Does gender matter in grant peer review? An empirical investigation using the example of the Austrian Science Fund

Zeitschrift fur Psychologie / Journal of Psychology

Volumn 220, Issue 2, 2012, Pages 121-129

  Mutz, Rüdiger ^a   Bornmann, Lutz ^b   Daniel, Hans Dieter ^a,c  

^a ETH ZURICH   (Switzerland)

^b MAX PLANCK INSTITUTE   (Germany)

^c UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Austrian science fund; Female reviewer salience effect; Gender bias; Grant peer review

Indexed keywords

EID: 84863617974     PISSN: 21908370     EISSN: 21512604     Source Type: Journal    
DOI: 10.1027/2151-2604/a000103     Document Type: Article

References (30)

1. Bauer, D. J. (2009). A note on comparing the estimates of models for cluster-correlated or longitudinal data with binary or ordinal outcomes. Psychometrika, 74, 97-105. doi: 10.1007/S11336-008-9080-1
2. Bornmann, L. (2011). Scientific peer review. Annual Review of Information Science and Technology, 45, 199-245.
3. Bornmann, L., & Daniel, H.-D. (2007a). Reliability, fairness and predictive validity of committee peer review - evaluation of the selection of post-graduate fellowship holders by the Boehringer Ingelheim Fonds. B.I.F. Futura, 19, 7-19.
4. Bornmann, L., & Daniel, H.-D. (2007b). Gatekeepers of science - effects of external reviewers' attributes on the assessments of fellowship applications. Journal of Informetrics, 1, 83-91. doi: 10.1016/j.joi.2006.09.005
5. Bornmann, L., Mutz, R., & Daniel, H.-D. (2007). Gender differences in grant peer review: A meta-analysis. Journal of Informetrics, 1, 226-238. doi: 10.1016/j.joi.2007.03.001
6. Bornmann, L., Mutz, R., & Daniel, H.-D. (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, 2, 280-287.
7. Bornmann, L., Mutz, R., Hug, S. E., & Daniel, H. D. (2011). A meta-analysis of studies reporting correlations between the h index and 37 different h index variants. Journal of Informetrics, 5, 346-359. doi: 10.1016/j.joi.2011.01.006
8. Ceci, S. J., & Williams, W. M. (2011). Understanding current causes of women's underrepresentation in science. Proceedings of the National Academy of Sciences, 108, 3157-3167. doi: 10.1073/pnas.1014871108
9. Fischer, C., & Reckling, F. (2010). Factors influencing approval probability in FWF decision-making procedures. Vienna, Austria: Fonds zur Förderung der wissenschaftlichen Forschung (FWF).
10. Hox, J. J. (2010). Multilevel analysis: Techniques and applications (2nd ed.). New York, NY: Routledge.
11. Hyde, J. S. (2005). The gender similarities hypothesis. American Psychologist, 60, 581-592. doi: 10.1037/0003-066x.60.6.581
12. Jayasinghe, U. W., Marsh, H. W., & Bond, N. (2003). A multilevel cross-classified modelling approach to peer review of grant proposals: The effects of assessor and researcher attributes on assessor ratings. Journal of the Royal Statistical Society Series A (Statistics in Society), 166, 279-300.
13. Kostoff, R. N. (1995). Federal, research impact assessment - axioms, approaches, applications. Scientometrics, 34, 163-206.
14. Littell, R. C., Milliken, G. A., Stroup, W. W., Wolfinger, R. D., & Schabenberger, O. (2006). SAS for mixed models (2nd ed.). Cary, NC: SAS Institute.
15. Maas, C. J. M., & Hox, J. J. (2004). Robustness issues in multilevel regression analysis. Statistica Neerlandica, 58, 127-137. doi: 10.1046/j.0039-0402.2003.00252.x
16. Marsh, H., & Bornmann, L. (2009). Do women have less success in peer review? Nature, 459, 602.
17. Marsh, H. W., Bornmann, L., Mutz, R., Daniel, H. D., & O'Mara, A. (2009). Gender effects in the peer reviews of grant proposals: A comprehensive meta-analysis comparing traditional and multilevel approaches. Review of Educational Research, 79, 1290-1326. doi: 10.3102/0034654309334143
18. Martinson, B. C., Anderson, M. S., Crain, A. L., & de Vries, R. (2006). Scientists' perceptions of organizational justice and self-reported misbehaviors. Journal of Empirical Research on Human Research Ethics, 1, 51-66. doi: 10.1525/jer.2006.1.1.51
19. Marwell, G. (1963). Visibility in small groups. The Journal of Social Psychology, 61, 311-325.
20. McGuire, W. J., McGuire, C. V., & Winton, W. (1979). Effects of household sex composition on the salience of one's gender in the spontaneous self-concept. Journal of Experimental Psychology, 15, 77-90. doi: 10.1016/0022-1031(79)90020-9
21. Moineddin, R., Matheson, F. I., & Glazier, R. H. (2007). A simulation study of sample size for multilevel logistic regression models. BMC Medical Research Methodology, 7. doi: 10.1186/1471-2288-7-34
22. Moreland, R. L., & Levine, J. M. (2003). Group composition: Explaining similarities and differences among group members. In M. A. Hogg & J. Cooper (Eds.), The Sage handbook of social psychology (pp. 367-380). London, UK: Sage.
23. Rudman, L. A., & Glick, P. (2008). The social psychology of gender. London, UK: Guilford Press.
24. Sun, S. Y., Pan, W., & Wang, L. L. (2011). Rethinking observed power concept, practice, and implications. Methodology-European Journal of Research Methods for the Behavioral and Social Sciences, 7, 81-87. doi: 10.1027/1614-2241/A000025
25. Thorngate, W., Dawes, R. M., & Foddy, M. (2009). Judging merit. New York, NY: Psychology Press.
26. Voci, A., Hewstone, M., Crisp, R. J., & Rubin, M. (2008). Majority, minority, and parity: Effects of gender and group size on perceived group variability. Social Psychology Quarterly, 71, 114-142. doi: 10.1111/1467-985X.00278
27. Ward, J. E., & Donnelly, N. (1998). Is there gender bias in research fellowships awarded by the NHMRC7? The Medical Journal of Australia, 169, 21623-21624.
28. Wellcome Trust. (1997). Women and peer review. An audit of the Wellcome Trust's decision-making on grants. London, UK: The Wellcome Trust.
29. Wennerås, C., & Wold, A. (1997). Nepotism and sexism in peerreview. Nature, 387, 341-343. doi: 10.1038/387341a0
30. Ziman, J. (2000). Real science. What it is, and what it means. Cambridge, UK: Cambridge University Press.