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Record W2131516502 · doi:10.1177/0143034307084136

Responding to Bullying

2007· article· en· W2131516502 on OpenAlexaffabout
Wendy Craig, Debra Pepler, Julie Blais

Bibliographic record

VenueSchool Psychology International · 2007
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsYork UniversityQueen's University
Fundersnot available
KeywordsAssertivenessPsychologySuicide preventionInjury preventionPoison controlDevelopmental psychologyClinical psychologySocial psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

Children who are bullied are often told to `solve the problems themselves'; however, when bullying is repeated over time, it becomes increasingly difficult for victimized children to stop the torment because of their relative lack of power. We examine the ways in which children respond to bullying and their evaluations of the effectiveness of various strategies in reducing their bullying problems. One thousand eight hundred and fifty-two Canadian children and youth, ranging in age from 4- to 19-years-old (mean 12.6, SD 2.4) responded to a web-based questionnaire. Few respondents indicated that they were motivated by public education campaigns or information about bullying. Participants indicated they were motivated to do something to stop bullying by their own need to exert control and be assertive and by their emotional reactions to bullying. A significant group of youth responded that they did nothing to stop bullying. Finally, the longer the bullying had been ongoing, the less effective students perceived their own strategies. The results highlight the importance of adults supporting students. Similarly, it is important to provide children and youth with strategies that are effective, as they are most likely to implement strategies that are only going to increase the victimization over time.

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)0.010
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 score0.051
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.394
Teacher spread0.364 · 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

Citations193
Published2007
Admission routes2
Has abstractyes

Explore more

Same venueSchool Psychology InternationalSame topicBullying, Victimization, and AggressionFrench-language works237,207