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Record W2102106185

Approach to bullying and victimization.

2009· article· en· W2102106185 on OpenAlexaffabout
Jennifer Lamb, Debra Pepler, Wendy Craig

Bibliographic record

VenuePubMed · 2009
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsWomen's College HospitalUniversity of Toronto
Fundersnot available
KeywordsPsycINFOPsychosocialIntervention (counseling)Poison controlMEDLINEMedicineSuicide preventionInjury preventionOccupational safety and healthHuman factors and ergonomicsPsychologyClinical psychologyPsychiatryMedical emergencyPathology
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To review the epidemiology, identification, and management of bullying and victimization among children in the primary care setting. SOURCES OF INFORMATION: Information was obtained from PsycINFO and MEDLINE databases, as well as the authors' own clinical and research experience. Information is based on levels II and III evidence. MAIN MESSAGE: Involvement in bullying is a destructive relationship problem, with important health implications. Physicians need to be aware of the physical and psychosocial symptoms commonly associated with involvement in bullying so that they can screen and identify those children involved. This article presents a review of bullying and associated symptoms, a tool for assessing bullying involvement, and an overview of intervention and management. CONCLUSION: Bullying is a substantial problem affecting Canadian children. With an increased awareness and understanding of bullying as a health problem, physicians can play an instrumental role in identifying children involved in bullying and providing them with the support needed to develop healthy 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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.934
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

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

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 head0.026
GPT teacher head0.255
Teacher spread0.230 · 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 teacher head, 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

Citations54
Published2009
Admission routes2
Has abstractyes

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