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Record W4391844670 · doi:10.1037/bul0000421

Wipe it off: A meta-analytic review of the psychological consequences and antecedents of physical cleansing.

2024· review· en· W4391844670 on OpenAlexafffund
Spike W. S. Lee, Kathleen Chen, C. Ma, Joe Hoang

Bibliographic record

VenuePsychological Bulletin · 2024
Typereview
Languageen
FieldPsychology
TopicOptimism, Hope, and Well-being
Canadian institutionsUniversity of Toronto
FundersConnaught FundUniversity of TorontoSocial Sciences and Humanities Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsPsychologyData cleansingFeelingOutlierMeta-analysisVariance (accounting)Sample (material)Sample size determinationSocial psychologyPsychological scienceStatisticsData qualityMathematics

Abstract

fetched live from OpenAlex

= 0.103 to 0.331 and always exhibited considerable heterogeneity. Effect sizes were especially large for behavioral measures and varied significantly between sample types, sample regions, and report types. Meanwhile, effects were domain-general (observed in the moral domain and beyond), bidirectional (physical cleansing ↔ psychological variables), and robust across theoretical types, manipulation operationalizations, and study designs. Limitations included mixed replicability, suboptimal methodological rigor, and restricted sample diversity. We recommend future studies to (a) incorporate power analysis, preregistration, and replication; (b) investigate generalizability across samples; (c) strengthen discriminant validity; and (d) test competing theoretical accounts. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.762
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.004
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0080.001

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 head0.164
GPT teacher head0.460
Teacher spread0.297 · 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 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

Citations10
Published2024
Admission routes2
Has abstractyes

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