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Record W4366236677 · doi:10.1177/09567976231158576

Thinking About God Encourages Prosociality Toward Religious Outgroups: A Cross-Cultural Investigation

2023· article· en· W4366236677 on OpenAlexafffund
Michael H. Pasek, John Kelly, Crystal Shackleford, Cindel White, Allon Vishkin, Julia M. Smith, Ara Norenzayan, Azim Shariff, Jeremy Ginges

Bibliographic record

VenuePsychological Science · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEvolutionary Game Theory and Cooperation
Canadian institutionsUniversity of British ColumbiaYork University
FundersSocial Sciences and Humanities Research Council of CanadaTempleton Religion TrustNational Science Foundation
KeywordsIngroups and outgroupsOutgroupPsychologySocial psychologyGroup conflictProsocial behaviorIn-group favoritismJudaismHinduismSocial groupSocial identity theoryTheology

Abstract

fetched live from OpenAlex

Most humans believe in a god or gods, a belief that may promote prosociality toward coreligionists. A critical question is whether such enhanced prosociality is primarily parochial and confined to the religious ingroup or whether it extends to members of religious outgroups. To address this question, we conducted field and online experiments with Christian, Muslim, Hindu, and Jewish adults in the Middle East, Fiji, and the United States ( N = 4,753). Participants were given the opportunity to share money with anonymous strangers from different ethno-religious groups. We manipulated whether they were asked to think about their god before making their choice. Thinking about God increased giving by 11% (4.17% of the total stake), an increase that was extended equally to ingroup and outgroup members. This suggests that belief in a god or gods may facilitate intergroup cooperation, particularly in economic transactions, even in contexts with heightened intergroup tension.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.513
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0030.004
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.083
GPT teacher head0.448
Teacher spread0.364 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations31
Published2023
Admission routes2
Has abstractyes

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