IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v101y2014i1d10.1007_s11192-014-1354-z.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-014-1354-z
    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/s11192-014-1354-z?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. 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).
    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. Lin Zhang & Yuanyuan Shang & Ying Huang & Gunnar Sivertsen, 2022. "Gender differences among active reviewers: an investigation based on publons," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 145-179, January.
    2. Zhang, Lin & Shang, Yuanyuan & HUANG, Ying & Sivertsen, Gunnar, 2021. "Gender differences among active reviewers: an investigation based on Publons," SocArXiv 4z6w8, Center for Open Science.
    3. Justus Haucap & Johannes Muck, 2015. "What drives the relevance and reputation of economics journals? An update from a survey among economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 849-877, June.
    4. Gerson Pech & Catarina Delgado, 2020. "Percentile and stochastic-based approach to the comparison of the number of citations of articles indexed in different bibliographic databases," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 223-252, April.
    5. Pengfei Jia & Weixi Xie & Guangyao Zhang & Xianwen Wang, 2023. "Do reviewers get their deserved acknowledgments from the authors of manuscripts?," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5687-5703, October.
    6. Clemens B. Fell & Cornelius J. König, 2016. "Is there a gender difference in scientific collaboration? A scientometric examination of co-authorships among industrial–organizational psychologists," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 113-141, July.
    7. David Downie & Austin Chinal & Ryan Fritz & Natalie Intemann & Kayla Urbanowski, 2018. "The first 6 years of JESS: categorizing authors and topics," Journal of Environmental Studies and Sciences, Springer;Association of Environmental Studies and Sciences, vol. 8(3), pages 371-375, September.

    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. 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.
    2. Marco Seeber & Alberto Bacchelli, 2017. "Does single blind peer review hinder newcomers?," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 567-585, October.
    3. Kok, Holmer & Faems, Dries & de Faria, Pedro, 2022. "Pork Barrel or Barrel of Gold? Examining the performance implications of earmarking in public R&D grants," Research Policy, Elsevier, vol. 51(7).
    4. Laura Hospido & Carlos Sanz, 2019. "Gender gaps in the evaluation of research: evidence from submissions to economics conferences (Updated March 2020)," Working Papers 1918, Banco de España, revised Mar 2020.
    5. Laura Hospido & Carlos Sanz, 2021. "Gender Gaps in the Evaluation of Research: Evidence from Submissions to Economics Conferences," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 83(3), pages 590-618, June.
    6. Cruz-Castro, Laura & Sanz-Menendez, Luis, 2021. "What should be rewarded? Gender and evaluation criteria for tenure and promotion," Journal of Informetrics, Elsevier, vol. 15(3).
    7. Vicente Safón, 2019. "Inter-ranking reputational effects: an analysis of the Academic Ranking of World Universities (ARWU) and the Times Higher Education World University Rankings (THE) reputational relationship," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 897-915, November.
    8. 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).
    9. 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.
    10. 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.
    11. David Card & Stefano DellaVigna, 2020. "What Do Editors Maximize? Evidence from Four Economics Journals," The Review of Economics and Statistics, MIT Press, vol. 102(1), pages 195-217, March.
    12. Vincent Chandler, 2019. "Identifying emerging scholars: seeing through the crystal ball of scholarship selection committees," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 39-56, July.
    13. Pardeep Sud & Mike Thelwall, 2014. "Evaluating altmetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 1131-1143, February.
    14. Wang, Yukai & Yang, Zhongkai & Liu, Lanjian & Wang, Xianwen, 2020. "Gender bias in patenting process," Journal of Informetrics, Elsevier, vol. 14(3).
    15. Emre Özel, 2024. "What is Gender Bias in Grant Peer review?," Working Papers halshs-03862027, HAL.
    16. 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.
    17. Stephen A Gallo & Joanne H Sullivan & Scott R Glisson, 2016. "The Influence of Peer Reviewer Expertise on the Evaluation of Research Funding Applications," PLOS ONE, Public Library of Science, vol. 11(10), pages 1-18, October.
    18. 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.
    19. Lokman Tutuncu, 2023. "All-pervading insider bias alters review time in Turkish university journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(6), pages 3743-3791, June.
    20. Teplitskiy, Misha & Acuna, Daniel & Elamrani-Raoult, Aïda & Körding, Konrad & Evans, James, 2018. "The sociology of scientific validity: How professional networks shape judgement in peer review," Research Policy, Elsevier, vol. 47(9), pages 1825-1841.

    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:101:y:2014:i:1:d:10.1007_s11192-014-1354-z. 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.