Tag Archives | Culture and Cognition

Subjective Political Polarization

Hyunku Kwon, John Levi Martin

Sociological Science November 27, 2023
10.15195/v10.a32


Although the political polarization literature has provided important insights in understanding the structure of political attitudes in the United States at the aggregate level, and how this has changed in recent years, few attempts have been made to examine how each individual subjectively perceives political space and how she locates herself vis-à-vis her political in/out groups at the individual level. To examine such subjective polarization, this paper proposes an approach that examines the trifold relationship between a political actor and the two major political parties. Such relational properties are studied by looking at how each individual locates herself in relation to political in/out groups. Using the American National Election Studies Dataset, this paper sheds new light on the patterns and trends of mass polarization in the United States and demonstrates that subjective polarization has a distinct contribution to partisan animus, or “affective polarization.”
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Hyunku Kwon: Department of Sociology, University of Chicago
E-mail: hyunkukwon@uchicago.edu

John Levi Martin: Department of Sociology, University of Chicago
E-mail: jlmartin@uchicago.edu

Acknowledgements: We thank Eric J. Oliver, Elisabeth Clemens, Oscar Stuhler, Austin Kozlowski, Benjamin Rohr, and Jake Burchard for their comments and suggestions on the earlier draft. We also appreciate the input from the participants of Culture and Action Network. Previous versions of this paper were presented at the meetings of 2020 American Politics Workshop and Politics, History, and Society Workshop at the University of Chicago, and at the 2021 meeting of American Sociological Association.

  • Citation: Kwon, Hyunku, and John Levi Martin. 2023. “Subjective Political Polarization.” Sociological Science 10: 903–929.
  • Received: August 3, 2023
  • Accepted: August 23, 2023
  • Editors: Ari Adut, Peter Bearman
  • DOI: 10.15195/v10.a32


0

Testing Models of Cognition and Action Using Response Conflict and Multinomial Processing Tree Models

Andrew Miles, Gordon Brett, Salwa Khan, and Yagana Samim

Sociological Science March 07, 2023
10.15195/v10.a4


Dual-process perspectives have made substantial contributions to our understanding of behavior, but fundamental questions about how and when deliberate and automatic cognition shape action continue to be debated. Among these are whether automatic or deliberate cognition is ultimately in control of behavior, how often each type of cognition controls behavior in practice, and how the answers to each of these questions depends on the individual in question. To answer these questions, sociologists need methodological tools that enable them to directly test competing claims. We argue that this aim will be advanced by (a) using a particular type of data known as response conflict data and (b) analyzing those data using multinomial processing tree models. We illustrate the utility of this approach by reanalyzing three samples of data from Miles et al. (2019) on behaviors related to politics, morality, and race.
Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Andrew Miles: Department of Sociology, University of Toronto
E-mail: andrew.miles@utoronto.ca

Gordon Brett: Department of Sociology, University of Toronto
E-mail: gordon.brett@alum.utoronto.ca

Salwa Khan: Department of Sociology, University of Toronto
E-mail: slw.khan@mail.utoronto.ca

Yagana Samim: Department of Sociology, University of Toronto
E-mail: yagana.samim@mail.utoronto.ca

Acknowledgments: We wish to thank the reviewers and editors at Sociological Science for their helpful comments.

  • Citation: Miles, Andrew, Gordon Brett, Salwa Khan, and Yagana Samim. 2023. “Testing Models of Cognition and Action Using Response Conflict and Multinomial Processing Tree Models.” Sociological Science 10: 118-149.
  • Received: September 23, 2022
  • Accepted: November 22, 2022
  • Editors: Arnout van de Rijt, Werner Raub
  • DOI: 10.15195/v10.a4


0

Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method

Andrei Boutyline

Sociological Science, May 29, 2017
DOI 10.15195/v4.a15

Measurement of shared cultural schemas is a central methodological challenge for the sociology of culture. Relational Class Analysis (RCA) is a recently developed technique for identifying such schemas in survey data. However, existing work lacks a clear definition of such schemas, which leaves RCA’s accuracy largely unknown. Here, I build on the theoretical intuitions behind RCA to arrive at this definition. I demonstrate that shared schemas should result in linear dependencies between survey rows—the relationship usually measured with Pearson’s correlation. I thus modify RCA into a “Correlational Class Analysis” (CCA). When I compare the methods using a broad set of simulations, results show that CCA is reliably more accurate at detecting shared schemas than RCA, even in scenarios that substantially violate CCA’s assumptions. I find no evidence of theoretical settings where RCA is more accurate. I then revisit a previous RCA analysis of the 1993 General Social Survey musical tastes module. Whereas RCA partitioned these data into three schematic classes, CCA partitions them into four. I compare these results with a multiple-groups analysis in structural equation modeling and find that CCA’s partition yields greatly improved model fit over RCA. I conclude with a parsimonious framework for future work.

Creative Commons LicenseThis work is licensed under a Creative Commons Attribution 4.0 International License.

Andrei Boutyline: Department of Sociology, University of California, Berkeley
Email: boutyline@berkeley.edu

Acknowledgements: This research was supported in part by fellowships from National Science Foundation Graduate Research Fellowship Program and Interdisciplinary Graduate Education and Research Traineeship Program. I thank Ronald Breiger, Neil Fligstein, John Flournoy, Amir Goldberg, Monica Lee, Valden Kamph, James Kitts, Fabiana Silva, Matthew Stimpson, Stephen Vaisey, Robb Willer, and the participants of the Berkeley Mathematical, Analytical, and Experimental Sociology workshop for feedback on the article. I am also grateful to Amir Goldberg for generously discussing RCA and making its software implementation available online. Direct all correspondence to Andrei Boutyline at Department of Sociology, 410 Barrows Hall, University of California, Berkeley, CA 94720. E-mail: boutyline@berkeley.edu

  • Citation: Boutyline, Andrei. 2017. “Improving the Measurement of Shared Cultural Schemas with Correlational Class Analysis: Theory and Method.” Sociological Science 4: 353-393.
  • Received: July 22, 2016
  • Accepted: April 4, 2017
  • Editors: Olav Sorenson, Gabriel Rossman
  • DOI: 10.15195/v4.a15


0
SiteLock