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Peer Victimization and Internalizing Symptoms From Adolescence Into Young Adulthood: Building Strength Through Emotional Support

2012· article· en· W2097793260 on OpenAlexafffund
Rachel S. Yeung Thompson, Bonnie J. Leadbeater

Bibliographic record

VenueJournal of Research on Adolescence · 2012
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of Victoria
FundersCanadian Institutes of Health ResearchU.S. Public Health Service
KeywordsPsychologyPeer victimizationDevelopmental psychologyEmotional supportLongitudinal studyAssociation (psychology)Clinical psychologyInjury preventionPoison controlSocial supportSocial psychologyMedicine

Abstract

fetched live from OpenAlex

This longitudinal study investigated how changes in peer victimization were associated with changes in internalizing symptoms among 662 adolescents across a 4-year period. The moderating effects of initial levels of father, mother, and friend emotional support on this association were also examined. Gender and age group differences (early adolescent group aged 12-15 years; late adolescent group aged 16-18 years) were tested. Increases in physical and relational victimization were related to increases in internalizing symptoms. Friend emotional support was more protective in reducing internalizing symptoms for adolescent males than adolescent females in both the early and late adolescent groups. Gender differences also moderated the effects of mother and father emotional support.

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)0.003
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.047
GPT teacher head0.398
Teacher spread0.351 · 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

Citations88
Published2012
Admission routes2
Has abstractyes

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