This is the replication package for the manuscript "Inequality in measuring scholarly success: Variation in the h-index within and between disciplines by Ryan Light, Aaron Gullickson, and Jill Ann Harrison. From the abstract of the paper:
Scholars and university administrators have a vested interest in building equitable valuation systems of academic work for both practical (e.g., resource distribution) and more lofty purposes (e.g., what constitutes “good” research). Well-established inequalities in science pose a difficult challenge to those interested in constructing a parsimonious and fair method for valuation as stratification occurs within academic disciplines, but also between them. The h-index, a popular research metric, has been formally used as one such method of valuation. In this article, we use the case of the h-index to examine how the distribution of research metrics reveal within and between discipline inequalities. Using bibliometric data from 1960-2019 on over 50,000 high performing scientists - the top 2% most frequently cited authors - across 174 disciplines, we construct random effects within-between models predicting the h-index. Results suggest significant within-discipline variation in several forms, specifically sole-authorship and female penalties. Results also show that a sole authorship penalty plays a significant role in well-known between-discipline variation. Field-specific models emphasize the “apples-to-oranges,” or incommensurable, property of cross-discipline comparison with significant heterogeneity in sole-authorship and female penalties within fields. Conclusions include continued caution when using the h-index or similar metrics for valuation purposes.
The analysis is done exclusively in R. All code and data to reproduce the analysis is available in the analysis subdirectory as well as a README that describes the analysis in more detail. The data directory where the data are stored.