
Abstract The positive effects of increased diversity and inclusion in scientific research and practice are well documented. In this issue, DeVilbiss et al. (Am J Epidemiol. 2020;189(10):998–1010) present findings from a survey used to collect information to characterize diversity among epidemiologists and perceptions of inclusion in the epidemiologic profession. They capture identity across a range of personal characteristics, including race, gender, socioeconomic background, sexual orientation, religion, and political leaning. In this commentary, we assert that the inclusion of political leaning as an axis of identity alongside the others undermines the larger project of promoting diversity and inclusion in the profession and is symptomatic of the movement for “ideological diversity” in higher education. We identify why political leaning is not an appropriate metric of diversity and detail why prioritizing ideological diversity counterintuitively can work against equity building initiatives. As an alternative to ideological diversity, we propose that epidemiologists take up an existing framework for research and practice that centers the voices and perspectives of historically marginalized populations in epidemiologic work.
Epidemiology, Politics, Cultural Diversity
Epidemiology, Politics, Cultural Diversity
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 7 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
