The illusion of scientific talent identification through publication counts: a critical commentary on Haunschild and Bornmann

Abstract

This letter responds to the article by Haunschild and Bornmann, published in the Journal of Informetrics, which proposes a bibliometric framework for identifying promising early-career scientists based on three specific indicators: the number of publications in top-quartile journals (Q1), total publication output (O), and corresponding authorship (C). Using the combined OxQ1 indicator, the authors compile a dataset of 46,200 individuals classified as “potentially talented,” intended to support informed peer review and hiring decisions. This commentary directly examines the methodological assumptions underlying the authors’ indicator selection and their validation strategy. The use of Q1—a journal-level quartile metric—as a proxy for individual research quality is problematic, particularly given the authors’ own acknowledgment of the Journal Impact Factor’s limitations. More critically, the authors’ own validation analysis yields type I and type II error rates of approximately 28–30%, raising serious questions about the OxQ1 combination’s reliability for the talent identification purposes proposed. The reliance on total publication output (O) as a core indicator risks conflating productivity with intellectual contribution, while the public release of a dataset labeling 46,200 researchers as “potentially talented” carries methodological and ethical implications that this letter addresses directly. The argument is not that bibliometrics lacks value, nor that Q1 journals lack quality, but that talent is a capacity which cannot be read off counts of output and journal placement; the letter explains why and points to indicators better suited to assessing individuals.