2023 Grant Recipients

Fictional TV Preferences and U.S. Political Polarization, 2012-2023

tess_mcnulty_headshot.jpg

Co-authors:  Hoyt Long (UChicago)

Throughout the past decade, critics and scholars alike have raised the alarm about rising rates of political polarization in the United States. Multiple studies have focused on the role that media have played in this process, showing how Americans' preferences for different types of web and TV-based news provide evidence for, and exacerbate, polarization. Far fewer studies, however, have asked similar questions about preferences for non-news entertainment, despite the fact that fictional media—from primetime TV serials to bestselling novels—attract as many, if not more consumers than news. Almost no studies, moreover, have approached relationships between fictional media and political partisanship from particularly humanistic or cultural-critical perspectives: looking closely, not only at popular fictions' thematics, but also at their more aesthetic features, including character, setting, narrative structure, and linguistic style.

In this project, we propose to begin to fill this gap in the research, by studying American fictional television preferences across party lines, with particular attention to the aesthetics that have characterized Democrat and Republican-favored programming, during the past ten years of rising polarization. We will draw on a dataset of Nielsen TV ratings—supplemented by a few other data sources—to track monthly state and county-level viewership for the most watched shows in the years 2012-2022. Using this data, we will assess whether there are statistically meaningful correlations between high rates of viewership for individual programs, and Democrat and Republican voting records, at county and state levels. Here, we expect to expand on results of earlier studies, showing, for example, that Republicans have favored police procedurals and reality TV, while Democrats have favored sitcoms or savvy comedies. Once any correlations are determined, we will locate aesthetic features that characterize the "Blue" and "Red" programs, attending, for example, to narrative structure, character-type, and genre, and using methods of both "close" and "distant" (or computational) reading. In this way, we will expand the current work on the role that media plays in reflecting and affecting partisan divides."

A Health Equity Approach to Characterizing the Menstrual Epigenome

headshotrivera.jpeg

This project will develop self-collection methods and computational approaches for analyzing the menstrual epigenome. It lays the methodological groundwork for a broader interdisciplinary project examining the impact of life course stressors and the impact of social inequity on the molecular biology of menstrual effluent. 

Menstrual effluent is the tissue of the shed endometrial lining; several studies have shown it is a powerful proxy for endometrial tissue at a cellular level, but there are no standardized methods for its collection or developed scalable bioinformatic pipelines for its analysis. Current research in this area is limited by the need for in-person collection as well as labor-intensive laboratory methods to characterize its functional composition and epigenome. Lack of knowledge about menstruating individuals' preferences for collection, the impact of collection methods on sample biology, and stigma regarding menstruation have also limited menstrual biomarker development. 

Our research addresses these limitations by 1) developing scalable and remote self-collection methods for menstrual effluent and 2) developing computational analytic approaches for menstrual effluent using DNA methylation deconvolution algorithms that characterize its cellular (focusing on the immune compartment) composition. 

This project benefits from the interdisciplinary expertise available at Dartmouth: PI Luisa Rivera is a current Neukom Postdoctoral Scholar in the Department of Anthropology whose research program focuses on epigenetic research with translations to population health equity and that centers participant ethics, experiences and meaning-making. She is co-mentored by Brock Christensen at the Christensen Lab, which has developed cutting edge computational techniques for cellular deconvolution of multiple tissues using DNA methylation microarrays. Participant-centered and critical biocultural analysis will be supported by the co-mentorship of Zaneta Thayer, an expert in the impacts of life course stress on reproductive physiology and the anthropology of social epigenetics. The Dartmouth MShop at Thayer of Engineering will also collaborate on product design and development.