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Record W4237631515 · doi:10.31234/osf.io/tjn3e

Appealing to the minds of gods: Religious beliefs and appeals correspond to features of local social ecologies

2021· preprint· en· W4237631515 on OpenAlexfundno aff
Theiss Bendixen, Coren L. Apicella, Quentin D. Atkinson, Emma Cohen, Joseph Henrich, Rita Anne McNamara, Ara Norenzayan, Aiyana K. Willard, Dimitris Xygalatas, Benjamin Grant Purzycki

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaAarhus Universitets ForskningsfondMax-Planck-GesellschaftAarhus UniversitetJohn Templeton Foundation
KeywordsEthnographyVariation (astronomy)Set (abstract data type)SociologyField (mathematics)Cognitive science of religionEpistemologyCognitionSocial psychologyKey (lock)PsychologySocial scienceAnthropologyEcologyPhilosophyComputer science

Abstract

fetched live from OpenAlex

How do beliefs about gods vary across populations, and what accounts for this variation? We argue that appeals to gods generally reflect prominent features of local social ecologies. We first draw from a synthesis of theoretical, experimental, and ethnographic evidence to delineate a set of predictive criteria for the kinds of contexts with which religious beliefs and behaviors will be associated. To evaluate these criteria, we examine the content of freely-listed data about gods’ concerns collected from individuals across eight diverse field sites and contextualize these beliefs in their respective cultural milieus. In our analysis, we find that local deities’ concerns point to costly threats to local coordination and cooperation. We conclude with a discussion of how alternative approaches to religious beliefs and appeals fare in light of our results and close by considering some key implications for the cognitive and evolutionary sciences of religion.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.020
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.020
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.007
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.018
GPT teacher head0.319
Teacher spread0.300 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations14
Published2021
Admission routes1
Has abstractyes

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