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Empirical demonstration of the Matthew effect in scientific research careers

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  • 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
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    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. Birkmaier, Daniel & Wohlrabe, Klaus, 2014. "The Matthew effect in economics reconsidered," Journal of Informetrics, Elsevier, vol. 8(4), pages 880-889.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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).
    15. repec:nas:journl:v:115:y:2018:p:4887-4890 is not listed on IDEAS
    16. 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.
    17. 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).
    18. 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.
    19. 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.
    20. 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.
    21. Tol, Richard S.J., 2013. "The Matthew effect for cohorts of economists," Journal of Informetrics, Elsevier, vol. 7(2), pages 522-527.
    22. 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.
    23. 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.
    24. Liao, Chien Hsiang, 2021. "The Matthew effect and the halo effect in research funding," Journal of Informetrics, Elsevier, vol. 15(1).
    25. 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.
    26. 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).
    27. Wang, Jian, 2014. "Unpacking the Matthew effect in citations," Journal of Informetrics, Elsevier, vol. 8(2), pages 329-339.
    28. 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.
    29. 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.
    30. 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.
    31. 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).
    32. 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).
    33. 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.
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