No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Digital and computational demography
... Digitalized scholarly databases with bibliometric information are a new source for studying scientists as a population, even though they first need to be repurposed to focus on individual scientists rather than individual publications. This allows for the exploration of questions about science and scientists at an unprecedented level of detail (Kashyap et al., 2023;Liu et al., 2023;Wang & Barabási, 2021). Individuals can be studied according to age, seniority, gender, discipline, and institutional type-and most importantly, for the present study, scientists can be tracked over time. ...
... Attrition in science can be quantified beyond individual institutions and countries, and largescale datasets can be used for this purpose. Global and longitudinal approaches to academic (publishing) careers have only recently been made possible by increasing access to digital databases with comprehensive information about scientists, their research outputs, and their citation-based impact on global scholarly conversations (Kashyap et al., 2023;Wang & Barabási, 2021). The advent of new digital datasets, access to immense computing power, and a more general turn toward structured big data in social science research have led to a recent explosion of studies about the various aspects of academic careers, with an impressive line of research focused on the differences between men and women in science from various perspectives (e.g., King et al., 2017;Nielsen & Andersen, 2021;Sugimoto & Larivière, 2023). ...
In this paper, we explore how members of the scientific community leave academic science and how attrition (defined as ceasing to publish) differs across genders, academic disciplines, and over time. Our approach is cohort-based and longitudinal: We track individual male and female scientists over time and quantify the phenomenon traditionally referred to as “leaving science.” Using publication metadata from Scopus—a global bibliometric database of publications and citations—we follow the details of the publishing careers of scientists from 38 OECD countries who started publishing in 2000 (N = 142,776) and 2010 (N = 232,843). Our study is restricted to 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine), and we track the individual scholarly output of the two cohorts until 2022. We use survival analysis to compare attrition of men and women scientists. With more women in science and more women within cohorts, attrition is becoming ever less gendered. In addition to the combined aggregated changes at the level of all STEMM disciplines, widely nuanced changes were found to occur at the discipline level and over time. Attrition in science means different things for men versus women depending on the discipline; moreover, it means different things for scientists from different cohorts entering the scientific workforce. Finally, global bibliometric datasets were tested in the current study, opening new opportunities to explore gender and disciplinary differences in attrition.
... Digitalized scholarly databases with bibliometric information are a new source for studying scientists as a population, even though they first need to be repurposed to focus on individual scientists rather than individual publications. This allows for the exploration of questions about science and scientists at an unprecedented level of detail (Kashyap et al., 2023;Liu et al., 2023;Wang & Barabási, 2021). Individuals can be studied according to age, seniority, gender, discipline, and institutional type-and most importantly, for the present study, scientists can be tracked over time. ...
... Attrition in science can be quantified beyond individual institutions and countries, and largescale datasets can be used for this purpose. Global and longitudinal approaches to academic (publishing) careers have only recently been made possible by increasing access to digital databases with comprehensive information about scientists, their research outputs, and their citation-based impact on global scholarly conversations (Kashyap et al., 2023;Wang & Barabási, 2021). The advent of new digital datasets, access to immense computing power, and a more general turn toward structured big data in social science research have led to a recent explosion of studies about the various aspects of academic careers, with an impressive line of research focused on the differences between men and women in science from various perspectives (e.g., King et al., 2017;Nielsen & Andersen, 2021;Sugimoto & Larivière, 2023). ...
In the present research, we explore how members of the global scientific community leave academic science and how attrition differs across genders, academic disciplines, and over time. Our approach is global, cohort-based, and longitudinal: we track individual male and female scientists over time and quantify the phenomenon traditionally referred to as “leaving science.” Using publication metadata from Scopus—a global bibliometric database of publications and citations—we follow the details of the publishing careers of scientists who started publishing in 2000 (N = 142,776) and 2010 (N = 232,843). Our study is restricted to 16 STEMM disciplines (science, technology, engineering, mathematics, and medicine), and we track the individual scholarly output of the two cohorts until 2022. Survival analyses show that attrition becomes ever less gendered, while regression models show that publication quantity is more consequential than publication quality for careers. Behind the aggregated changes at the level of all STEMM disciplines combined, widely nuanced changes were found to occur at the level of disciplines and over time. Attrition in science means different things for men versus women depending on the discipline; moreover, it means different things for scientists from different cohorts entering the scientific workforce. Finally, global bibliometric datasets were tested in this study, opening new opportunities to explore gender and disciplinary differences in attrition.
We examine biologists leaving science in 38 OECD countries in the past two decades. In a cohort‐based and longitudinal fashion, we follow individuals over time, from their first publication ( N = 86 178). We examine four disciplines: AGRI (agricultural, biological sciences), BIO (biochemistry, genetics, molecular biology), IMMU (immunology, microbiology), and NEURO (neuroscience). Our Kaplan–Meier survival analysis of BIO shows that 60% of women are still in science after 5 years, 40% after 10 years, and only 20% after 19 years. Women in BIO are 23.26% more likely than men to leave science after 10 years and 39.74% after 19 years. Gender differences increase consistently in later career stages. They are high, but comparing the 2000 and 2010 cohorts, have slightly decreased over time.
This study examines biologists leaving science in 38 OECD countries in the past two decades. We use publication metadata from a global bibliometric database (raw Scopus data at the micro-level of individual scientists). In a cohort-based and longitudinal fashion, we follow individual men and women scientists over time, from their first to their last publication (N=86,178). We examine four academic disciplines: AGRI (agricultural and biological sciences), BIO (biochemistry, genetics, and molecular biology), IMMU (immunology and microbiology), and NEURO (neuroscience). We apply survival analysis, conceptualizing scientific life as a sequence of scholarly publishing events. Our Kaplan-Meier survival analysis shows how women disappear from science: in BIO, about 60% are still in science after 5 years, 40% after 10 years, and only 20% by the end of the period examined (i.e., after 19 years). The percentages are substantially higher for men: approximately 70%, 50%, and 30%, respectively. Kaplan-Meier estimations indicate that women in the largest discipline (BIO) are 23.26% more likely to leave science after 10 years and 39.74% more likely to leave science at the end of the study period. Gender difference in attrition, slightly visible after 5 years, increase consistently in later career stages. The probability of surviving for women after 15 years varies considerably, from 47.8% in AGRI to 27.6% in IMMU; for men, the probability is about a fifth higher. Our data show that with the passage of time, women disappear from science in ever-larger proportions compared to men. Gender differences in attrition in the four disciplines have been and continue to be high, but comparing the 2000 and 2010 cohorts, have slightly decreased over time.
ResearchGate has not been able to resolve any references for this publication.