cover image: Talk of Family: How Institutional Overlap Shapes Family-Related Discourse Across Social Class

20.500.12592/1arvhf6

Talk of Family: How Institutional Overlap Shapes Family-Related Discourse Across Social Class

1 Sep 2024

We develop a novel application of machine learning and apply it to the interview transcripts from the American Voices Project (N = 1,396), using discourse atom topic modeling to explore social class variation in the centrality of family in adults’ lives. We take a two-phase approach, first analyzing transcripts at the person level and then at the line level. Our findings suggest that family, as represented by talk, is more central in the lives of those without a college degree than among the college educated. However, the degree of institutional overlap between family and other key institutions—health, work, religion, and criminal justice—does not vary by education. We interpret these findings in the context of debates about the deinstitutionalization of family in the contemporary United States. This demonstrates the value of a new method for analyzing qualitative interview data at scale. We address ways to expand the use of this method to shed light on educational disparities.
family social institutions social class topic modeling

Authors

Jessica Halliday Hardie, Alina Arseniev-Koehler, Judith A. Seltzer, Jacob G. Foster

DOI
https://doi.org/10.7758/RSF.2024.10.5.07
ISBN
2377-8253 2377-8261
Pages
23
Published in
United States of America
Rights
© 2024 Russell Sage Foundation. Hardie, Jessica Halliday, Alina Arseniev-Koehler, Judith A. Seltzer, and Jacob G. Foster. 2024. “Talk of Family: How Institutional Overlap Shapes Family-Related Discourse Across Social Class.” RSF: The Russell Sage Foundation Journal of the Social Sciences 10(5): 165–87. https://doi.org/10.7758/RSF.2024.10.5.07. This article uses data from the American Voices Project. The authors appreciate the support of the AVP investigators and staff. The authors thank the editors and participants at a Russell Sage Foundation Conference for their helpful comments. They also thank Sarah Damaske and Carrie Shandra for their constructive feedback. This project was supported in part by the California Center for Population Research at UCLA (CCPR), which receives core support (P2C- HD041022) from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD). The content is solely the responsibility of the authors

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