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The Reverse Matthew Effect: Consequences of Retraction in Scientific Teams

Author

Listed:
  • Ginger Zhe Jin

    (University of Maryland and NBER)

  • Benjamin Jones

    (Northwestern University and NBER)

  • Susan Feng Lu

    (Purdue University and CCER)

  • Brian Uzzi

    (Northwestern University)

Abstract

Teamwork pervades modern production, yet teamwork can make individual roles difficult to ascertain. The Matthew effect suggests that communities reward eminent team members for great outcomes at the expense of less eminent team members. We study this phenomenon in reverse, investigating credit sharing after damaging events. Our context is article retractions in the sciences. We find that retractions impose little citation penalty on the prior work of eminent coauthors, but less eminent coauthors experience substantial citation declines, especially when teamed with eminent authors. These findings suggest a reverse Matthew effect for team-produced negative events. A Bayesian model provides a candidate interpretation.

Suggested Citation

  • Ginger Zhe Jin & Benjamin Jones & Susan Feng Lu & Brian Uzzi, 2019. "The Reverse Matthew Effect: Consequences of Retraction in Scientific Teams," The Review of Economics and Statistics, MIT Press, vol. 101(3), pages 492-506, July.
  • Handle: RePEc:tpr:restat:v:101:y:2019:i:3:p:492-506
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    Citations

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    Cited by:

    1. Eleonora Alabrese, 2022. "Bad Science: Retractions and Media Coverage," CESifo Working Paper Series 10195, CESifo.
    2. Sebastian Hager & Carlo Schwarz & Fabian Waldinger, 2023. "Measuring Science: Performance Metrics and the Allocation of Talent," Rationality and Competition Discussion Paper Series 455, CRC TRR 190 Rationality and Competition.
    3. 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).
    4. Lea Heursen & Svenja Friess & Marina Chugunova, 2023. "Reputational Concerns and Advice-Seeking at Work," Rationality and Competition Discussion Paper Series 447, CRC TRR 190 Rationality and Competition.
    5. Rainer Widmann & Michael E. Rose & Marina Chugunova, 2023. "Allegations of Sexual Misconduct, Accused Scientists, and Their Research," Rationality and Competition Discussion Paper Series 419, CRC TRR 190 Rationality and Competition.
    6. Ozerturk, Saltuk & Yildirim, Huseyin, 2021. "Credit attribution and collaborative work," Journal of Economic Theory, Elsevier, vol. 195(C).
    7. Kiran Sharma, 2021. "Team size and retracted citations reveal the patterns of retractions from 1981 to 2020," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(10), pages 8363-8374, October.
    8. Xu, Haifeng & Ding, Yi & Zhang, Cheng & Tan, Bernard C.Y., 2023. "Too official to be effective: An empirical examination of unofficial information channel and continued use of retracted articles," Research Policy, Elsevier, vol. 52(7).
    9. Benjamin F. Jones, 2021. "The Rise of Research Teams: Benefits and Costs in Economics," Journal of Economic Perspectives, American Economic Association, vol. 35(2), pages 191-216, Spring.
    10. Ajab Khan & Ali Sina Önder & Sercan Özcan, 2023. "Does Performance-based Public Funding Pay off? UK’s Research Excellence Framework (REF) and Research Productivity," Working Papers in Economics & Finance 2023-08, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    11. Kiran Sharma & Satyam Mukherjee, 2024. "The ripple effect of retraction on an author’s collaboration network," Journal of Computational Social Science, Springer, vol. 7(2), pages 1519-1531, October.
    12. Završnik, Jernej & Perc, Matjaž, 2024. "Bird’s-eye view of Slovenian pediatrics reveals complexity but also consistency," Chaos, Solitons & Fractals, Elsevier, vol. 181(C).
    13. Timm Opitz, 2024. "Interpersonal Preferences and Team Performance: The Role of Liking in Complex Problem Solving," Rationality and Competition Discussion Paper Series 492, CRC TRR 190 Rationality and Competition.
    14. 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.

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