Language and socioeconomics predict geographic variation in peer review outcomes at an ecology journal
- 218 Downloads
Papers submitted by scientists located in western nations generally fare better in the peer review process than do papers submitted by scientists from elsewhere. This paper examines geographic variation in peer review outcomes (whether a manuscript is sent for review, review scores obtained, and final decisions by editors) for 3529 submissions over a 4.5 year period at the journal Functional Ecology. In particular, we test whether geographic variation in language and socioeconomics are adequate to explain most or are all of this variation. There was no relationship between the geographic regions of handling editors and the decisions to send papers for review or invite revision, but there was substantial variation among author geographic locations; generally papers from first authors located in Oceania, the United States, and the United Kingdom fared better, and papers from first authors located in Africa, Asia, and Latin America fared worst. Language and the Human Development Index (HDI) explained the geographic variation in the proportion of papers sent for review, but socioeconomics alone (HDI) was the best predictor of mean review scores obtained by papers and whether authors were invited to submit a revision. Though we cannot exclude a role for editor and reviewer biases against authors based on their geographic location, variation in socioeconomics and language explain much of the variation in manuscript editorial and peer review outcomes among authors from different regions of the world.
KeywordsPeer review Language bias Geographic bias Socioeconomics Human development index
Mathematics Subject Classification62P25
JEL ClassificationC12 C13 C14
We thank the British Ecological Society (BES), owners of the journal Functional Ecology, for permitting us to use their peer review database for this project. Brandi Frisby provided comments on an earlier draft of this paper. This work was reviewed and approved by the Internal Review Board at the University of Kentucky, IRB 14-0570-P4S.
- CIA. (2016). The world factbook. Retrieved from https://www.cia.gov/library/publications/the-world-factbook/fields/2098.html.
- Daniel, H.-D. (1993). Fairness in manuscript evaluation (W. E. Russey, Trans.). In Guardians of science: fairness and reliability of peer review (pp. 29–46). Weinheim: VCH Verlagsgesellschaft.Google Scholar
- Field, A., Miles, J., & Field, Z. (2012). Discovering statistics using R. Los Angeles: Sage.Google Scholar
- Fox, J., & Weisberg, S. (2011). An R companion to applied regression (2nd ed.). Thousand Oaks: Sage.Google Scholar
- Harrell, Jr, F. E. (2016). Hmisc: Harrell miscellaneous. R package version 4.0-2. https://CRAN.R-project.org/package=Hmisc.
- Lesnoff, M., and Lancelot, R. (2012). aod: Analysis of overdispersed data. R package version 1.3. http://cran.r-project.org/package=aod.
- Man, J. P., Weinkauf, J. G., Tsang, M., & Sin, D. D. (2004). Why do some countries publish more than others? An international comparison of research funding, English proficiency and publication output in highly ranked general medical journals. European Journal of Epidemiology, 19(8), 811–817.CrossRefGoogle Scholar
- Meyer, D., Zeileis, A., and Hornick, K. (2016). Vcd: Visualizing categorical data. R package version 1.4-3.Google Scholar
- Opthof, T., Coronel, R., & Janse, M. J. (2002). The significance of the peer review process against the background of bias: priority ratings of reviewers and editors and the prediction of citation, the role of geographical bias. Cardiovascular Research, 56(3), 339–346. doi: 10.1016/S0008-6363(02)00712-5.CrossRefGoogle Scholar
- R Core Team. (2016). R: A language and environment for statistical computing. (Version 3.3.1). R foundation for statistical computing. Available at http://www.R-project.org/.
- United Nations Development Programme. (2015). International human development indicators. Retrieved from http://hdr.undp.org/en/countries.
- Uthman, O. A., Wiysong, C. S., Ota, M. O., Nicol, M., Hussey, G. D., Ndumbe, P. M., et al. (2014). Increasing the value of health research in the WHO African Region beyond 2015—reflecting on the past, celebrating the present and building the future: a bibliometric analysis. British Medical Journal Open, 5, e006340. doi: 10.1136/bmjopen-2014-006340.Google Scholar
- Waheed, A. (2012). Why developing countries are lesser innovators. International Journal of Social, Behavioral, Educational, Business and Industrial Engineering, 6(7), 1686–1691.Google Scholar
- Wickham, H. (2007). Reshaping data with the reshape package. Journal of Statistical Software, 21, 1–20. http://www.jstatsoft.org/v21/i12/.
- Wickham, H. (2011). The split-apply-combine strategy for data analysis. Journal of Statistical Software, 40, 1–29. http://www.jstatsoft.org/v40/i01/.
- Wickham, H., and Francois, R. (2016). dplyr: A grammar of data manipulation. R package version 0.5.0. https://CRAN.R-project.org/package=dplyr.