The h-index is no longer an effective correlate of scientific reputation

TL;DR

This study shows that the traditional h-index's effectiveness in measuring scientific reputation has declined, but fractional citation measures like h-frac offer more reliable alternatives, especially when predicting scientific awards.

Contribution

The paper introduces a fractional citation-based measure, h-frac, which outperforms the traditional h-index in correlating with scientific recognition and awards.

Findings

H-index correlation with awards has declined over time.

Fractional citation allocation improves the predictive power of scientometric measures.

H-frac outperforms traditional h-index in predicting scientific awards.

Abstract

The impact of individual scientists is commonly quantified using citation-based measures. The most common such measure is the h-index. A scientist's h-index affects hiring, promotion, and funding decisions, and thus shapes the progress of science. Here we report a large-scale study of scientometric measures, analyzing millions of articles and hundreds of millions of citations across four scientific fields and two data platforms. We find that the correlation of the h-index with awards that indicate recognition by the scientific community has substantially declined. These trends are associated with changing authorship patterns. We show that these declines can be mitigated by fractional allocation of citations among authors, which has been discussed in the literature but not implemented at scale. We find that a fractional analogue of the h-index outperforms other measures as a correlate and predictor of scientific awards. Our results suggest that the use of the h-index in ranking scientists should be reconsidered, and that fractional allocation measures such as h-frac provide more robust alternatives. An interactive visualization of our work can be found at https://h-frac.org