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Self-Citations and scientific evaluation: Leadership, influence, and performance

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  • Simoes, Nadia
  • Crespo, Nuno

Abstract

The hα index was recently proposed by Hirsch (2019) to measure the degree of scientific leadership. However, as discussed in recent literature, this measure has important shortcomings. We introduce an alternative approach that does not suffer from these limitations. It uses self-citations as a source of information, makes the evaluation at the paper-level, and centers the analysis on the new and broader concept of scientific influence. In each specific paper, the level of scientific influence of an author ranges between 0 and 1 and corresponds to his/her share in the total number of self-citations in that paper. Moreover, we show how this concept can be used to produce a more accurate co-authorship weighting scheme that allows for adjusting the standard measures of scientific performance. This is particularly important in the case of areas in which the alphabetical order of the names is the rule commonly followed, since it provides a way to differentiate the authors according to their role in each paper. We illustrate our method with an empirical example, comparing male and female economists of world top universities. The evidence highlights the existence of substantial gender differences in terms of scientific leadership and scientific influence.

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  • Simoes, Nadia & Crespo, Nuno, 2020. "Self-Citations and scientific evaluation: Leadership, influence, and performance," Journal of Informetrics, Elsevier, vol. 14(1).
    • Handle: RePEc:eee:infome:v:14:y:2020:i:1:s1751157719302640
    DOI: 10.1016/j.joi.2019.100990
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