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A New Mechanism to Alleviate the Crises of Confidence in Science With An Application to the Public Goods GameA Review

Author

Listed:
  • Luigi Butera

    (CBS - Copenhagen Business School [Copenhagen])

  • Philip J Grossman

    (Monash University [Melbourne])

  • Daniel Houser

    (George Mason University [Fairfax])

  • John A List

    (University of Chicago)

  • Marie Claire Villeval

    (GATE Lyon Saint-Étienne - Groupe d'Analyse et de Théorie Economique Lyon - Saint-Etienne - ENS de Lyon - École normale supérieure de Lyon - UL2 - Université Lumière - Lyon 2 - UCBL - Université Claude Bernard Lyon 1 - Université de Lyon - UJM - Université Jean Monnet - Saint-Étienne - CNRS - Centre National de la Recherche Scientifique)

Abstract

Recently a credibility crisis has taken hold across the social s ciences, arguing that a component of Fischer (1935)'s tripod has not been fully embraced: replication. The importance of replications is not debatable scientifically, but researchers' incentives are not sufficient to encourage replications. We analyze a novel mechanism promoting replications through beneficial gains between scholars and editors. We highlight the tradeoffs involved in seeking independent replications before submission to journals, and demonstrate the operation of this method via an investigation of the effects of Knightian uncertainty on cooperation in public goods games, a pervasive but largely unexplored feature in the literature.

Suggested Citation

  • Luigi Butera & Philip J Grossman & Daniel Houser & John A List & Marie Claire Villeval, 2020. "A New Mechanism to Alleviate the Crises of Confidence in Science With An Application to the Public Goods GameA Review," Working Papers halshs-02512932, HAL.
    • Handle: RePEc:hal:wpaper:halshs-02512932
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    References listed on IDEAS

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    Cited by:

    1. Brodeur, Abel & Cook, Nikolai & Hartley, Jonathan & Heyes, Anthony, 2022. "Do Pre-Registration and Pre-analysis Plans Reduce p-Hacking and Publication Bias?," MetaArXiv uxf39, Center for Open Science.
    2. Abel Brodeur & Nikolai M. Cook & Jonathan S. Hartley & Anthony Heyes, 2024. "Do Preregistration and Preanalysis Plans Reduce p-Hacking and Publication Bias? Evidence from 15,992 Test Statistics and Suggestions for Improvement," Journal of Political Economy Microeconomics, University of Chicago Press, vol. 2(3), pages 527-561.
    3. Takeuchi, Ai & Seki, Erika, 2023. "Coordination and free-riding problems in the provision of multiple public goods," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 95-121.
    4. Silvia Saccardo & Hengchen Dai & Maria A. Han & Sitaram Vangala & Juyea Hoo & Jeffrey Fujimoto, 2024. "Field testing the transferability of behavioural science knowledge on promoting vaccinations," Nature Human Behaviour, Nature, vol. 8(5), pages 878-890, May.
    5. Gary Charness & Brian Jabarian & John A. List, 2023. "Generation Next: Experimentation with AI," NBER Working Papers 31679, National Bureau of Economic Research, Inc.
    6. Dorner, Zack & Tucker, Steven & Hassan, Gazi M, 2024. "Heterogeneous productivity stabilizes public good contributions under certainty, uncertainty and ambiguity," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 110(C).
    7. Ai Takeuchi & Erika Seki, 2023. "Overcoming problems of coordination and freeriding in a game with multiple public goods: dynamic contribution with information provision," The Japanese Economic Review, Springer, vol. 74(3), pages 379-411, July.
    8. Robert Ammerman & Anne Duggan & John List & Lauren Supplee & Dana Suskind, 2021. "The role of open science practices in scaling evidence-based prevention programs," Natural Field Experiments 00741, The Field Experiments Website.
    9. Moritz A. Drupp & Menusch Khadjavi & Rudi Voss, 2024. "The Truth-Telling of Truth-Seekers: Evidence from Online Experiments with Scientists," CESifo Working Paper Series 10897, CESifo.
    10. Ahsanuzzaman, & Palm-Forster, Leah H. & Suter, Jordan F., 2022. "Experimental evidence of common pool resource use in the presence of uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 194(C), pages 139-160.
    11. John A. List & Azeem M. Shaikh & Atom Vayalinkal, 2023. "Multiple testing with covariate adjustment in experimental economics," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(6), pages 920-939, September.
    12. Igor Asanov & Christoph Buehren & Panagiota Zacharodimou, 2020. "The power of experiments: How big is your n?," MAGKS Papers on Economics 202032, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    13. John A. List, 2024. "Optimally generate policy-based evidence before scaling," Nature, Nature, vol. 626(7999), pages 491-499, February.

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