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Record W2905024522 · doi:10.1177/0146167218808502

The Content and Correlates of Belief in Karma Across Cultures

2018· article· en· W2905024522 on OpenAlexafffundabout
Cindel White, Ara Norenzayan, Mark Schaller

Bibliographic record

VenuePersonality and Social Psychology Bulletin · 2018
Typearticle
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of British Columbia
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsKarmaPsychologySocial psychologyAttributionJust-world hypothesisCausationContext (archaeology)Economic JusticeCultural diversityBelief in GodSocial cognitionEpistemologyCognitionSociologyAnthropologyTheology

Abstract

fetched live from OpenAlex

Karmic beliefs, centered on the expectation of ethical causation within and across lifetimes, appear in major world religions as well as spiritual movements around the world, yet they remain an underexplored topic in psychology. In three studies, we assessed the psychological predictors of Karmic beliefs among participants from culturally and religiously diverse backgrounds, including ethnically and religiously diverse students in Canada, and broad national samples of adults from Canada, India, and the United States (total N = 8,996). Belief in Karma is associated with, but not reducible to, theoretically related constructs including belief in a just world, belief in a moralizing God, religious participation, and cultural context. Belief in Karma also uniquely predicts causal attributions for misfortune. Together, these results show the value of measuring explicit belief in Karma in cross-cultural studies of justice, religion, and social cognition.

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)0.011
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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.126
GPT teacher head0.425
Teacher spread0.299 · 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

Citations95
Published2018
Admission routes3
Has abstractyes

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