Abstract
Researchers debate the extent of issue polarization in the United States, as well as what role (if any) social identities such as partisanship and religion play in issue polarization. In an effort to answer these questions, we develop a theory that social identities may lead to issue polarization, as long as identifiers have the constraint necessary to connect their identities to each issue. Using this theory, we hypothesize that partisanship should structure polarization on nearly any salient issues, while the impact of religious identities should be concentrated among cultural issues. We then introduce an original measure of issue polarization that allows us to capture the "depth" of issue polarization on five cultural issues (abortion, same-sex marriage, teaching Intelligent Design in public schools, displaying the Ten Commandments on government property, and anti-transgender bathroom bills) and five non-cultural issues (welfare, healthcare, immigration, the environment, and the size of the military). Relying on data from an original survey fielded in February 2020, we find evidence that a sizeable minority of the population holds polarized views on each issue. In addition, we find that partisanship structures polarization on nearly all of these issues, while religion's impact is mostly concentrated on cultural issues. Our findings help clarify academic debates about the origins and extent of issue polarization by demonstrating that a sizeable minority of the public holds polarized views on these issues, and that social identities such as partisanship and religion are important factors in that polarization.
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Source: Weighted 2020 Dynata data
Source: Weighted 2020 Dynata data
Source: Weighted 2020 Dynata data
Source: Weighted 2020 Dynata data
Source: Weighted 2020 Dynata data
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Notes
Details on the weighting procedure are available in Online Appendix C.
Thus, the present study cannot speak to attitudes when the questions do not frame the issues, or how various frames influence levels of polarization, but these questions present a natural topic for further research.
Bivariate effects are shown in Online Appendix D. In the body of the paper, we focus on multivariate analysis in order to guard against presentation of spurious relationships as well as to save space.
Religious commitment is a scale of frequency of attendance, frequency of prayer, and religious guidance, all recoded to range from 0 to 1. To preserve cases, missing values were replaced with the mean of that individual's non-missing values. All items loaded strongly on one factor, with an eigenvalue of 2.07, explaining 69% of the total variation. Cronbach's alpha is .775, indicating the scale is quite reliable. In the model, the religious tradition dummy variables represent the difference between evangelicals and the group indicated when attendance is zero, religious commitment is the effect of commitment among evangelicals, and the tradition X commitment interactions represent the change in the effect of attendance for the tradition indicated. Religious tradition was measured via self-identification with broad categories such as "Protestant Christian." Protestants who were Black were assigned to the Black Protestant tradition, and non-Black Protestants who answered yes to a follow-up question asking whether they considered themselves "a born-again or evangelical Christian" were assigned to the Evangelical category. Burge and Lewis (2018) find that this approach yields similar results to the full denominational battery used in large surveys like the ANES and GSS. Full details on coding and question wording are available in Online Appendix B.
As is standard practice in the religion and politics literature, we do not include a dummy variable for African Americans because nearly all African Americans are Black Protestants, and if both dummy variables were included it would create severe multicollinearity.
Overlapping 95% confidence intervals create an overly conservative test of statistical difference, providing a type I error rate of .006 rather than the conventionally desired .05 (Maghsoodloo and Huang 2010; Payton et al. 2003; Schenker and Gentleman 2001). These authors recommend using 83.5 percent confidence intervals to achieve type I error rates of five percent (we round up to 85% for convenience).
Notably, Fiorina et al. (2011) do not include the unaffiliated in their analysis, which likely contributes to their finding of minimal religious group differences on abortion.
We thank one of the anonymous reviewers for raising this point.
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Acknowledgements
The authors would like to thank our colleagues, Candice Ortbals, the editors, and the four anonymous reviewers for their helpful comments. This research was partially supported by a grant from Pepperdine University's Office of the Vice Provost. Of course, any remaining errors are our own.
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Replication data for this study can be found at: https://doi.org/10.7910/DVN/IVLUBU.
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Castle, J.J., Stepp, K.K. Partisanship, Religion, and Issue Polarization in the United States: A Reassessment. Polit Behav 43, 1311–1335 (2021). https://doi.org/10.1007/s11109-020-09668-5
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DOI: https://doi.org/10.1007/s11109-020-09668-5