citations

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    Cited by:

    1. Alexey Lyutov & Yilmaz Uygun & Marc-Thorsten Hütt, 2021. "Machine learning misclassification of academic publications reveals non-trivial interdependencies of scientific disciplines," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1173-1186, February.
    2. Andrea Palmucci & Hao Liao & Andrea Napoletano & Andrea Zaccaria, 2020. "Where is your field going? A machine learning approach to study the relative motion of the domains of physics," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-16, June.
    3. Sha Yuan & Zhou Shao & Xingxing Wei & Jie Tang & Wendy Hall & Yongli Wang & Ying Wang & Ye Wang, 2020. "Science behind AI: the evolution of trend, mobility, and collaboration," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 993-1013, August.
    4. Zhu, Wanying & Jin, Ching & Ma, Yifang & Xu, Cong, 2023. "Earlier recognition of scientific excellence enhances future achievements and promotes persistence," Journal of Informetrics, Elsevier, vol. 17(2).
    5. Julián D. Cortés & Daniel A. Andrade, 2022. "Winners and runners-up alike?—a comparison between awardees and special mention recipients of the most reputable science award in Colombia via a composite citation indicator," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    6. Ho-Chun Herbert Chang & Feng Fu, 2021. "Elitism in mathematics and inequality," Palgrave Communications, Palgrave Macmillan, vol. 8(1), pages 1-8, December.
    7. Yinyu Jin & Sha Yuan & Zhou Shao & Wendy Hall & Jie Tang, 2021. "Turing Award elites revisited: patterns of productivity, collaboration, authorship and impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2329-2348, March.

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