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The reviewer in the mirror: examining gendered and ethnicized notions of reciprocity in peer review

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  • Bradford Demarest

    (Indiana University Bloomington)

  • Guo Freeman

    (Indiana University Bloomington)

  • Cassidy R. Sugimoto

    (Indiana University Bloomington)

Abstract

Numerous studies have sought to uncover violations of objectivity and impartiality in peer review; however the notion of reciprocity has been absent in much of this discussion, particularly as it relates to gendered and ethnicized behaviors of peer review. The current study addresses this gap in research by investigating patterns of reciprocity (i.e., correspondences between patterns of recommendations received by authors and patterns of recommendations given by reviewers in the same social group) by perceived gender and ethnicity of reviewers and authors for submissions to the Journal of the American Society for Information Science and Technology from June 2009 to May 2011. The degree of reciprocity for each social group was examined by employing Monte Carlo resampling to extrapolate more robust patterns from the limited data available. We found that papers with female authors received more negative reviews than reviews for male authors. Reciprocity was suggested by the fact that female reviewers gave lower reviews than male reviewers. Reciprocity was also exhibited by ethnicity, although non-Western reviewers gave disproportionately more recommendations of major revision, while non-Western authors tended to receive more outright rejections. This study provides a novel theoretical and methodological basis for future studies on reciprocity in peer review.

Suggested Citation

  • Bradford Demarest & Guo Freeman & Cassidy R. Sugimoto, 2014. "The reviewer in the mirror: examining gendered and ethnicized notions of reciprocity in peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 717-735, October.
    • Handle: RePEc:spr:scient:v:101:y:2014:i:1:d:10.1007_s11192-014-1354-z
    DOI: 10.1007/s11192-014-1354-z
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    References listed on IDEAS

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    1. Falk, Armin & Fischbacher, Urs, 2006. "A theory of reciprocity," Games and Economic Behavior, Elsevier, vol. 54(2), pages 293-315, February.
    2. Lutz Bornmann & Rüdiger Mutz & Hans-Dieter Daniel, 2010. "A Reliability-Generalization Study of Journal Peer Reviews: A Multilevel Meta-Analysis of Inter-Rater Reliability and Its Determinants," PLOS ONE, Public Library of Science, vol. 5(12), pages 1-10, December.
    3. Lutz Bornmann & Rüdiger Mutz & Hans-Dieter Daniel, 2009. "The influence of the applicants’ gender on the modeling of a peer review process by using latent Markov models," Scientometrics, Springer;Akadémiai Kiadó, vol. 81(2), pages 407-411, November.
    4. Charles F. Manski, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 60(3), pages 531-542.
    5. 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.
    6. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2008. "How to detect indications of potential sources of bias in peer review: A generalized latent variable modeling approach exemplified by a gender study," Journal of Informetrics, Elsevier, vol. 2(4), pages 280-287.
    7. Christine Wennerås & Agnes Wold, 1997. "Nepotism and sexism in peer-review," Nature, Nature, vol. 387(6631), pages 341-343, May.
    8. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2007. "Gender differences in grant peer review: A meta-analysis," Journal of Informetrics, Elsevier, vol. 1(3), pages 226-238.
    9. 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.
    10. Enrico Moretti, 2011. "Social Learning and Peer Effects in Consumption: Evidence from Movie Sales," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 78(1), pages 356-393.
    11. Blank, Rebecca M, 1991. "The Effects of Double-Blind versus Single-Blind Reviewing: Experimental Evidence from The American Economic Review," American Economic Review, American Economic Association, vol. 81(5), pages 1041-1067, December.
    12. Oswald, Andrew J., 2008. "Can We Test for Bias in Scientific Peer-Review?," IZA Discussion Papers 3665, Institute of Labor Economics (IZA).
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