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A new reader trial approach to peer review in funding research grants: An Australian experiment

Author

Listed:
  • Upali W. Jayasinghe

    (University of Western Sydney)

  • Herbert W. Marsh

    (University of Western Sydney; Department of Educational Studies, University of Oxford)

  • Nigel Bond

    (University of Western Sydney)

Abstract

Summary Peer reviews are highly valued in academic life, but are notoriously unreliable. A major problem is the substantial measurement error due to the idiosyncratic responses when large numbers of different assessors each evaluate only a single or a few submissions (e.g., journal articles, grants, etc.). To address this problem, the main funding body of academic research in Australia trialed a “reader system” in which each of a small number of senior academics read all proposals within their subdiscipline. The traditional peer review process for 1996 (2,989 proposals, 6,233 assessors) resulted in unacceptably low reliabilities comparable with those found in other research (0.475 for research project, 0.572 for researcher). For proposals from psychology and education in 1997, the new reader system resulted in substantially higher reliabilities: 0.643 and 0.881, respectively. In comparison to the traditional peer review approach, the new reader system is substantially more reliable, timely, and cost efficient - and applicable to many peer review situations.

Suggested Citation

  • Upali W. Jayasinghe & Herbert W. Marsh & Nigel Bond, 2006. "A new reader trial approach to peer review in funding research grants: An Australian experiment," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(3), pages 591-606, December.
    • Handle: RePEc:spr:scient:v:69:y:2006:i:3:d:10.1007_s11192-006-0171-4
    DOI: 10.1007/s11192-006-0171-4
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    Cited by:

    1. Wiltrud Kuhlisch & Magnus Roos & Jörg Rothe & Joachim Rudolph & Björn Scheuermann & Dietrich Stoyan, 2016. "A statistical approach to calibrating the scores of biased reviewers of scientific papers," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 37-57, January.
    2. Vieira, Elizabeth S. & Cabral, José A.S. & Gomes, José A.N.F., 2014. "How good is a model based on bibliometric indicators in predicting the final decisions made by peers?," Journal of Informetrics, Elsevier, vol. 8(2), pages 390-405.
    3. Katarína Cechlárová & Tamás Fleiner & Eva Potpinková, 2014. "Assigning evaluators to research grant applications: the case of Slovak Research and Development Agency," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 495-506, May.
    4. 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.
    5. Wei-dong Zhu & Fang Liu & Yu-wang Chen & Jian-bo Yang & Dong-ling Xu & Dong-peng Wang, 2015. "Research project evaluation and selection: an evidential reasoning rule-based method for aggregating peer review information with reliabilities," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1469-1490, December.
    6. 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.
    7. Dekel Omer & Schurr Amos, 2014. "Cognitive Biases in Government Procurement – An Experimental Study," Review of Law & Economics, De Gruyter, vol. 10(2), pages 169-200, July.
    8. Marsh, Herbert W. & Jayasinghe, Upali W. & Bond, Nigel W., 2011. "Gender differences in peer reviews of grant applications: A substantive-methodological synergy in support of the null hypothesis model," Journal of Informetrics, Elsevier, vol. 5(1), pages 167-180.
    9. 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, January.
    10. 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.

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