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Record W2496530857 · doi:10.1163/15736121-12341324

More Religion, Less Justification for Violence

2016· article· en· W2496530857 on OpenAlexaff
Joshua D. Wright

Bibliographic record

VenueArchive for the Psychology of Religion · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicReligion, Spirituality, and Psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsPrayerMeaning (existential)Social psychologyPsychology of religionReligiosityArgument (complex analysis)PsychologySociology of religionSociologyReligious studiesSocial sciencePhilosophy

Abstract

fetched live from OpenAlex

A cross-national multilevel analysis was conducted to determine the effects of religion on the extent to which violence is seen as justified against others. Contrary to popular notions that religion causes violence, frequency of prayer, importance of religion, and importance of God were negatively related to justification of violence. Only frequency of service attendance and justification of violence had a positive relationship. This relationship was attenuated when a supernatural meaning system was applied to one's religious beliefs (i.e., religion is primarily for the purpose of making sense of life after death). This meaning system also moderated the relationship between importance of religion and justification of violence. Finally, national-level importance of God moderated the negative relationship between individual level importance of God and justification of violence, strengthening this relationship. Results undermine the constructivist argument for religion as a cause of violence.

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)0.002
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.000

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 head0.052
GPT teacher head0.396
Teacher spread0.343 · 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 designObservational
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

Citations13
Published2016
Admission routes1
Has abstractyes

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