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Record W2614302206 · doi:10.1177/1088868317734944

The Psychology of Rituals: An Integrative Review and Process-Based Framework

2017· review· en· W2614302206 on OpenAlexaff
Nicholas Hobson, Juliana Schroeder, Jane L. Risen, Dimitris Xygalatas, Michael Inzlicht

Bibliographic record

VenuePersonality and Social Psychology Review · 2017
Typereview
Languageen
FieldPsychology
TopicCultural Differences and Values
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSociocultural evolutionPsychologyFunction (biology)Value (mathematics)CognitionMeaning (existential)Social psychologyCross-cultural psychologySocial cognitionPsychological researchProcess (computing)EpistemologySociologyAnthropology

Abstract

fetched live from OpenAlex

Traditionally, ritual has been studied from broad sociocultural perspectives, with little consideration of the psychological processes at play. Recently, however, psychologists have begun turning their attention to the study of ritual, uncovering the causal mechanisms driving this universal aspect of human behavior. With growing interest in the psychology of ritual, this article provides an organizing framework to understand recent empirical work from social psychology, cognitive science, anthropology, behavioral economics, and neuroscience. Our framework focuses on three primary regulatory functions of rituals: regulation of (a) emotions, (b) performance goal states, and (c) social connection. We examine the possible mechanisms underlying each function by considering the bottom-up processes that emerge from the physical features of rituals and top-down processes that emerge from the psychological meaning of rituals. Our framework, by appreciating the value of psychological theory, generates novel predictions and enriches our understanding of ritual and human behavior more broadly.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0050.006
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.431
GPT teacher head0.607
Teacher spread0.175 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations329
Published2017
Admission routes1
Has abstractyes

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