I am currently an Assistant Professor of Sociology at the University of Minnesota. My research focuses on identifying the structural processes that (re)generate racial health inequality in the United States. Indeed, the stylized question motivating my work to date is, How is it possible that Black Americans have, for as long as we’ve monitored population health, borne a disproportionate share of illness and premature death relative to their White peers? Alongside the efforts of many others, my research has helped make the case that racial health disparities are the consequence of racism that’s deeply embedded in our political, economic, and social systems – an organizing logic that has long motivated institutional actors to extend health-relevant privileges to White communities, but dump hazards onto Black populations, resulting in significant health inequality between the two.

I’ve contributed to this collective project – i.e., of demonstrating a tight link between structural racism and health inequality – in three general ways. One broad “bucket” of my work, for instance, includes several studies which evidence the health impacts of institutions that weigh heavily in the lives of Black Americans. This includes studies which demonstrate the role that the criminal legal system plays in producing vulnerabilities to premature death; how neighborhoods – and the (often racialized) segmenting of resources among them – shape cognitive health as people age; and how historical institutions (e.g., redlining) set the stage for the racial health inequalities we observe today. Another broad category involves studies which demonstrate how structural racism distorts processes that are made to be foundational to well-being in the US – e.g., how social mobility yields differential health benefits for Black and White Americans. And a final class of study consistently found among my record is more explicitly methodological: several of my projects have indeed called attention to the unique tensions that arise when using quantitative data to speak to the production of health inequality.