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The Higher Power of Religiosity Over Personality on Political Ideology

  • Aleksander KsiazkiewiczEmail author
  • Amanda Friesen
Original Paper

Abstract

Two streams of research, culture war and system justification, have proposed that religious orientations and personality, respectively, play critical roles in political orientations. There has been only limited work integrating these two streams. This integration is now of increased importance given the introduction of behavior-genetic frameworks into our understanding of why people differ politically. Extant research has largely considered the influence of personality as heritable and religiosity as social, but this view needs reconsideration as religiosity is also genetically influenced. Here we integrate these domains and conduct multivariate analyses on twin samples in the U.S. and Australia to identify the relative importance of genetic, environmental, and cultural influences. First, we find that religiosity’s role on political attitudes is more heritable than social. Second, religiosity accounts for more genetic influence on political attitudes than personality. When including religiosity, personality’s influence is greatly reduced. Our results suggest religion scholars and political psychologists are partially correct in their assessment of the “culture wars”—religiosity and ideology are closely linked, but their connection is grounded in genetic predispositions.

Keywords

Religion Religiosity Personality Ideology Attitudes Genetics 

Notes

Funding

The U.S. data employed in this project were collected with the financial support of the National Science Foundation in the form of SES-0721378, PI: John R. Hibbing; Co-PIs: John R. Alford, Lindon J. Eaves, Carolyn L. Funk, Peter K. Hatemi, and Kevin B. Smith, and with the cooperation of the Minnesota Twin Registry at the University of Minnesota, Robert Krueger and Matthew McGue, Directors. The Australian data employed in this project were collected with the financial support of the National Science Foundation (SES-0729493 and SES-0721707). PIs: John R. Alford, Peter K. Hatemi, John R. Hibbing, Nicholas Martin and Kevin B. Smith. The analyses in this paper were made possible in part by training received at workshops held at the Institute for Genomic Biology at the University of Colorado Boulder and funded by the National Science Foundation (SES-0921008 and SES-1259678). All analysis scripts are available on Dataverse ( https://doi.org/10.7910/DVN/YBCZHI). We would like to thank Peter Hatemi and Claire Gothreau for their very helpful comments on earlier versions of this project.

Supplementary material

11109_2019_9566_MOESM1_ESM.docx (402 kb)
Supplementary material 1 (DOCX 401 kb)

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Authors and Affiliations

  1. 1.University of Illinois at Urbana-ChampaignUrbanaUSA
  2. 2.IUPUIIndianapolisUSA

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