The rise of diversity terminology in biomedical research

Recent scholarship has highlighted the rise of "diversity projects" across various educational and business contexts, but few studies have explored the meaning of diversity in biomedical research. In this paper, we employ a computationally driven matching technique to examine quantitative trends in the use of various forms of diversity and population terminology in a sample of nearly two million biomedical abstracts spanning a 30-y period. The curated dictionaries we leverage to detect these trends were formalized into open-source software that are publicly available for other researchers to use. Our analyses demonstrate marked growth in diversity, sex, gender, life course, and socioeconomic terms while terms relating to race and ethnicity largely plateaued or declined in usage, beginning in the mid-2000s. In addition, the use of national, continental, and subcontinental population labels increased dramatically over the same period. We also present logistic regression analyses to investigate what may be fueling the rise in use of diversity terminology. We argue that the use of diversity has grown to encompass concepts beyond its historical origins in race-based programs as it has in fields like higher education and employment. Despite some critics' claims regarding the role of diversity in research, we do not find evidence that its use signals retreat from or commitment to equity and inclusion efforts.

Authors

Institutions

Publication Details

Journal
Proceedings of the National Academy of Sciences
Published
2025-08-19
DOI
https://doi.org/10.1073/pnas.2401805122
Primary Topic
Race, Genetics, and Society
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The rise of diversity terminology in biomedical research

Catherine Lee, Brandon L. Kramer
Proceedings of the National Academy of Sciences
Race, Genetics, and Society
article

The rise of diversity terminology in biomedical research

Catherine Lee, Brandon L. Kramer
article en

Abstract

Recent scholarship has highlighted the rise of "diversity projects" across various educational and business contexts, but few studies have explored the meaning of diversity in biomedical research. In this paper, we employ a computationally driven matching technique to examine quantitative trends in the use of various forms of diversity and population terminology in a sample of nearly two million biomedical abstracts spanning a 30-y period. The curated dictionaries we leverage to detect these trends were formalized into open-source software that are publicly available for other researchers to use. Our analyses demonstrate marked growth in diversity, sex, gender, life course, and socioeconomic terms while terms relating to race and ethnicity largely plateaued or declined in usage, beginning in the mid-2000s. In addition, the use of national, continental, and subcontinental population labels increased dramatically over the same period. We also present logistic regression analyses to investigate what may be fueling the rise in use of diversity terminology. We argue that the use of diversity has grown to encompass concepts beyond its historical origins in race-based programs as it has in fields like higher education and employment. Despite some critics' claims regarding the role of diversity in research, we do not find evidence that its use signals retreat from or commitment to equity and inclusion efforts.

Proceedings of the National Academy of SciencesVol. 122(34)
Rutgers, The State University of New Jersey (US), Rutgers Sexual and Reproductive Health and Rights (NL), Grass Foundation (US), Fondazione GraphiTech (IT)
Openalex Percentile: Top 77%
Race, Genetics, and Society
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.