Quantifying delayed recognition of scientists

Alex J. Yang, Yiqin Zhang, Zuorong Wang, Hao Wang and Sanhong Deng

Journal of Informetrics, 2025, vol. 19, issue 3

Abstract: Delayed recognition is a significant phenomenon with implications for career advancement, funding opportunities, and the dissemination of scientific knowledge. Despite its importance, most studies have focused on delayed recognition at the paper level, leaving a gap in understanding how this phenomenon unfolds at the level of individual scientists. This paper presents a novel framework for quantifying delayed recognition in scientists by analyzing their career-level citation trajectories. The framework utilizes two key metrics—the author beauty coefficient (AB) and author career awakening time (Atα)—to capture the temporal dynamics of a scientist’s citation impact over the course of their career. Our analysis demonstrates that these metrics reveal patterns distinct from paper-level measures, with no significant correlation to averaged paper delayed recognition scores. Fixed-effect regression analyses indicate that female scientists and those pursuing novel or disruptive research experience greater delays in recognition. Additionally, through Coarsened Exact Matching (CEM) analysis, we find that scientists in smaller groups exhibit higher survival rates in academia but also face more significant delayed recognition. This paper delivers a fresh methodological approach and critical insights into the demographic and research factors driving delayed recognition, enhancing our understanding of scientific impact at the individual level.

Keywords: Delayed Recognition; Citation Trajectories; Innovation; Scientific Careers (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S1751157725000525
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:infome:v:19:y:2025:i:3:s1751157725000525

DOI: 10.1016/j.joi.2025.101688

Access Statistics for this article

Journal of Informetrics is currently edited by Leo Egghe

More articles in Journal of Informetrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().