DLAIMay 17, 2021

A Measure of Research Taste

arXiv:2105.08089v11 citations
Originality Incremental advance
AI Analysis

This addresses the issue of suboptimal incentives in research evaluation for hiring, promotion, and funding decisions, though it is incremental as it builds on prior citation-based metrics.

The paper tackles the problem of citation-based metrics incentivizing excessive publication by introducing CAP, a measure that rewards both productivity and the ability to focus on impactful contributions, resulting in a simple, interpretable metric that produces plausible outcomes across multiple disciplines.

Researchers are often evaluated by citation-based metrics. Such metrics can inform hiring, promotion, and funding decisions. Concerns have been expressed that popular citation-based metrics incentivize researchers to maximize the production of publications. Such incentives may not be optimal for scientific progress. Here we present a citation-based measure that rewards both productivity and taste: the researcher's ability to focus on impactful contributions. The presented measure, CAP, balances the impact of publications and their quantity, thus incentivizing researchers to consider whether a publication is a useful addition to the literature. CAP is simple, interpretable, and parameter-free. We analyze the characteristics of CAP for highly-cited researchers in biology, computer science, economics, and physics, using a corpus of millions of publications and hundreds of millions of citations with yearly temporal granularity. CAP produces qualitatively plausible outcomes and has a number of advantages over prior metrics. Results can be explored at https://cap-measure.org/

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