Masters of suspicion: A Bayesian decision model of motivated political reasoning
Open accessAbstract
Motivated reasoning occurs when judgements subserve motives that go beyond accuracy seeking. Substantial evidence indicates that motivated political reasoning is ubiquitous. This is hard to reconcile with computational theories (following Marr's terminology, theories describing the fundamental principles underlying a cognitive process) like Bayesian inference, because these rely on accuracy maximization. Hence, motivated political reasoning is often interpreted as violating computational principles. Here we propose a different view by offering a computational account of motivated political reasoning which relies on the notion of Bayesian decision (instead of Bayesian inference). The key idea is that utility maximization, and not accuracy maximization, drives political thinking. This implies that agents will tend to endorse judgements that serve their instrumental goals even when evidence in support is poor (though agents will still believe their judgements are the most accurate). In this framework, motivated political reasoning is not interpreted as violating computational principles, although its nature is now conceived as pragmatic (i.e., serving instrumental goals) rather than epistemic (i.e., seeking understanding). The paper presents a mathematical description of the theory and shows how this can help interpreting important phenomena in political psychology such contextual priming, stereotyping, and displaced aggression.
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Once groups are ideologically polarized, their members may engage in 'normal' or 'cold' cognitive processes, possibly including Bayesian updating, to maintain or exacerbate motivated differences in beliefs, opinions and values.
“Once groups are ideologically polarized (that is, extreme), their members may engage in ‘normal’ or ‘cold’ cognitive processes, possibly including Bayesian updating, to maintain or exacerbate motivated differences in beliefs, opinions and values61,102–105.”
From Cognitive–motivational mechanisms of political polarization in social-communicative contexts (2022) · cites this paper as [105]
Section 3 describes a Bayesian decision model in which prior beliefs and evidence contribute to motivated political beliefs, while §3.2 explains how people may give greater weight to sources aligned with their ideology. This supports the possibility that ordinary computational processes sustain differences in political beliefs. The cited paper does not specifically establish that these processes maintain or exacerbate differences once groups have become ideologically extreme or polarized. (LLM, conf=0.82)
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Self-citation
- Authors
- Rigoli, F.
- Affiliations
- University of London (GB)
- Corresponding author
- Rigoli, Francesco
- ORCID
- Rigoli, Francesco
- Venue
- Journal for the Theory of Social Behaviour
- Publisher
- Wiley
- Published
- 2021-03-09
- Volume
- 51
- Issue
- 3
- Pages
- 350-370
- ISSN
- 0021-8308 (ISSN-L)
- 1468-5914
- OpenAlex
- W3133858850
- Cited by
- 15
- References
- 46
- Citations by year
- 2026: 1 · 2024: 3 · 2023: 2 · 2022: 7 · 2021: 2
- FWCI
- 2.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Journal for the Theory of Social Behaviour (publishedVersion, cc-by)
- City Research Online (City University London) (acceptedVersion)
- Topics
- Social Sciences › Decision Sciences › General Decision Sciences › Decision-Making and Behavioral Economics
- Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
- Life Sciences › Neuroscience › Cognitive Neuroscience › Psychology of Moral and Emotional Judgment
- Keywords
- motivated reasoning, political reasoning, Bayesian decision model, utility maximization, instrumental goals, contextual priming, stereotyping, displaced aggression, political psychology
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