Violence in privacy, Gender and Human Rights: expressions of youth in educational context
Bibliographic record
Abstract
Abstract: In contexts of rape and abusive relationships, analyzing the violence in intimacy relations, with generational cut in youth from the perspective of Human Rights and gender, is the central focus. The issue has reached visibility, at the social and scientific levels, being considered as a problem and one of the current urgencies, due to the multiplicity of manifestations and consequences. Therefore, mapping violent occurrences in the intimacy relations of / among young people, in addition to listing the main legal elements of protection and defense, in light of the literature composes scope of the article. As a methodological approach, the study was carried out with two young men and women, aged between 16 and 24 years, from two middle-sized public schools in the municipalities of Bahia (Salvador and Feira de Santana). It was used as instrument "Young Loving Trajectory \\ PAJ" (original from Canada - Parcour amoreux des jeunes), Brazilian version, to operationalize the qualitative approach (interviews - subjective questions). The need for effective investments, sensitizing family and educational contexts (prevention and information), from different social sectors to the importance of intimate relationships among young people, was concluded. Other results point to the construction of projects based on awareness and education for and by the Rights of youth, informing, understanding and avoiding abusive relationships.\n \nKeywords: violence; youth; intimacy; social and family context; human rights; citizenship.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".