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Identification of successful mentoring communities using network-based analysis of mentor–mentee relationships across Nobel laureates

Author

Listed:
  • Julia H. Chariker

    (University of Louisville
    University of Louisville)

  • Yihang Zhang

    (University of Louisville)

  • John R. Pani

    (University of Louisville)

  • Eric C. Rouchka

    (University of Louisville
    University of Louisville)

Abstract

Skills underlying scientific innovation and discovery generally develop within an academic community, often beginning with a graduate mentor’s laboratory. In this paper, a network analysis of doctoral student-dissertation advisor relationships in The Academic Family Tree indicates the pattern of Nobel laureate mentoring relationships is non-random. Nobel laureates had a greater number of Nobel laureate ancestors, descendants, mentees/grandmentees, and local academic family, supporting the notion that assortative processes occur in the selection of mentors and mentees. Subnetworks composed entirely of Nobel laureates extended across as many as four generations. Several successful mentoring communities in high-level science were identified, as measured by number of Nobel laureates within the community. These communities centered on Cambridge University in the latter nineteenth century and Columbia University in the early twentieth century. The current practice of building web-based academic networks, extended to include a wider variety of measures of academic success, would allow for the identification of modern successful scientific communities and should be promoted.

Suggested Citation

  • Julia H. Chariker & Yihang Zhang & John R. Pani & Eric C. Rouchka, 2017. "Identification of successful mentoring communities using network-based analysis of mentor–mentee relationships across Nobel laureates," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1733-1749, June.
  • Handle: RePEc:spr:scient:v:111:y:2017:i:3:d:10.1007_s11192-017-2364-4
    DOI: 10.1007/s11192-017-2364-4
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    References listed on IDEAS

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    1. Barabási, A.L & Jeong, H & Néda, Z & Ravasz, E & Schubert, A & Vicsek, T, 2002. "Evolution of the social network of scientific collaborations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 311(3), pages 590-614.
    2. Stephen V David & Benjamin Y Hayden, 2012. "Neurotree: A Collaborative, Graphical Database of the Academic Genealogy of Neuroscience," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-12, October.
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    Cited by:

    1. Thomas Heinze & Arlette Jappe & David Pithan, 2019. "From North American hegemony to global competition for scientific leadership? Insights from the Nobel population," PLOS ONE, Public Library of Science, vol. 14(4), pages 1-14, April.
    2. Jingjing Ren & Fang Wang & Minglu Li, 2023. "Dynamics and characteristics of interdisciplinary research in scientific breakthroughs: case studies of Nobel-winning research in the past 120 years," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(8), pages 4383-4419, August.
    3. 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.
    4. Rafael J. P. Damaceno & Luciano Rossi & Rogério Mugnaini & Jesús P. Mena-Chalco, 2019. "The Brazilian academic genealogy: evidence of advisor–advisee relationships through quantitative analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 303-333, April.
    5. Iván Aranzales & Ho Fai Chan & Benno Torgler, 2023. "Finally! How time lapse in Nobel Prize reception affects emotionality in the Nobel Prize banquet speeches," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(7), pages 4089-4115, July.
    6. Fu, Zhongmeng & Cao, Yuan & Zhao, Yong, 2024. "Identifying knowledge evolution in computer science from the perspective of academic genealogy," Journal of Informetrics, Elsevier, vol. 18(2).
    7. Debarshi Kumar Sanyal & Sumana Dey & Partha Pratim Das, 2020. "gm-index: a new mentorship index for researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 71-102, April.
    8. 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.
    9. Jianhua Hou & Bili Zheng & Yang Zhang & Chaomei Chen, 2021. "How do Price medalists’ scholarly impact change before and after their awards?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5945-5981, July.
    10. Shang, Jing & Zeng, Mingbin & Zhang, Gupeng, 2022. "Investigating the mentorship effect on the academic success of young scientists: An empirical study of the 985 project universities of China," Journal of Informetrics, Elsevier, vol. 16(2).
    11. Wuestman, Mignon & Wanzenböck, Iris & Frenken, Koen, 2023. "Local peer communities and future academic success of Ph.D. candidates," Research Policy, Elsevier, vol. 52(8).

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    More about this item

    Keywords

    Academic tree; Nobel Prize; Nobel laureate; Nobel network; Academic genealogy; Scientific communities;
    All these keywords.

    JEL classification:

    • A23 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Graduate

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