IDEAS home Printed from https://ideas.repec.org/a/eee/infome/v17y2023i4s1751157723000901.html
   My bibliography  Save this article

Empirical demonstration of the Matthew effect in scientific research careers

Author

Listed:
  • Katchanov, Yurij L.
  • Markova, Yulia V.
  • Shmatko, Natalia A.

Abstract

The Matthew effect qualitatively describes the social phenomenon that the impact and recognition of well-known scientists for their new accomplishments are relatively overpriced by the scientific community when compared to the similar output of researchers without fame or status. We quantify the manifestation of this phenomenon in scientific research careers. For this purpose, using a mixed survey-plus-bibliometrics method, we assembled a dataset containing detailed career information on scientists in the field of chemistry. The mathematical model of the Matthew effect in scientific research careers proposed in this paper identifies career distribution as the generalized extreme value distribution with the shape parameter q=0.5. This result is in good agreement with the obtained data: the empirical distribution of scientific careers can be approximated by the generalized extreme value distribution with q=0.423. We also find that the distribution of starting positions of social trajectories of scientists fits by the Pareto distribution. Our analysis deepens scientific insight into the emergence of the Matthew effect in scientific careers and its relationship to the distribution of citations and citation entropy.

Suggested Citation

  • Katchanov, Yurij L. & Markova, Yulia V. & Shmatko, Natalia A., 2023. "Empirical demonstration of the Matthew effect in scientific research careers," Journal of Informetrics, Elsevier, vol. 17(4).
    • Handle: RePEc:eee:infome:v:17:y:2023:i:4:s1751157723000901
    DOI: 10.1016/j.joi.2023.101465
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1751157723000901
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.joi.2023.101465?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. Jaime A. Teixeira da Silva, 2021. "The Matthew effect impacts science and academic publishing by preferentially amplifying citations, metrics and status," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 5373-5377, June.
    2. Betancourt, Nathan & Jochem, Torsten & Otner, Sarah M.G., 2023. "Standing on the shoulders of giants: How star scientists influence their coauthors," Research Policy, Elsevier, vol. 52(1).
    3. Hendrik P. Dalen, 2021. "How the publish-or-perish principle divides a science: the case of economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1675-1694, February.
    4. Yegorov, Yury & Wirl, Franz & Grass, Dieter & Eigruber, Markus & Feichtinger, Gustav, 2022. "On the matthew effect on individual investments in skills in arts, sports and science," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 178-199.
    5. Yifang Ma & Satyam Mukherjee & Brian Uzzi, 2020. "Mentorship and protégé success in STEM fields," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(25), pages 14077-14083, June.
    6. Chakraborty, Tanmoy & Tammana, Vihar & Ganguly, Niloy & Mukherjee, Animesh, 2015. "Understanding and modeling diverse scientific careers of researchers," Journal of Informetrics, Elsevier, vol. 9(1), pages 69-78.
    7. Feichtinger, Gustav & Grass, Dieter & Kort, Peter M. & Seidl, Andrea, 2021. "On the Matthew effect in research careers," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    8. Ho Fai Chan & Laura Gleeson & Benno Torgler, 2014. "Awards before and after the Nobel Prize: A Matthew effect and/or a ticket to one’s own funeral?," Research Evaluation, Oxford University Press, vol. 23(3), pages 210-220.
    9. Robinson-Garcia, Nicolás & Sugimoto, Cassidy R. & Murray, Dakota & Yegros-Yegros, Alfredo & Larivière, Vincent & Costas, Rodrigo, 2019. "The many faces of mobility: Using bibliometric data to measure the movement of scientists," Journal of Informetrics, Elsevier, vol. 13(1), pages 50-63.
    10. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    11. Carolina Cañibano & Richard Woolley & Eric J. Iversen & Sybille Hinze & Stefan Hornbostel & Jakob Tesch, 2019. "A conceptual framework for studying science research careers," The Journal of Technology Transfer, Springer, vol. 44(6), pages 1964-1992, December.
    12. Clara Boothby & Staša Milojević, 2021. "An exploratory full-text analysis of Science Careers in a changing academic job market," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4055-4071, May.
    13. Wang, Jian, 2014. "Unpacking the Matthew effect in citations," Journal of Informetrics, Elsevier, vol. 8(2), pages 329-339.
    14. K. Hunter Wapman & Sam Zhang & Aaron Clauset & Daniel B. Larremore, 2022. "Quantifying hierarchy and dynamics in US faculty hiring and retention," Nature, Nature, vol. 610(7930), pages 120-127, October.
    15. Squazzoni, Flaminio & Gandelli, Claudio, 2012. "Saint Matthew strikes again: An agent-based model of peer review and the scientific community structure," Journal of Informetrics, Elsevier, vol. 6(2), pages 265-275.
    16. Liv Langfeldt & Mats Benner & Gunnar Sivertsen & Ernst H. Kristiansen & Dag W. Aksnes & Siri Brorstad Borlaug & Hanne Foss Hansen & Egil Kallerud & Antti Pelkonen, 2015. "Excellence and growth dynamics: A comparative study of the Matthew effect," Science and Public Policy, Oxford University Press, vol. 42(5), pages 661-675.
    17. 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).
    18. Kyle Siler & Philippe Vincent-Lamarre & Cassidy R Sugimoto & Vincent Larivière, 2022. "Cumulative advantage and citation performance of repeat authors in scholarly journals," PLOS ONE, Public Library of Science, vol. 17(4), pages 1-17, April.
    19. Birkmaier, Daniel & Wohlrabe, Klaus, 2014. "The Matthew effect in economics reconsidered," Journal of Informetrics, Elsevier, vol. 8(4), pages 880-889.
    20. Yang Wang & Benjamin F. Jones & Dashun Wang, 2019. "Early-career setback and future career impact," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    21. van Dalen, Hendrik Peter, 2021. "How the publish-or-perish principle divides a science: The case of economists," Other publications TiSEM a6a5a855-bb5a-4d52-a841-3, Tilburg University, School of Economics and Management.
    22. Weihua Li & Tomaso Aste & Fabio Caccioli & Giacomo Livan, 2019. "Early coauthorship with top scientists predicts success in academic careers," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    23. Richard S.J. Tol, 2009. "The Matthew effect defined and tested for the 100 most prolific economists," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(2), pages 420-426, February.
    24. Ho Fai Chan & Franklin G. Mixon & Jayanta Sarkar & Benno Torgler, 2022. "Recognition and longevity: an examination of award timing and lifespan in Nobel laureates," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3629-3659, June.
    25. Xue Yang & Xin Gu & Yuandi Wang & Guangyuan Hu & Li Tang, 2015. "The Matthew effect in China’s science: evidence from academicians of Chinese Academy of Sciences," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2089-2105, March.
    26. Thijs Bol & Mathijs de Vaan & Arnout van de Rijt, 2018. "The Matthew effect in science funding," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 115(19), pages 4887-4890, May.
    27. Yu, Xiaoyao & Szymanski, Boleslaw K. & Jia, Tao, 2021. "Become a better you: Correlation between the change of research direction and the change of scientific performance," Journal of Informetrics, Elsevier, vol. 15(3).
    28. Suwaiba Afonja & Damonie G Salmon & Shadelia I Quailey & W Marcus Lambert, 2021. "Postdocs’ advice on pursuing a research career in academia: A qualitative analysis of free-text survey responses," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-20, May.
    29. Diego Kozlowski & Vincent Larivière & Cassidy R. Sugimoto & Thema Monroe-White, 2022. "Intersectional inequalities in science," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(2), pages 2113067119-, January.
    30. Fengli Xu & Lingfei Wu & James Evans, 2022. "Flat teams drive scientific innovation," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(23), pages 2200927119-, June.
    31. Liao, Chien Hsiang, 2021. "The Matthew effect and the halo effect in research funding," Journal of Informetrics, Elsevier, vol. 15(1).
    32. Wu, Lingfei & Kittur, Aniket & Youn, Hyejin & Milojević, Staša & Leahey, Erin & Fiore, Stephen M. & Ahn, Yong-Yeol, 2022. "Metrics and mechanisms: Measuring the unmeasurable in the science of science," Journal of Informetrics, Elsevier, vol. 16(2).
    33. 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).
    Full references (including those not matched with items on IDEAS)

    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. Daniel Birkmaier & Klaus Wohlrabe, 2014. "Der Matthäus-Effekt in der Ökonomie," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 67(17), pages 38-42, September.
    2. Migheli, Matteo & Zotti, Roberto, 2020. "The strange case of the Matthew effect and beauty contests: Research evaluation and specialisation in Italian universities," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    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. 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).
    5. Birkmaier, Daniel & Wohlrabe, Klaus, 2014. "The Matthew effect in economics reconsidered," Journal of Informetrics, Elsevier, vol. 8(4), pages 880-889.
    6. Rodrigo Dorantes-Gilardi & Aurora A. Ramírez-Álvarez & Diana Terrazas-Santamaría, 2023. "Is there a differentiated gender effect of collaboration with super-cited authors? Evidence from junior researchers in economics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2317-2336, April.
    7. Yue Wang & Ning Li & Bin Zhang & Qian Huang & Jian Wu & Yang Wang, 2023. "The effect of structural holes on producing novel and disruptive research in physics," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1801-1823, March.
    8. Yu, Xiaoyao & Szymanski, Boleslaw K. & Jia, Tao, 2021. "Become a better you: Correlation between the change of research direction and the change of scientific performance," Journal of Informetrics, Elsevier, vol. 15(3).
    9. Liao, Chien Hsiang, 2021. "The Matthew effect and the halo effect in research funding," Journal of Informetrics, Elsevier, vol. 15(1).
    10. Zhang, Yang & Wang, Yang & Du, Haifeng & Havlin, Shlomo, 2024. "Delayed citation impact of interdisciplinary research," Journal of Informetrics, Elsevier, vol. 18(1).
    11. Mario González-Sauri & Giulia Rossello, 2023. "The Role of Early-Career University Prestige Stratification on the Future Academic Performance of Scholars," Research in Higher Education, Springer;Association for Institutional Research, vol. 64(1), pages 58-94, February.
    12. Zhang, Wanshu & Wang, Xuefeng & Chen, Hongshu & Liu, Jia, 2024. "The impact of early debut on scientists: Evidence from the Young Scientists Fund of the NSFC," Research Policy, Elsevier, vol. 53(2).
    13. 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.
    14. 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.
    15. Feichtinger, Gustav & Grass, Dieter & Kort, Peter M. & Seidl, Andrea, 2021. "On the Matthew effect in research careers," Journal of Economic Dynamics and Control, Elsevier, vol. 123(C).
    16. Matteo Cinelli & Giovanna Ferraro & Antonio Iovanella, 2022. "Connections matter: a proxy measure for evaluating network membership with an application to the Seventh Research Framework Programme," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3959-3976, July.
    17. Yang, Alex Jie & Wu, Linwei & Zhang, Qi & Wang, Hao & Deng, Sanhong, 2023. "The k-step h-index in citation networks at the paper, author, and institution levels," Journal of Informetrics, Elsevier, vol. 17(4).
    18. Justus Haucap & Nima Moshgbar & W. Benedikt Schmal, 2021. "The impact of the German 'DEAL' on competition in the academic publishing market," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(8), pages 2027-2049, December.
    19. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    20. Tol, Richard S.J., 2023. "Nobel begets Nobel in economics," Journal of Informetrics, Elsevier, vol. 17(4).

    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:eee:infome:v:17:y:2023:i:4:s1751157723000901. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/joi .

    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.