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Negative school perceptions and involvement in school bullying: A universal relationship across 40 countries

2010· article· en· W2154591254 on OpenAlexaff
Yossi Harel‐Fisch, Sophie D. Walsh, Haya Fogel‐Grinvald, Gabriel Amitai, William Pickett, Michal Molcho, Pernille Due, Margarida Gaspar de Matos, Wendy Craig

Bibliographic record

VenueJournal of Adolescence · 2010
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyPerceptionDevelopmental psychologySocial psychology

Abstract

fetched live from OpenAlex

Cross-national analyses explore the consistency of the relationship between negative school experiences and involvement in bullying across 40 European and North American countries, using the 2006 (40 countries n = 197,502) and 2002 (12 countries, n = 57,007) WHO-HBSC surveys. Measures include two Cumulative Negative School Perception (CNSP) scales, one based on 6 mandatory items (2006) and another including an additional 11 items (2002). Outcome measures included bullying perpetration, victimization and involvement as both bully and victim. Logistic regression analyses suggested that children with only 2-3 negative school perceptions, experience twice the relative odds of being involved in bullying as compared with children with no negative school perceptions. Odds Ratios (p < 0.001) increase in a graded fashion according to the CNSP, from about 2.2 to over 8.0. Similar consistent effects are found across gender and almost all countries. Further research should focus on the mechanisms and social context of these relationships.

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)0.004
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.021
GPT teacher head0.312
Teacher spread0.291 · 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

Citations185
Published2010
Admission routes1
Has abstractyes

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