Evidence map›Paper›PMID 39926322›Full record

ArticleThe Russell Sage Foundation journal of the social sciences : RSF2024

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

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

Abstract read
In one paragraph

Article in The Russell Sage Foundation journal of the social sciences : RSF, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Jessica Halliday HardieHunter College and the Graduate Center, City University of New York, United States.ORCID 0000-0002-8085-3884
Alina Arseniev-Koehlerassistant professor of sociology, Purdue University, and postdoctoral fellow of biomedical informatics, University of California, San Diego, United States.ORCID 0000-0003-2544-5607
Judith A SeltzerCalifornia Center for Population Research, University of California, Los Angeles, United States.ORCID 0009-0005-4452-8231
Jacob G Fosterprofessor of informatics and cognitive science, Indiana University, adjunct professor of sociology and faculty fellow at the California Center for Population Research, University of California, Los Angeles, United States, and external professor at the Santa Fe Institute.

Funding

Statistics and Methods CoreR24HD041022 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HANDCOCK, MARK STEPHEN · 2001 to 2016
$10.1M
Scientific and Technical CoreP2CHD041022 · NICHD · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Martha Jane Bailey · 2016 to 2026
$6.9M
NICHD NIH HHS P2C HD041022NICHD NIH HHS R24 HD041022
6 · The paper itself

Abstract

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.

Indexed as

familysocial classsocial institutionstopic modeling

Identifiers

PMID39926322
PMCPMC11804896

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.