P1-399 Dating violence: prevalence of physical violence and directionality pattern in ten Brazilian cities
Bibliographic record
Abstract
The study investigates the prevalence and directionality pattern (only male, only female, or both are perpetrators) of physical violence in dating relationships perpetrated by secondary-school adolescents in 10 Brazilian cities. The hypothesis is that reciprocity pattern prevails and that female adolescents show the highest rates of perpetration. A sample of 3205 adolescents, aged 15–19, from state to private schools, was investigated, using the Conflict in Adolescent Dating Relationships Inventory. The majority of participants were female adolescents (59%). The prevalence of violence perpetrated by male adolescents stood at 22.4%, whereas for the female participants it was 39.4%. The analysis of the directionality pattern shows that in most relationships both partners practiced aggression, corroborating the evidence for violence reciprocity. This pattern was found in four out of the ten cities, while in the other six, violence perpetrated by female adolescents reached the highest prevalence rates (average of 43.1%). However, in all ten cities, violence perpetrated only by male adolescents shows lower prevalence levels, reaching an average of 9.7%. In line with other studies in Brazil and the USA, female adolescents seem to be more violent than male teenagers, contradicting common sense and the findings from studies on violence among adult couples, in which case women are the main victims. Further investigation is needed into the following aspects: severity and frequency of violent acts; evolution of violence dynamics from dating to adult relationships; and the underlying reasons and context in which violence occurs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| 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".