In my dissertation, I study how statistical tools are adapted to resolve social conflicts.

I focus on the method of meta-analysis, which I trace from its origins in psychology, where it was devised to resolve scientific disagreements, to its uptake in domains of policy, where it has been used to resolve political clashes. My research spans three empirical sites—hospitals, global health NGOs, and the US federal courts—where meta-analysis is increasingly used to make decisions. I introduce the concept of “p-value politics” to theorize how meta-analysis and other statistical tools are used to resolve conflict to the detriment of more inclusive processes of deliberation.

My dissertation’s first empirical chapter on hospitals is based on interviews with surgeons about how they use meta-analysis as the basis for clinical-practice guidelines.

I recently published the findings from this study in a Sociology of Health & Illness article in which I argue that patients, payers, providers, and hospital administrators rely on meta-analysis to settle debate over what counts as a “good” outcome from surgery.

The second chapter of my dissertation is about the rise of actors in global health called “knowledge brokers.”

Knowledge brokers use meta-analysis to resolve conflicts over where aid money should be allocated. As centralized bodies like the WHO lose funding, I argue, meta-analysis becomes essential for synthesizing evaluation studies conducted by local NGOs and determining which among their interventions is worthy of funding.

I approach my dissertation’s third chapter on the US federal courts with mixed methods.

At the 2025 Law and Society Association Annual Meeting, I presented a quantitative analysis of ~100 orders on motions to exclude expert testimony that hinged on meta-analysis from federal court cases. I found that statisticians, when testifying as experts, are held to often contradictory standards. (The cases in my dataset are visualized here.) I contextualize these findings with a qualitative analysis of court transcripts which I presented at the 2025 Society for Social Studies of Science Annual Meeting. In it, I argued that judges are inconsistent when it comes to meta-analysis not because they lack training in statistics, but because of their focus on the conduct of individual, testifying experts rather than on the often contradictory data synthesized in their meta-analyses.

My earlier work focused on health social movements.

In work for my Master’s thesis which was ultimately published in Social Studies of Science, I studied a group of people with type 1 diabetes who engineered an open-source artificial pancreas. My longitudinal digital ethnography of the community filled an important gap in the STS literature by showing how lay expertise could be “routinized” over time.

My interest in health social movements dates to my first research project on how contemporary HIV activists engaged with clinical trials of the novel HIV prevention drug PrEP, which also culminated in a Social Studies of Science paper.

In collaboration with Christine Percheski, I am revisiting HIV PrEP in an ongoing quantitative study of the drug’s accessibility. Percheski and I introduce a measure of PrEP uptake that is better suited to capture variation in rural US counties where data are sparse. I presented work from this project at the Interdisciplinary Association for Population Health Science Conference in 2023. Our novel measure is depicted here as an interactive map.