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Intellectual synthesis in mentorship determines success in academic careers

Author

Listed:
  • Jean F. Liénard

    (Oregon Hearing Research Center, Oregon Health & Science University, Portland
    Okinawa Institute for Science and Technology, Onna-son)

  • Titipat Achakulvisut

    (University of Pennsylvania)

  • Daniel E. Acuna

    (School of Information Studies, Syracuse University)

  • Stephen V. David

    (Oregon Hearing Research Center, Oregon Health & Science University, Portland)

Abstract

As academic careers become more competitive, junior scientists need to understand the value that mentorship brings to their success in academia. Previous research has found that, unsurprisingly, successful mentors tend to train successful students. But what characteristics of this relationship predict success, and how? We analyzed an open-access database of 18,856 researchers who have undergone both graduate and postdoctoral training, compiled across several fields of biomedical science with an emphasis on neuroscience. Our results show that postdoctoral mentors were more instrumental to trainees’ success compared to graduate mentors. Trainees’ success in academia was also predicted by the degree of intellectual synthesis between their graduate and postdoctoral mentors. Researchers were more likely to succeed if they trained under mentors with disparate expertise and integrated that expertise into their own work. This pattern has held up over at least 40 years, despite fluctuations in the number of students and availability of independent research positions.

Suggested Citation

  • Jean F. Liénard & Titipat Achakulvisut & Daniel E. Acuna & Stephen V. David, 2018. "Intellectual synthesis in mentorship determines success in academic careers," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-07034-y
    DOI: 10.1038/s41467-018-07034-y
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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. 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).
    4. Li Hou & Qiang Wu & Yundong Xie, 2022. "Does early publishing in top journals really predict long-term scientific success in the business field?," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(11), pages 6083-6107, November.
    5. Sofia Patsali & Michele Pezzoni & Fabiana Visentin, 2021. "The Impact of Research Independence on PhD Students' Careers: Large-scale Evidence from France," GREDEG Working Papers 2021-35, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    6. Shibayama, Sotaro, 2019. "Sustainable development of science and scientists: Academic training in life science labs," Research Policy, Elsevier, vol. 48(3), pages 676-692.
    7. Corsini, Alberto & Pezzoni, Michele & Visentin, Fabiana, 2022. "What makes a productive Ph.D. student?," Research Policy, Elsevier, vol. 51(10).
    8. Batista-Jr, Antônio de Abreu & Gouveia, Fábio Castro & Mena-Chalco, Jesús P., 2021. "Predicting the Q of junior researchers using data from the first years of publication," Journal of Informetrics, Elsevier, vol. 15(2).
    9. Liang, Zhentao & Ba, Zhichao & Mao, Jin & Li, Gang, 2023. "Research complexity increases with scientists’ academic age: Evidence from library and information science," Journal of Informetrics, Elsevier, vol. 17(1).
    10. Aliakbar Akbaritabar & Andrés F. Castro Torres & Vincent Larivière, 2023. "A global perspective on the social structure of science," MPIDR Working Papers WP-2023-029, Max Planck Institute for Demographic Research, Rostock, Germany.
    11. Mignon Wuestman & Koen Frenken & Iris Wanzenböck, 2020. "A genealogical approach to academic success," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-16, December.
    12. 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.

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