Corporal punishment bans and physical fighting in adolescents: an ecological study of 88 countries
Bibliographic record
Abstract
OBJECTIVE: To examine the association between corporal punishment bans and youth violence at an international level. DESIGN: Ecological study of low-income to high-income 88 countries. SETTING: School-based health surveys of students. PARTICIPANTS: 403 604 adolescents. INTERVENTIONS: National corporal punishment bans. PRIMARY OUTCOME MEASURE: Age-standardised prevalence of frequent physical fighting (ie, 4+ episodes in the previous year) for male and female adolescents in each country. RESULTS: Frequent fighting was more common in males (9.9%, 95% CI 9.1% to 10.7%) than females (2.8%, 95% CI 2.5% to 3.1%) and varied widely between countries, from 0.9% (95% CI 0.8% to 0.9%) in Costa Rican females to 34.8% (95% CI 34.7 to 35.0) in Samoan males. Compared with 20 countries with no ban, the group of 30 countries with full bans (in schools and in the home) experienced 69% the rate of fighting in males and 42% in females. Thirty-eight countries with partial bans (in schools but not in the home) experienced less fighting in females only (56% the rate found in countries without bans). CONCLUSIONS: Country prohibition of corporal punishment is associated with less youth violence. Whether bans precipitated changes in child discipline or reflected a social milieu that inhibits youth violence remains unclear due to the study design and data limitations. However, these results support the hypothesis that societies that prohibit the use of corporal punishment are less violent for youth to grow up in than societies that have not.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".