SCHOOL-BASED VICTIMIZATION: DEVELOPMENTAL TRAJECTORY & SEX DIFFERENCES IN SELF REPORTED VICTIMIZATION RATES
Bibliographic record
Abstract
Research into children’s mental health has developed a focus on childhood aggression, bullying, and victimization. Previous research of school-based aggression has identified sex differences in the experience of bullying and victimization in relation to the type of bullying in question. The present study examined sex and developmental differences in the experience of victimization through verbal, physical, social, sexual, and cyber bullying. Participants of this study were 43 741 students in grades 4 through 12 who completed the Safe Schools Survey through the Thames Valley District School Board in London, Ontario. Results indicated that male students are most likely to be victimized by school-based aggression, including social and sexual bullying, relative to female students. An interaction was found between sex and development in their relation on frequency of victimization. Students in grades 9 and 10 were most likely to be victimized, regardless of sex or type of bullying. The results are discussed in terms of the relevance to previous findings and implications for practitioners.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".