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The role of mentorship in protégé performance

Author

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  • R. Dean Malmgren

    (Northwestern University, Evanston, Illinois 60208, USA
    Datascope Analytics, Evanston, Illinois 60201, USA)

  • Julio M. Ottino

    (Northwestern University, Evanston, Illinois 60208, USA
    Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois 60208, USA)

  • Luís A. Nunes Amaral

    (Northwestern University, Evanston, Illinois 60208, USA
    Northwestern Institute on Complex Systems, Northwestern University, Evanston, Illinois 60208, USA
    Howard Hughes Medical Institute, Northwestern University, Evanston, Illinois 60208, USA)

Abstract

Mathematical mentors: leading by example It is clear that mentors, in academia and elsewhere, influence the future success of their protégés, but it is unclear to what extent they influence future mentorship skills and career choices of their protégés. The records of the Mathematics Genealogy Project, which track the careers of 114,666 mathematicians since 1637, provide a data set with sufficient detail for those questions to be addressed. Malmgren et al. determine that career success of academic mathematicians was correlated with how many protégés they mentored, and the protégés of mentors with small trainee pools went on to have significantly larger than expected mentorship pools themselves.

Suggested Citation

  • R. Dean Malmgren & Julio M. Ottino & Luís A. Nunes Amaral, 2010. "The role of mentorship in protégé performance," Nature, Nature, vol. 465(7298), pages 622-626, June.
    • Handle: RePEc:nat:nature:v:465:y:2010:i:7298:d:10.1038_nature09040
    DOI: 10.1038/nature09040
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    Cited by:

    1. Lu, Wei & Ren, Yan & Huang, Yong & Bu, Yi & Zhang, Yuehan, 2021. "Scientific collaboration and career stages: An ego-centric perspective," Journal of Informetrics, Elsevier, vol. 15(4).
    2. Dhananjay Kumar & Plaban Kumar Bhowmick & Sumana Dey & Debarshi Kumar Sanyal, 2023. "On the banks of Shodhganga: analysis of the academic genealogy graph of an Indian ETD repository," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 3879-3914, July.
    3. Chaocheng He & Jiang Wu & Qingpeng Zhang, 2022. "Proximity‐aware research leadership recommendation in research collaboration via deep neural networks," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 73(1), pages 70-89, January.
    4. Rocío Deanna & Bethann Garramon Merkle & Kwok Pan Chun & Deborah Navarro-Rosenblatt & Ivan Baxter & Nora Oleas & Alejandro Bortolus & Patricia Geesink & Luisa Diele-Viegas & Valeria Aschero & María Jo, 2022. "Community voices: the importance of diverse networks in academic mentoring," Nature Communications, Nature, vol. 13(1), pages 1-7, December.
    5. Weihua Li & Sam Zhang & Zhiming Zheng & Skyler J. Cranmer & Aaron Clauset, 2022. "Untangling the network effects of productivity and prominence among scientists," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    6. Klebel, Thomas & Traag, Vincent, 2024. "Introduction to causality in science studies," SocArXiv 4bw9e, Center for Open Science.
    7. Yun Liu & Mengya Zhang & Gupeng Zhang & Xiongxiong You, 2022. "Scientific elites versus other scientists: who are better at taking advantage of the research collaboration network?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3145-3166, June.
    8. Lu Liu & Benjamin F. Jones & Brian Uzzi & Dashun Wang, 2023. "Data, measurement and empirical methods in the science of science," Nature Human Behaviour, Nature, vol. 7(7), pages 1046-1058, July.

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