Social Environments and Physical Aggression Among 21,107 Students in the United States and Canada
Bibliographic record
Abstract
BACKGROUND: Physical aggression is an important issue in North American populations. The importance of students' social environments in the occurrence of physical aggression requires focused study. In this study, reports of physical aggression were examined in relation to social environment factors among national samples of students from Canada and the United States. METHODS: Students in grades 6-10 from the United States (n = 14,049) and Canada (n = 7058) who had participated in the Health Behaviour in School-aged Children Survey (HBSC) were studied. Rates of students' physical aggression were compared between the 2 countries. School, family, socioeconomic, and peer-related factors were considered as potential risk factors. A simple social environment risk score was developed using the US data and was subsequently tested in the Canadian sample. RESULTS: Risks for physical aggression were consistently higher among United States versus Canadian students, but the magnitude of these differences was modest. The relative odds of physical aggression increased with reported environmental risk. To illustrate, US boys in grades 6-8 reporting the highest social environment risk score (5+) experienced a relative odds of physical aggression 4.02 (95% CI 2.7-5.9) times higher than those reporting the lowest score (adjusted OR for risk scores 0 through 5+ was 1.00, 1.19, 2.10, 2.01, 3.71, and 4.02, respectively, p(trend) < .001). CONCLUSIONS: Unexpectedly, rates of physical aggression and associations between social environments and students' aggression were remarkably similar in Canada and the United States. Family, peer, and school social environments serve as risk or protective factors, with significant cumulative impact on physical aggression in both countries. Given the observed high rates and the many negative effects of aggression on long-term health, school policies aimed at the reduction of such behavior remain a clear priority.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".