IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v103y2015i1d10.1007_s11192-015-1526-5.html
   My bibliography  Save this article

Close to the edge: co-authorship proximity of Nobel laureates in Physiology or Medicine, 1991–2010, to cross-disciplinary brokers

Author

Listed:
  • Chris Fields

    (528 Zinnia Court)

Abstract

Between 1991 and 2010, 45 scientists were honored with Nobel prizes in Physiology or Medicine. It is shown that these 45 Nobel laureates are separated, on average, by at most 2.8 co-authorship steps from at least one cross-disciplinary broker, defined as a researcher who has published co-authored papers both in some biomedical discipline and in some non-biomedical discipline. If Nobel laureates in Physiology or Medicine and their immediate collaborators can be regarded as forming the intuitive “center” of the biomedical sciences, then at least for this 20-year sample of Nobel laureates, the center of the biomedical sciences within the co-authorship graph of all of the sciences is closer to the edges of multiple non-biomedical disciplines than typical biomedical researchers are to each other.

Suggested Citation

  • Chris Fields, 2015. "Close to the edge: co-authorship proximity of Nobel laureates in Physiology or Medicine, 1991–2010, to cross-disciplinary brokers," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 267-299, April.
  • Handle: RePEc:spr:scient:v:103:y:2015:i:1:d:10.1007_s11192-015-1526-5
    DOI: 10.1007/s11192-015-1526-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-015-1526-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s11192-015-1526-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Isidro F. Aguillo, 2012. "Is Google Scholar useful for bibliometrics? A webometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 343-351, May.
    2. Andrea Landherr & Bettina Friedl & Julia Heidemann, 2010. "A Critical Review of Centrality Measures in Social Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 2(6), pages 371-385, December.
    3. Anne-Wil Harzing, 2013. "A preliminary test of Google Scholar as a source for citation data: a longitudinal study of Nobel prize winners," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1057-1075, March.
    4. Alan L. Porter & Ismael Rafols, 2009. "Is science becoming more interdisciplinary? Measuring and mapping six research fields over time," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(3), pages 719-745, December.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yalcin, Haydar & Daim, Tugrul & Moughari, Mahdieh Mokhtari & Mermoud, Alain, 2024. "Supercomputers and quantum computing on the axis of cyber security," Technology in Society, Elsevier, vol. 77(C).
    2. 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.
    3. Chris Fields, 2015. "Co-authorship proximity of A. M. Turing Award and John von Neumann Medal winners to the disciplinary boundaries of computer science," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(3), pages 809-825, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chris Fields, 2015. "How small is the center of science? Short cross-disciplinary cycles in co-authorship graphs," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1287-1306, February.
    2. Martin-Martin, Alberto & Orduna-Malea, Enrique & Harzing, Anne-Wil & Delgado López-Cózar, Emilio, 2017. "Can we use Google Scholar to identify highly-cited documents?," Journal of Informetrics, Elsevier, vol. 11(1), pages 152-163.
    3. Enrique Orduña-Malea & Emilio Delgado López-Cózar, 2014. "Google Scholar Metrics evolution: an analysis according to languages," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 2353-2367, March.
    4. Ronnie Ramlogan & Davide Consoli, 2014. "Dynamics of collaborative research medicine: the case of glaucoma," The Journal of Technology Transfer, Springer, vol. 39(4), pages 544-566, August.
    5. Hugo Confraria & Fernando Vargas, 2019. "Scientific systems in Latin America: performance, networks, and collaborations with industry," The Journal of Technology Transfer, Springer, vol. 44(3), pages 874-915, June.
    6. Cristòfol Rovira & Lluís Codina & Frederic Guerrero-Solé & Carlos Lopezosa, 2019. "Ranking by Relevance and Citation Counts, a Comparative Study: Google Scholar, Microsoft Academic, WoS and Scopus," Future Internet, MDPI, vol. 11(9), pages 1-21, September.
    7. Cristòfol Rovira & Lluís Codina & Carlos Lopezosa, 2021. "Language Bias in the Google Scholar Ranking Algorithm," Future Internet, MDPI, vol. 13(2), pages 1-17, January.
    8. Wahid-Ul-Ashraf, Akanda & Budka, Marcin & Musial, Katarzyna, 2019. "How to predict social relationships — Physics-inspired approach to link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1110-1129.
    9. Miguel A. García-Pérez, 2015. "Online supplemental information: a sizeable black hole for citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1655-1659, February.
    10. Mark R. Costa & Jian Qin & Sarah Bratt, 2016. "Emergence of collaboration networks around large scale data repositories: a study of the genomics community using GenBank," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 21-40, July.
    11. Enrique Orduna-Malea & Selenay Aytac & Clara Y. Tran, 2019. "Universities through the eyes of bibliographic databases: a retroactive growth comparison of Google Scholar, Scopus and Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 433-450, October.
    12. Jacob Wood & Gohar Feroz Khan, 2015. "International trade negotiation analysis: network and semantic knowledge infrastructure," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 537-556, October.
    13. Stephen Carley & Alan L. Porter, 2012. "A forward diversity index," Scientometrics, Springer;Akadémiai Kiadó, vol. 90(2), pages 407-427, February.
    14. Marian-Gabriel Hâncean & Matjaž Perc & Lazăr Vlăsceanu, 2014. "Fragmented Romanian Sociology: Growth and Structure of the Collaboration Network," PLOS ONE, Public Library of Science, vol. 9(11), pages 1-9, November.
    15. Jian Xu & Yi Bu & Ying Ding & Sinan Yang & Hongli Zhang & Chen Yu & Lin Sun, 2018. "Understanding the formation of interdisciplinary research from the perspective of keyword evolution: a case study on joint attention," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(2), pages 973-995, November.
    16. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    17. Diego Chavarro & Puay Tang & Ismael Rafols, 2014. "Interdisciplinarity and research on local issues: evidence from a developing country," Research Evaluation, Oxford University Press, vol. 23(3), pages 195-209.
    18. Su, Hsin-Ning & Moaniba, Igam M., 2017. "Investigating the dynamics of interdisciplinary evolution in technology developments," Technological Forecasting and Social Change, Elsevier, vol. 122(C), pages 12-23.
    19. Laura Borge & Stefanie Bröring, 2020. "What affects technology transfer in emerging knowledge areas? A multi-stakeholder concept mapping study in the bioeconomy," The Journal of Technology Transfer, Springer, vol. 45(2), pages 430-460, April.
    20. Marian-Gabriel Hâncean & Matjaž Perc & Jürgen Lerner, 2021. "The coauthorship networks of the most productive European researchers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 201-224, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:103:y:2015:i:1:d:10.1007_s11192-015-1526-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.