Abstract
Many cognitive and evolutionary theories of religion argue that supernatural explanations are byproducts of our cognitive adaptations. An influential argument states that our supernatural explanations result from a tendency to generate anthropomorphic explanations, and that this tendency is a byproduct of an error management strategy because agents tend to be associated with especially high fitness costs. We propose instead that anthropomorphic and other supernatural explanations result as features of a broader toolkit of well-designed cognitive adaptations, which are designed for explaining the abstract and causal structure of complex, unobservable, and uncertain phenomena that have substantial impacts on fitness. Specifically, we argue that (1) mental representations about the abstract vs. the supernatural are largely overlapping, if not identical, and (2) when the data-generating processes for scarce and ambiguous observations are complex and opaque, a naive observer can improve a bias-variance trade-off by starting with a simple, underspecified explanation that Western observers readily interpret as “supernatural.” We then argue that (3) in many cases, knowledge specialists across cultures offer pragmatic services that involve apparently supernatural explanations, and their clients are frequently willing to pay them in a market for useful and effective services. We propose that at least some ethnographic descriptions of religion might actually reflect ordinary and adaptive responses to novel problems such as illnesses and natural disasters, where knowledge specialists possess and apply the best available explanations about phenomena that would otherwise be completely mysterious and unpredictable.
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Notes
Our distinction here is similar to the one made in Sperber (1997) between intuitive and reflective beliefs. Intuitive beliefs, akin to mental models, are the representational output of cognition resulting from the mind’s architecture. Reflective beliefs, akin to explanations, are higher-order propositions, the sources and contents of which are evaluated using a lexicon of preexisting beliefs (which are often cultural). Our occasional use of the term explanatory models emphasizes the representational nature of explanations, but it is critical to keep in mind that these representations, while informed a great deal by internal cognitive models of the world, are ultimately communicated to others. In other words, they are public, rather than private, representations (see also Sperber, 1996).
The “ordered matter” in this context refers to its low entropy, in contrast to chaotic or randomly distributed matter.
Abductive inference was proposed and discussed by C. S. Peirce (e.g., 1958) as a type of inference that complements others, such as inductive and deductive modes of inference.
Strictly speaking, and to reiterate the distinction made at the outset of the section on Explanations, our use of the term “models” in this context refers to explanatory models, and should not be confused with mental models. We made this distinction above by suggesting that explanations are higher-level and socially communicated models, or public representations, compared to lower-level mental models, or private representations. Nevertheless, in some cases, explanatory models might strongly resemble the mental models that generated them. We revisit this possibility further below.
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Acknowledgements
ADL and EHH acknowledge funding from the Issachar Fund and Templeton Religion Trust on the Religion and Science as Meaning-Making Systems project, and ADL acknowledges funding from the Aarhus University Research Foundation. We thank Michael Barlev, Theiss Bendixen, Pascal Boyer, Cynthiann Heckelsmiller, Kevin Hong, Martin Lang, Ben Purzycki, Tadeg Quillien, Uffe Schjødt, Kristen Syme, Jesper Sørensen, Michael Winkelman, the Religion, Cognition, and Culture team, and two anonymous reviewers for helpful comments and feedback during the development of this manuscript.
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Lightner, A.D., Hagen, E.H. All Models Are Wrong, and Some Are Religious: Supernatural Explanations as Abstract and Useful Falsehoods about Complex Realities. Hum Nat 33, 425–462 (2022). https://doi.org/10.1007/s12110-022-09437-9
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DOI: https://doi.org/10.1007/s12110-022-09437-9