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The protective role of supportive friends against bullying perpetration and victimization

2012· article· en· W2023721061 on OpenAlexaff
Kristin Kendrick, Göran Jutengren, Håkan Stattin

Bibliographic record

VenueJournal of Adolescence · 2012
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of British Columbia
FundersForskningsrådet för Arbetsliv och Socialvetenskap
KeywordsFriendshipPsychologyPsychological interventionHuman factors and ergonomicsPoison controlInjury preventionSuicide preventionDevelopmental psychologySocial supportStructural equation modelingVictimisationSocial psychologyAggressionClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

A crossed-lagged regression model was tested to investigate relationships between friendship support, bullying involvement, and its consequences during adolescence. Students, 12-16 years (N = 880), were administered questionnaires twice, one year apart. Using structural equation modeling, a model was specified and higher levels of support from friends were related to lower levels of bullying and victimization one year later. Additionally, a bidirectional relationship between victimization and depression was found, and greater property crimes commission was related to higher levels of future bullying. These findings support the 'friendship protection hypothesis' and suggest the quality of support in friendships can protect against bullying victimization and perpetration. Prior research has shown that friendships can protect against victimization; however this is one of the few longitudinal studies to focus on the quality of friendship, rather than other characteristics of the friends. It is suggested that interventions should focus on increasing perceptions of support within existing friendships.

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)0.003
metaresearch head score (Gemma)0.011
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 score0.019
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.011
GPT teacher head0.272
Teacher spread0.261 · 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

Citations249
Published2012
Admission routes1
Has abstractyes

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