IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v81y2009i2d10.1007_s11192-008-2189-2.html
   My bibliography  Save this article

The influence of the applicants’ gender on the modeling of a peer review process by using latent Markov models

Author

Listed:
  • Lutz Bornmann

    (ETH Zurich)

  • Rüdiger Mutz

    (ETH Zurich)

  • Hans-Dieter Daniel

    (ETH Zurich
    University of Zurich)

Abstract

In the grant peer review process we can distinguish various evaluation stages in which assessors judge applications on a rating scale. Bornmann & al. [2008] show that latent Markov models offer a fundamentally good opportunity to model statistically peer review processes. The main objective of this short communication is to test the influence of the applicants’ gender on the modeling of a peer review process by using latent Markov models. We found differences in transition probabilities from one stage to the other for applications for a doctoral fellowship submitted by male and female applicants.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:scient:v:81:y:2009:i:2:d:10.1007_s11192-008-2189-2
    DOI: 10.1007/s11192-008-2189-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-008-2189-2
    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/s11192-008-2189-2?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. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2008. "Latent Markov modeling applied to grant peer review," Journal of Informetrics, Elsevier, vol. 2(3), pages 217-228.
    2. 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.
    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. Lutz Bornmann & Hanna Herich & Hanna Joos & Hans-Dieter Daniel, 2012. "In public peer review of submitted manuscripts, how do reviewer comments differ from comments written by interested members of the scientific community? A content analysis of comments written for Atmo," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 915-929, December.
    2. 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.
    3. 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.
    4. 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.
    5. Mingliang Yue & Hongbo Tang & Fan Liu & Tingcan Ma, 2021. "Consistency index: measuring the performances of scholar journal reviewers," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(8), pages 7183-7195, August.

    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. Day, Theodore Eugene, 2015. "The big consequences of small biases: A simulation of peer review," Research Policy, Elsevier, vol. 44(6), pages 1266-1270.
    2. Amy Hinsley & William J Sutherland & Alison Johnston, 2017. "Men ask more questions than women at a scientific conference," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-14, October.
    3. Krawczyk, Michał & Smyk, Magdalena, 2016. "Author׳s gender affects rating of academic articles: Evidence from an incentivized, deception-free laboratory experiment," European Economic Review, Elsevier, vol. 90(C), pages 326-335.
    4. Jonas Lindahl & Cristian Colliander & Rickard Danell, 2020. "Early career performance and its correlation with gender and publication output during doctoral education," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 309-330, January.
    5. Michał Krawczyk & Magdalena Smyk, 2015. "Gender, beauty and support networks in academia: evidence from a field experiment," Working Papers 2015-43, Faculty of Economic Sciences, University of Warsaw.
    6. Shen, Hongquan & Cheng, Ying & Ju, Xiufang & Xie, Juan, 2022. "Rethinking the effect of inter-gender collaboration on research performance for scholars," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Hartshorn, Jessica A. & Brockerhoff, Eckehard G. & Klapwijk, Maartje J. & Marzano, Mariella & Ganley, Rebecca J. & Darr, Molly N., 2023. "Attracting and retaining women in forest entomology and forest pathology," Forest Policy and Economics, Elsevier, vol. 154(C).
    8. Marjolijn N. Wijnen & Jorg J. M. Massen & Mariska E. Kret, 2021. "Gender bias in the allocation of student grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5477-5488, July.
    9. Charles Ayoubi & Michele Pezzoni & Fabiana Visentin, 2021. "Does It Pay to Do Novel Science? The Selectivity Patterns in Science Funding," Science and Public Policy, Oxford University Press, vol. 48(5), pages 635-648.
    10. F. Bartolucci & A. Farcomeni & F. Pennoni, 2014. "Latent Markov models: a review of a general framework for the analysis of longitudinal data with covariates," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(3), pages 433-465, September.
    11. 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.
    12. Chao Zhang & Jiancheng Guan, 2017. "How to identify metaknowledge trends and features in a certain research field? Evidences from innovation and entrepreneurial ecosystem," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1177-1197, November.
    13. 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.
    14. 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).
    15. Magdalena Formanowicz & Marta Witkowska & Weronika Hryniszak & Zuzanna Jakubik & Aleksandra Cisłak, 2023. "Gender bias in special issues: evidence from a bibliometric analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2283-2299, April.
    16. Jordi Duch & Xiao Han T Zeng & Marta Sales-Pardo & Filippo Radicchi & Shayna Otis & Teresa K Woodruff & Luís A Nunes Amaral, 2012. "The Possible Role of Resource Requirements and Academic Career-Choice Risk on Gender Differences in Publication Rate and Impact," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-11, December.
    17. 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.
    18. 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.
    19. Martha M Bakker & Maarten H Jacobs, 2016. "Tenure Track Policy Increases Representation of Women in Senior Academic Positions, but Is Insufficient to Achieve Gender Balance," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-15, September.
    20. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Murgia, Gianluca, 2013. "Gender differences in research collaboration," Journal of Informetrics, Elsevier, vol. 7(4), pages 811-822.

    More about this item

    Statistics

    Access and download statistics

    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:81:y:2009:i:2:d:10.1007_s11192-008-2189-2. 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.