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.