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Record W2103457541 · doi:10.1177/0829573509358686

Places to Avoid: Population-Based Study of Student Reports of Unsafe and High Bullying Areas at School

2010· article· en· W2103457541 on OpenAlexaffabout
Tracy Vaillancourt, Heather Brittain, Lindsay Bennett, Steven Arnocky, Patricia McDougall, Shelley Hymel, Kathy Short, Shafik Sunderani, Carol F. Scott, Meredith MacKenzie Greenle, Lesley J. Cunningham

Bibliographic record

VenueCanadian Journal of School Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicBullying, Victimization, and Aggression
Canadian institutionsUniversity of British ColumbiaUniversity of SaskatchewanMcMaster UniversityHamilton Health SciencesUniversity of Ottawa
Fundersnot available
KeywordsPsychologyFeelingSuicide preventionPopulationPerceptionCafeteriaOccupational safety and healthPoison controlInjury preventionMedical educationDevelopmental psychologySocial psychologyMedicineEnvironmental health

Abstract

fetched live from OpenAlex

Students’ perceptions of school safety and experiences with bullying were examined in a large Canadian cohort of 5,493 girls and 5,659 boys in Grades 4 to 12. Results indicate notable differences in when and where students felt safe based on their own perceptions of safety and their own experiences with bullying, particularly across elementary and secondary schools. For elementary students, especially those involved in bullying, the playground/school yard and outside recess/break time were particularly hazardous, whereas for secondary students involved in bullying, the hallways, school lunchroom/cafeteria, and outside recess/break were considered especially dangerous. The commonality across student-identified unsafe areas is that they tend to not be well supervised by school personnel. Accordingly, the present results underscore the need to increase adult supervision in areas in which an overwhelming majority of students report feeling unsafe.

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)0.002
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 score0.787
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.023
GPT teacher head0.329
Teacher spread0.307 · 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

Citations186
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of School PsychologySame topicBullying, Victimization, and AggressionFrench-language works237,207