Extreme inequalities of citation counts in environmental sciences

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1 Department of Biological Sciences, National University of Singapore, Singapore, Singapore
2 Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
3 Yale-NUS College, National University of Singapore, Singapore, Singapore
DOI
10.7287/peerj.preprints.265v1
Published
Accepted
Subject Areas
Ethical Issues, Science Policy
Keywords
Matthew effect, preferential attachment, h-index, research merit, rich get richer, role-based h-index.
Copyright
© 2014 Chimalakonda et al.
Licence
This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ PrePrints) and either DOI or URL of the article must be cited.
Cite this article
Chimalakonda D, Cook AR, Carrasco LR. 2014. Extreme inequalities of citation counts in environmental sciences. PeerJ PrePrints 2:e265v1

Abstract

Well-established scientists are expected to be more likely to have their work recognised than early-career individuals and thus receive more citations. Estimating the degree of inequality in citation counts in environmental sciences can help identify the dynamics behind citation inequalities. Using the scientific profiles of researchers in the Google Scholar database, we estimated the inequality in the distribution of citations in the disciplines of evolutionary biology, conservation biology and ecology. The data were modelled using short-tailed (exponential) and long-tailed power-law (Pareto) distributions. The inequality in performance in each distribution was assessed using Gini coefficients. Citations counts per researcher presented Gini coefficients of 0.83–0.84, indicating extreme inequality. The results suggest that the reinforcement in citation counts due to seniority and previous success might be very strong. To produce meaningful comparisons of actual research impact using citation counts, factors such as lab size, collaborations or role in articles should ideally be controlled for.

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