Zilberstein, Shira. 2026. “Jurisdictional Gerrymandering: The Authority of Problems without Solutions.” Social Problems. doi:10.1093/socpro/spag024

Abstract: This paper develops the concept of jurisdictional gerrymandering to explain how professionals selectively invoke boundaries around their expertise to frame their role and maintain authority in solving problems that extend beyond their jurisdiction. Drawing on a study of artificial intelligence (AI) model development for healthcare, I analyze how AI practitioners position their work in relation to health equity, an issue they acknowledge cannot be solved through technology. Rather than claiming full authority over equity solutions or deferring to other domains, AI practitioners engage in jurisdictional gerrymandering by critiquing, projecting, and dissolving jurisdiction for different aspects of defining and solving health equity. This process enables them to retain authority to participate in health equity problem solving through moral alignment without accountability for solutions. In contrast to jurisdictional models of professional authority or networked expertise, jurisdictional gerrymandering unbundles defining and solving problems. It reveals a key mechanism through which authority is maintained without asserting control or claiming to be able to achieve solutions. Jurisdictional gerrymandering enables problem frames to continually serve as justifications for technological projects and expert interventions regardless of solutions, shedding light on tensions between innovation, expertise, and responsibility for social problems.

Shira Zilberstein is a PhD candidate in sociology at Harvard University and a fellow in the Science and Technology Studies program at the Harvard Kennedy School. Her research focuses on cultural sociology, science and technology studies and organizations, as well as theory and methods. She is interested in the production, interpretation and evaluation of ideas and the dynamics between hegemonic and counter-hegemonic forms of knowledge in institutional and technical settings. To this end, she has conducted research on grassroots artists, international non-governmental organizations, American college students, academics and journalists. Her dissertation focuses on applied interdisciplinary research collaborations in the field of artificial intelligence. The project studies the ways in which social impact is understood and structured by organizational incentives and decision-making processes that define and seek to address social needs.