Violência física e fatores associados: estudo de base populacional no sul do Brasil
Bibliographic record
Abstract
OBJECTIVE: To estimate the prevalence of physical violence and its association with sociodemographic aspects, stressful life events, and the use of health services due to emotional problems. METHODS: A cross-sectional population-based study was conducted with a sample of 1,954 14-year-old or older inhabitants of the city of Canoas (Southern Brazil). They were selected by means of conglomerate sampling according to a pre-established system. Data were obtained in visits to households by means of a confidential semi-structured questionnaire. A bivariate analysis was carried out through multinomial logistic regression, and the multivariate analysis by polytomous logistic regression, categorizing the outcome by age group. RESULTS: The findings show a prevalence of 9.7% (CI 95%: 8.37;11.03) and association with: women 20 years old and older (OR=2.74; CI 95%: 1.52;4.94); higher schooling rate (p<0.03); higher experience of stressful life events at 20 years of age or more (OR=6.61; CI 95%: 2.71;16.1); and doctors' appointments due to emotional problems as of 10 years of age (p>0.001). CONCLUSIONS: The prevalence of physical violence in the population was significant, resulting in important emotional consequences and impact on health services, requiring capacity building of the professionals in the field.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| 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) | 0.001 | 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".