Adolescent risk correlates of bullying and different types of victimization
Bibliographic record
Abstract
This study examined correlates of different types of bullying and victimization relevant to the adolescent context. Of particular interest was the importance of risk factors that emerge and/or undergo significant changes during adolescence. Logistic regressions were performed using a representative sample of approximately 6,500 Canadian adolescents. We found that high-levels of victimization (7.6%), bullying (6.1%), and bully-victimization (0.9%) were quite prevalent amongst adolescents. The patterns of risk associated with each of these labels were different from each group. An examination of the different sub-types of victimization revealed that there were differences in both the prevalence and the risk patterns associated with each sub-type. Physical, verbal, and rumor victimization (the most common types) had similar risk patterns, while sexual victimization and ethnic victimization (the least most common type) each had a unique risk pattern. We conclude that emerging and/or changing risk factors associated with adolescent development are significantly related to bullying and victimization, with the specific relationships depending on the specific type of activity examined. These findings suggest that successful intervention strategies should try to be sensitive to the variations in prevalence and relationships with the risk factors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".