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Record W1981814738 · doi:10.1080/15374410709336569

Rumination on Anger and Sadness in Adolescence: Fueling of Fury and Deepening of Despair

2007· article· en· W1981814738 on OpenAlexaff
Maya Peled, Marlene M. Moretti

Bibliographic record

VenueJournal of Clinical Child & Adolescent Psychology · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Adolescent Psychosocial and Emotional Development
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAngerSadnessRuminationPsychologyAggressionFeelingClinical psychologyCognitionDevelopmental psychologySocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

We examined anger rumination and sadness rumination in clinic-referred adolescents (N = 121). Factor analysis indicated that items from analogous anger and sadness rumination measures loaded onto 2 factors tapping anger rumination and sadness rumination, respectively. Structural equation modeling confirmed unique relations between each form of rumination and specific emotional or behavioral problems. Anger and anger rumination were independent predictors of aggression, suggesting that both the affective component of anger (i.e., angry feelings) and the cognitive process (i.e., recurrent thoughts about anger) are important in predicting aggressive behavior. Girls reported higher levels of both forms of rumination compared to boys; however, no sex differences were found in the relations between either form of rumination and outcomes.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.420
Teacher spread0.366 · 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

Citations177
Published2007
Admission routes1
Has abstractyes

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