A new article by Marek Kwiek and Łukasz Szymula has been accepted for publication in “Quantitative Science Studies”, a journal ranked in the 99th percentile of the Scopus journals list!

The article is about “Quantifying Lifetime Productivity Changes: A Longitudinal Study of 320,000 Late-Career Scientists” and is available now from ArXiv here.

Marek Kwiek and Lukasz Szymula (2025). Quantifying Lifetime Productivity Changes: A Longitudinal Study of 320,000 Late-Career Scientists. Quantitative Science Studies (in press). Available ahead of print from: https://arxiv.org/abs/2404.16835

Abstract

The present study focuses on persistence in research productivity over the course of an individual’s entire scientific career. We track ‘late-career’ scientists – scientists with at least 25 years of publishing experience (N=320,564) – in 16 STEMM (science, technology, engineering, mathematics, and medicine) and social science disciplines from 38 OECD countries for up to five decades. Our OECD sample includes 79.42% of late-career scientists globally. We examine the details of their mobility patterns as early-career, mid-career, and late-career scientists between decile-based productivity classes, from the bottom 10% to top 10% of the productivity distribution. Methodologically, we turn a large-scale bibliometric dataset (Scopus raw data) into a comprehensive, longitudinal data source for research on careers in science. The global science system is highly immobile: half of global top performers continue their careers as top performers and one-third of global bottom performers as bottom performers. Jumpers-Up and Droppers-Down are extremely rare in science. The chances of moving radically up or down in productivity classes are marginal (1% or less). Our regression analyses show that productivity classes are highly path dependent: there is a single most important predictor of being a top performer, which is being a top performer at an earlier career stage.

Abstract

The present study focuses on persistence in research productivity over the course of an individual’s entire scientific career. We track ‘late-career’ scientists – scientists with at least 25 years of publishing experience (N=320,564) – in 16 STEMM (science, technology, engineering, mathematics, and medicine) and social science disciplines from 38 OECD countries for up to five decades. Our OECD sample includes 79.42% of late-career scientists globally. We examine the details of their mobility patterns as early-career, mid-career, and late-career scientists between decile-based productivity classes, from the bottom 10% to top 10% of the productivity distribution. Methodologically, we turn a large-scale bibliometric dataset (Scopus raw data) into a comprehensive, longitudinal data source for research on careers in science. The global science system is highly immobile: half of global top performers continue their careers as top performers and one-third of global bottom performers as bottom performers. Jumpers-Up and Droppers-Down are extremely rare in science. The chances of moving radically up or down in productivity classes are marginal (1% or less). Our regression analyses show that productivity classes are highly path dependent: there is a single most important predictor of being a top performer, which is being a top performer at an earlier career stage.