Violence and injuries among school children in the Republic of Srpska
Bibliographic record
Abstract
INTRODUCTION: There are only a limited number of researches on the frequency, extent, causality and the location of injuries among young people. It is difficult to say to which extent the risky behavior in youth is really spread, because there are no routine data on this issue. In the Republic of Srpska, the first nationwide survey on health behavior of school aged children was conducted, comprising a very important area of health behavior related to injuries, violence and harassment. The aim of this paper was to investigate the risky behavior of school children in the Republic of Srpska in relation to injuries, violence and harassment. MATERIAL AND METHODS: This cross-sectional study was conducted throughout the entire territory of the Republic of Srpska during 2002, on a selected sample of schools and covered a total of 1783 pupils, 15 years of age. The survey instrument was the international standard questionnaire, modified for the Republic of Srpska region. RESULTS: Almost a quarter of all polled school children of both sexes have participated in fights. More than 10% of boys carry weapons. Injuries have mostly occurred during sports activities, on sports grounds (35.8%), at home (26.9%), in the school yard (14.5%), in the street or parking lots (11.4%) and in the countryside (5.6%). CONCLUSION: The existing violence and injuries among school children indicate a clear need for improvement of mutual communication and tolerance among pupils and involvement of all relevant community members: parents, teachers, health workers and the entire society in health education of school children.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".