IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v109y2016i2d10.1007_s11192-016-2079-y.html
   My bibliography  Save this article

Authors and reviewers who suffer from confirmatory bias

Author

Listed:
  • J. A. García

    (CITIC-UGR, Universidad de Granada)

  • Rosa Rodriguez-Sánchez

    (CITIC-UGR, Universidad de Granada)

  • J. Fdez-Valdivia

    (CITIC-UGR, Universidad de Granada)

Abstract

Confirmatory bias induces overconfidence in the sense that people believe more strongly than they should in their preferred hypotheses. This work describes a Bayesian-based formal model to study the effect of overconfidence about the causes of manuscript rejection due to confirmatory bias in peer review. In addition, we also present an online tool that helps authors to study their beliefs about the causes of rejection. This tool takes the authors’ self-evaluated probability of misinterpretation (i.e. confirmatory bias) and self-evaluated probability of perceiving a review signal correlated with the true cause of rejection and a sequence of review signals perceived as input, and gives a prediction of whether there is overconfidence and wrongness in the author’s belief that bias in peer review caused rejection. We continue to discuss the effect of confirmatory bias in the editor-reviewer relationship in peer review process and show that when the strength of informative signals about the manuscript quality is sufficiently weak and reviewer’s confirmatory bias is sufficiently severe, there is a strong probability that the reviewer would erroneously identify the manuscript quality, making the editor less inclined to offer the potential reviewer any incentive to accept the invitation to review the manuscript. Based on these, we offer a theoretical explanation of current practices adopted to improve the review performance (e.g., desk rejection).

Suggested Citation

  • J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2016. "Authors and reviewers who suffer from confirmatory bias," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1377-1395, November.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:2:d:10.1007_s11192-016-2079-y
    DOI: 10.1007/s11192-016-2079-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-016-2079-y
    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/s11192-016-2079-y?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. Keren, Gideon, 1987. "Facing uncertainty in the game of bridge: A calibration study," Organizational Behavior and Human Decision Processes, Elsevier, vol. 39(1), pages 98-114, February.
    2. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    3. Jose A. García & Rosa Rodriguez-Sánchez & Joaquín Fdez-Valdivia, 2015. "Adverse selection of reviewers," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(6), pages 1252-1262, June.
    4. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2016. "Why the referees’ reports I receive as an editor are so much better than the reports I receive as an author?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 967-986, March.
    5. Matthew Rabin & Joel L. Schrag, 1999. "First Impressions Matter: A Model of Confirmatory Bias," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 37-82.
    6. Carole J. Lee & Cassidy R. Sugimoto & Guo Zhang & Blaise Cronin, 2013. "Bias in peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 2-17, January.
    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. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2017. "STRATEGY: a tool for the formulation of peer-review strategies," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 45-60, October.
    2. Ivana Drvenica & Giangiacomo Bravo & Lucija Vejmelka & Aleksandar Dekanski & Olgica Nedić, 2018. "Peer Review of Reviewers: The Author’s Perspective," Publications, MDPI, vol. 7(1), pages 1-10, December.
    3. J. A. Garcia & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2020. "Confirmatory bias in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 517-533, April.
    4. Bayindir, Esra Eren & Gurdal, Mehmet Yigit & Saglam, Ismail, 2019. "A Game Theoretic Approach to Peer Review of Grant Proposals," Journal of Informetrics, Elsevier, vol. 13(4).

    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. Rosa Rodriguez-Sánchez & J. A. García & J. Fdez-Valdivia, 2018. "Editorial decisions with informed and uninformed reviewers," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 25-43, October.
    2. J. A. Garcia & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2020. "Confirmatory bias in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 517-533, April.
    3. Jorge Chamorro-Padial & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & J. A. Garcia, 2019. "An evolutionary explanation of assassins and zealots in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(3), pages 1373-1385, September.
    4. Jürgen Janger & Nicole Schmidt-Padickakudy & Anna Strauss-Kollin, 2019. "International Differences in Basic Research Grant Funding. A Systematic Comparison," WIFO Studies, WIFO, number 61664, March.
    5. Rodríguez Sánchez, Isabel & Makkonen, Teemu & Williams, Allan M., 2019. "Peer review assessment of originality in tourism journals: critical perspective of key gatekeepers," Annals of Tourism Research, Elsevier, vol. 77(C), pages 1-11.
    6. Zhentao Liang & Jin Mao & Gang Li, 2023. "Bias against scientific novelty: A prepublication perspective," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 74(1), pages 99-114, January.
    7. Elena Veretennik & Maria Yudkevich, 2023. "Inconsistent quality signals: evidence from the regional journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3675-3701, June.
    8. Meyer, Matthias & Waldkirch, Rüdiger W. & Duscher, Irina & Just, Alexander, 2018. "Drivers of citations: An analysis of publications in “top” accounting journals," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 51(C), pages 24-46.
    9. Seeber, Marco & Alon, Ilan & Pina, David G. & Piro, Fredrik Niclas & Seeber, Michele, 2022. "Predictors of applying for and winning an ERC Proof-of-Concept grant: An automated machine learning model," Technological Forecasting and Social Change, Elsevier, vol. 184(C).
    10. Feliciani, Thomas & Morreau, Michael & Luo, Junwen & Lucas, Pablo & Shankar, Kalpana, 2022. "Designing grant-review panels for better funding decisions: Lessons from an empirically calibrated simulation model," Research Policy, Elsevier, vol. 51(4).
    11. David Card & Stefano DellaVigna, 2017. "What do Editors Maximize? Evidence from Four Leading Economics Journals," NBER Working Papers 23282, National Bureau of Economic Research, Inc.
    12. J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2016. "Why the referees’ reports I receive as an editor are so much better than the reports I receive as an author?," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(3), pages 967-986, March.
    13. Lybbert, Travis J. & Barrett, Christopher B. & McPeak, John G. & Luseno, Winnie K., 2007. "Bayesian Herders: Updating of Rainfall Beliefs in Response to External Forecasts," World Development, Elsevier, vol. 35(3), pages 480-497, March.
    14. Dietmar Wolfram & Peiling Wang & Adam Hembree & Hyoungjoo Park, 2020. "Open peer review: promoting transparency in open science," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1033-1051, November.
    15. Andrada Elena Urda-Cîmpean & Sorana D. Bolboacă & Andrei Achimaş-Cadariu & Tudor Cătălin Drugan, 2016. "Knowledge Production in Two Types of Medical PhD Routes—What’s to Gain?," Publications, MDPI, vol. 4(2), pages 1-16, June.
    16. Oleksiyenko, Anatoly V., 2023. "Geopolitical agendas and internationalization of post-soviet higher education: Discursive dilemmas in the realm of the prestige economy," International Journal of Educational Development, Elsevier, vol. 102(C).
    17. Randa Alsabahi, 2022. "English Medium Publications: Opening or Closing Doors to Authors with Non-English Language Backgrounds," English Language Teaching, Canadian Center of Science and Education, vol. 15(10), pages 1-18, October.
    18. Yuetong Chen & Hao Wang & Baolong Zhang & Wei Zhang, 2022. "A method of measuring the article discriminative capacity and its distribution," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(6), pages 3317-3341, June.
    19. Qianjin Zong & Yafen Xie & Jiechun Liang, 2020. "Does open peer review improve citation count? Evidence from a propensity score matching analysis of PeerJ," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 607-623, October.
    20. Thomas Feliciani & Junwen Luo & Lai Ma & Pablo Lucas & Flaminio Squazzoni & Ana Marušić & Kalpana Shankar, 2019. "A scoping review of simulation models of peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 555-594, October.

    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:109:y:2016:i:2:d:10.1007_s11192-016-2079-y. 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.