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Becoming an Ideologue: Social Sorting and the Microfoundations of Polarization

By on August 1, 2022 in Articles

Craig M. Rawlings

Sociological Science August 1, 2022
10.15195/v9.a13

Abstract

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This article elaborates and tests the hypothesis that the sociopolitical segregation of interpersonal networks (i.e., social sorting) is at the root of recent polarization trends in the United States. After reviewing recent trends, the article outlines the micro-level pathways through which social sorting along sociopolitical lines leads individuals to become more ideological in their identities and attitude structures. It then tests these pathways using panel data from the General Social Survey, which includes detailed measures of individuals’ social ties, ideological identification, and attitudes across a wide array of issues. Results show two dominant pathways through which more socially sorted individuals become more ideological: a short pathway directly linking social sorting to more extreme ideological identities, and a longer pathway linking social sorting to more extreme ideological identities through an increasingly ideological alignment of individuals’ attitude structures. The shorter pathway predominates among conservatives and the longer pathway among liberals. These micro-level pathways are shown to generalize to different macro-level polarization trends in identities and attitude structures for conservatives and liberals. Findings therefore uphold core sociological principles while providing stronger social-structural foundations for a growing body of mainly psychological research on ideological asymmetries.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Craig M. Rawlings: Department of Sociology, Duke University
E-mail: craig.rawlings@duke.edu

Acknowledgments: For helpful comments on earlier drafts, I thank Chris Bail and Clayton Childress. I am grateful for insights provided by several members of Duke University’s Worldview Lab, including Christopher Johnston, Nicholas Restrepo Ochoa, and Steve Vaisey. For useful comments at a conceptual stage of this work, which was presented at the 2019 Network Ecology mini-conference at Stanford University, I thank Delia Baldassarri, Amir Goldberg, John Levi Martin, and Dan McFarland. Any errors or omissions are my own. Address correspondence to Craig M. Rawlings, Dept. of Sociology, Duke University, 270 Reuben-Cooke, 417 Chapel Dr., Durham, NC 27708.

Supplemental Material

  • Citation: Rawlings, Craig M. 2022. “Becoming an Ideologue: Social Sorting and the Microfoundations of Polarization.” Sociological Science 9: 313-345.
  • Received: March 13, 2022
  • Accepted: June 7, 2022
  • Editors: Arnout van de Rijt, Gabriel Rossman
  • DOI: 10.15195/v9.a13


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Concept Class Analysis: A Method for Identifying Cultural Schemas in Texts

By on November 9, 2020 in Articles

Marshall A. Taylor, Dustin S. Stoltz

Sociological Science November 9, 2020
10.15195/v7.a23

Abstract
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Recent methodological work at the intersection of culture, cognition, and computational methods has drawn attention to how cultural schemas can be “recovered” from social survey data. Defining cultural schemas as slowly learned, implicit, and unevenly distributed relational memory structures, researchers show how schemas—or rather, the downstream consequences of people drawing upon them—can be operationalized and measured from domain-specific survey modules. Respondents can then be sorted into “classes” on the basis of the schema to which their survey response patterns best align. In this article, we extend this “schematic class analysis” method to text data. We introduce concept class analysis (CoCA): a hybrid model that combines word embeddings and correlational class analysis to group documents across a corpus by the similarity of schemas recovered from them. We introduce the CoCA model, illustrate its validity and utility using simulations, and conclude with considerations for future research and applications.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Marshall A. Taylor: Department of Sociology, New Mexico State University
E-mail: mtaylor2@nmsu.edu

Dustin S. Stoltz: Department of Sociology and Anthropology, Lehigh University
E-mail: dss219@lehigh.edu

Acknowledgments: A replication repository for this article can be found at: https://github.com/Marshall-Soc/CoCA. We thank Jesper Sørensen, the deputy editor, and the consulting editor for their thoughtful comments on this article.

  • Citation: Taylor, Marshall A., and Dustin S. Stoltz. 2020. “Concept Class Analysis: A Method for Identifying Cultural Schemas in Texts.” Sociological Science 7:544-569.
  • Received: July 31, 2020
  • Accepted: October 4, 2020
  • Editors: Jesper Sørensen, Gabriel Rossman
  • DOI: 10.15195/v7.a23


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