2024-25 Colloquium Series

UC San Diego Anthropology Department

Misuse of Genetic Ancestry and Race and the Promise of Epigenomics in Resolving Health Inequalities

Biomedical researchers in the US, and often globally, tend to make assumptions about the meaning and use of race and genetic ancestry that can lead to bias in our understanding racial health inequalities. These assumptions include 1) presuming the terms race, ethnicity and ancestry are the same, and conflating these concepts; 2) assuming genetic differences behind chronic diseases without testing relevant alleles; 3) assuming adequate diversity among participants of genetic (and epigenetic) studies, and 4) ignoring social factors, such as structural racism, that can confound associations with a health outcome. These problematic assumptions will be demonstrated through case studies of research on the etiology and treatment of hypertension both in the US and Puerto Rico. Finally, an epigenome-wide study of stress among children of Mexican descent will be briefly discussed as an example to identify mechanisms for racial inequalities in health. 

SSP Grads only

UC Irvine Department of Criminology, Law and Society

Borderland Circuitry: How Racist Gang Profiling on the Street Becomes Hard Data and Enables Land Destruction

Discourse on immigration in the United States has often focused on what is most visible, such as border walls and detention centers, while the information systems that undergird immigration enforcement remain obscure. Tracing the evolution of several surveillance-related systems, Borderland Circuitry investigates how this information infrastructure has shaped immigration enforcement practices since the late 1980s. Specifically, this book talk illuminates three phenomena that are becoming increasingly intertwined: digital surveillance, immigration control, and gang enforcement. Using ethnography, interviews, and analysis of never-before-seen documents, I uncover how information-sharing partnerships between local police, federal law enforcement, and foreign partners collide to create multiple digital borderlands; and how those in power deploy the specter of violent cross-border criminals to justify intensive surveillance, detention, brutality, deportation, and the destruction of land for border militarization.

Assistant Professor of Interdisciplinary Studies, Grand Valley State University and Ph.D. Candidate, Communication, Science Studies, & Critical Gender Studies, UC San Diego

Selling Stigma: Afflictive Power and Fat Oppression

In recent years, a number of scholars and commentators have asserted that the medicalization of fatness is destigmatizing – that portraying fat people as suffering from the disease of obesity will reduce negative societal attitudes and discrimination against them. Even critical Foucauldian theories of medicine have been mobilized to support this claim, rooted in analyses of disciplinary power and biopower. To assess these claims, I investigated the way fat people are depicted and framed in weight stigma research and advocacy that explicitly claims to fight obesity and weight stigma simultaneously. I present one piece of this broader project: an analysis of weight stigma-related media funded by the pharmaceutical company Novo Nordisk, maker of Ozempic. I argue that understanding how medicalization contributes to the oppression of fat people requires going beyond the existing frameworks of disciplinary power and biopower. Rather, weight-stigma related media frequently exerts what I call afflictive power: the capacity to define a way of being as a source of harm or suffering. The exercise of afflictive power stigmatizes fat people by devaluing their way of being and portraying it as antithetical to a good life. Because the medicalization of fatness necessarily depends on afflictive power, it contributes to fat oppression, even if it simultaneously reduces the extent to which individuals are blamed for being fat. Thus, portraying fatness as a disease and combating stigma against fat people are fundamentally incompatible goals.

UC San Diego

Health Data and the Politics of Classification

Biobanks, electronic health records systems, and other large health data infrastructures are proliferating, driving transformations in biomedical research and practice. Beyond the clinic, these datasets are also increasingly seen as the solution for other sorts of problems, and are deployed as training data to develop ML/AI models and algorithmic tools used in insurance markets, in the management of labor, and even in surveillance and policing. 

In this talk, I argue that it is not simply the newly-available quantity of health data, but the relentlessly particular qualities of individual datasets that have been most impactful—and which raise trenchant concerns for social equity and justice. As I will show, decisions about whose data is collected and how they are measured have cyclically reshaped our understanding of human diversity along a number of dimensions. In doing so, these infrastructures are changing our understanding of clinical classifications, and resourcing new ML/AI tools which seek to classify people and populations for other purposes. I make the case that health data represent a unique challenge for both extant data ethics and bioethics frameworks, demanding urgent attention as they are increasingly used to train socially consequential ML/AI technologies in and beyond the clinic.

February 17, 2025

No Meeting: President's Day