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The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science

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  • Benda, Wim G.G.
  • Engels, Tim C.E.

Abstract

In this review we investigate what the available data on the predictive validity of peer review can add to our understanding of judgmental forecasting. We found that peer review attests to the relative success of judgmental forecasting by experts. Both manuscript and group-based peer review allow, on average, for accurate decisions to be made. However, tension exists between peer review and innovative ideas, even though the latter underlie scientific advance. This points to the danger of biases and preconceptions in judgments. We therefore formulate two proposals for enhancing the likelihood of innovative work.

Suggested Citation

  • Benda, Wim G.G. & Engels, Tim C.E., 2011. "The predictive validity of peer review: A selective review of the judgmental forecasting qualities of peers, and implications for innovation in science," International Journal of Forecasting, Elsevier, vol. 27(1), pages 166-182.
    • Handle: RePEc:eee:intfor:v:27:y:2011:i:1:p:166-182
    DOI: 10.1016/j.ijforecast.2010.03.003
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    Cited by:

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    3. Lutz Bornmann, 2015. "Interrater reliability and convergent validity of F1000Prime peer review," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(12), pages 2415-2426, December.
    4. Gill, Chelsea & Mehrotra, Vishal & Moses, Olayinka & Bui, Binh, 2023. "The impact of the pitching research framework on AFAANZ grant applications," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    5. Frederik T. Verleysen & Tim C.E. Engels, 2013. "A label for peer-reviewed books," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(2), pages 428-430, February.
    6. Krist Vaesen & Joel Katzav, 2017. "How much would each researcher receive if competitive government research funding were distributed equally among researchers?," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-11, September.
    7. Wright, George & Rowe, Gene, 2011. "Group-based judgmental forecasting: An integration of extant knowledge and the development of priorities for a new research agenda," International Journal of Forecasting, Elsevier, vol. 27(1), pages 1-13, January.
    8. repec:eee:intfor:v:27:y:2011:i:1:p:1-13 is not listed on IDEAS
    9. Jens Jirschitzka & Aileen Oeberst & Richard Göllner & Ulrike Cress, 2017. "Inter-rater reliability and validity of peer reviews in an interdisciplinary field," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1059-1092, November.
    10. Girish Mallapragada & Nandini Lahiri & Atul Nerkar, 2016. "Peer Review and Research Impact," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(1), pages 29-41, March.
    11. Girish Mallapragada & Nandini Lahiri & Atul Nerkar, 2016. "Peer Review and Research Impact," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(1), pages 29-41, March.
    12. Lutz Bornmann, 2012. "The Hawthorne effect in journal peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(3), pages 857-862, June.

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