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Record W2894992065 · doi:10.1037/spq0000280

The role of shame in chronic peer victimization.

2018· article· en· W2894992065 on OpenAlexfundno aff
Alexandra Irwin, Joyce Li, Wendy Craig, Tom Hollenstein

Bibliographic record

VenueSchool Psychology · 2018
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsShamePsychologyMediationPsycINFOClinical psychologyPeer victimizationSuicide preventionInjury preventionHuman factors and ergonomicsPoison controlDevelopmental psychologySocial psychologyMedicineMEDLINEMedical emergency

Abstract

fetched live from OpenAlex

Emotional reactions to peer victimization may increase risk for subsequent peer victimization. In the present study, we investigated whether shame mediated the development of chronic peer victimization, i.e., young people's experiences of being bullied persistently across time. We used a multiple mediation model to test the indirect effects of Time-1 victimization on Time-3 victimization (1 year later) through 4 Time-2 shame-related variables (characterological, bodily, and behavioral shame; shame proneness) for 396 youth (10-13 years of age). The total indirect effect of Time-1 victimization on Time-3 victimization through the 4 shame-related mediators was statistically significant. Analyses revealed specific indirect positive effects for bodily shame and shame proneness. Findings suggest that shame may be an emotional mechanism underlying chronic peer victimization. (PsycINFO Database Record (c) 2019 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 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)0.010
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.015
GPT teacher head0.334
Teacher spread0.320 · 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

Citations16
Published2018
Admission routes1
Has abstractyes

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