HackerPapers

arXiv:2502.01508physics.soc-ph

Competition and survival in modern academia: A bibliometric case study of theoretical high-energy physics

Jarl Sidelmann, Jesper M. Grimstrup

HN submission. Found in a submission link or body. Submitters do not count as commenters in the main ranking; a submission is not an endorsement.

Abstract

We study the career lengths of researchers in theoretical high-energy physics from 1950 to 2020. Using a cohort-based analysis and bibliometric data from 30,149 authors in three physics disciplines we observe a dramatic increase in the ratio of academic dropouts over time. Where nearly all authors prior to the 1980s remained active more than a decade after their initial publication, this was the case for 50% or less by the 2010s. Consequently, the fraction of theoretical physicists who achieve full academic careers have diminished significantly in the last four decades. Additionally, we study correlations between author survivability and potential success factors, inferring that early author productivity and collaborative efforts have become increasingly strong determinants over time. A logistic regression is utilized to interpret the empirical findings through a survival model. Performance measures further indicate that early career collaboration and productivity rates have emerged as reliable predictors of author survivability during the period in which competition has intensified. Finally, we discuss the potential impacts that these developments may have on science itself.

arXiv comments
37 pages, 7 figures
Journal reference
DOI
Subjects
physics.soc-phPhysics and Society hep-thHigh Energy Physics, Theory

On Hacker News

No comments linking this paper were found in the collected sources. Found in 2 HN submissions from Feb 2025 to Feb 2025. Open submission discussions.

Comments linking this paper, per year.

Discussed in comments0 threads

No comments linking this paper were found in the collected sources. Open submission discussions.

Submitted to Hacker News

Connected through shared HN threads, not inferred similarity or a recommendation.