How two decades of fieldwork and AI are mapping the biology of inequality

Rice University announcement regarding Corey Abramson's 2026-27 CASBS fellowship at Stanford University.

The gap between a cancer diagnosis in a wealthy Houston suburb and one in a lower-income neighborhood is not just financial. It is biological. Patients in disadvantaged communities tend to arrive sicker, respond differently to treatment, and die sooner — patterns that reflect years of accumulated stress, environmental exposure, and unequal access long before they ever see an oncologist.

Mapping how that accumulation actually works — the specific pathways through which social position becomes physical reality — is the career-long project of Corey Abramson, associate professor of sociology at Rice University. This fall, he takes that project to one of the most selective perches in American academia.

A fellowship built for cross-disciplinary work

Abramson has been named a residential fellow at the Center for Advanced Study in the Behavioral Sciences (CASBS) at Stanford University for the 2026-27 academic year. The center, now in its eighth decade, has hosted scholars whose work reshaped fields from economics to cognitive science. Based on publicly available records, Abramson is the first fellow selected while holding a faculty position at Rice in the program's modern era, post-2007.

The fellowship gives him a year of protected time alongside researchers from other disciplines — the kind of sustained, cross-pollinating environment that is vanishingly rare in contemporary academia, where grant cycles and teaching loads crowd out extended thinking.

"Unequal Anatomies" — the book at the center

Abramson's primary project during the fellowship is completing "Unequal Anatomies," a book under contract with Oxford University Press. The work draws on two decades of fieldwork in cancer clinics, dementia care facilities, hospitals, and urban neighborhoods, combined with hundreds of in-depth interviews and large-scale quantitative data.

The book's central argument is that health and life chances don't just correlate with social position — they shape each other in feedback loops that compound over time. A child growing up near industrial pollution develops respiratory problems that limit school attendance, which constrains employment options, which determines neighborhood quality in adulthood, which affects diet, stress, and exposure to further environmental hazards. Each stage makes the next worse. The body keeps a running tab.

What makes Abramson's approach unusual is the methodological range. He pairs the granularity of ethnographic observation — sitting with patients during chemotherapy, accompanying elderly residents through daily routines — with computational analysis capable of detecting patterns across thousands of cases. Each method checks the other. The fieldwork ensures the models reflect real human experience. The computation ensures the stories aren't just anecdotes.

AI tools for qualitative research, built before the hype

The fellowship will also give Abramson dedicated time to refine machine learning and AI-based methods for qualitative health research. His lab at Rice — the Computational Ethnography Lab — began developing these tools before the recent explosion in consumer-facing generative AI, which gives the group a longer perspective on what these technologies can and cannot do for social science.

The promise is real but narrow. AI can help researchers process large volumes of interview transcripts, identify thematic patterns across hundreds of fieldwork notes, and flag connections that might take a human analyst weeks to spot. But the interpretation still requires deep contextual knowledge — the kind that comes from spending years in clinics and neighborhoods, not from training a model on text.

At Rice, Abramson co-directs the Center for Computational Insights on Inequality and Society and mentors students working at the intersection of qualitative research, computation, and public policy. The fellowship extends those collaborations by opening new networks and bringing students' work into broader policy conversations.

What the fellowship cannot do

A year at Stanford does not resolve the fundamental tensions in this kind of research. Combining ethnographic and computational methods means satisfying two audiences with different standards of evidence. Sociologists may question whether algorithms can capture the texture of lived experience. Computer scientists may wonder whether ethnographic samples are large enough to support generalizable claims. Abramson has navigated this tension throughout his career, but the interdisciplinary challenge remains real.

There is also the question of impact. Research that traces how inequality becomes embodied can inform policy — housing decisions, environmental regulations, healthcare access — but the translation from academic insight to political action is slow and uncertain. The structural forces driving health inequality in Houston and elsewhere are not waiting for peer review.

Still, the work addresses a gap that matters. Most health research focuses on biological mechanisms or healthcare delivery. Most inequality research focuses on economic outcomes. The space between — how social disadvantage literally gets under the skin — remains underpopulated by researchers with the training and patience to work in both domains simultaneously.

What it signals for Rice

For Rice University and for Houston, where aging populations, dementia care, and environmental health disparities are pressing concerns, the fellowship reflects institutional momentum. The university has invested in social science that bridges computation and fieldwork, and a CASBS fellowship is among the clearest external validations that investment can produce.

"I see it as a reflection of Rice's investment in rigorous social science and the support I've received since joining the university," Abramson said. "It's also an opportunity to represent Rice in a community where sustained, collaborative scholarship matters."

The year at Stanford begins in fall 2026. The book, when it arrives, will attempt something ambitious: a single, evidence-dense account of how American society writes its inequalities into the bodies of its citizens. Whether that account changes anything beyond the academy will depend on forces well outside any fellowship's control.