É POSSÍVEL PROFISSIONALIZAR AS FAMÍLIAS ACOLHEDORAS NO BRASIL?
Bibliographic record
Abstract
DOI: 10.12957/polemica.2016.22906 ____________ A família acolhedora, alternativa de proteção para lidar com casos de violência doméstica e violação de direitos contra crianças e adolescentes, é prioridade no atendimento, nos casos definidos, segundo previsão legal brasileira. Famílias acolhedoras tornam-se guardiães legais durante um prazo determinado, ficando responsáveis por prestar assistência e cuidados, de forma ampla. Este estudo tem por objetivo questionar o caráter de trabalho voluntário das mesmas no Brasil. Para isso, são trazidos os aspectos legais que dão subsídios a essa prática, bem como um breve recorte sobre as práticas de acolhimento em outros países. Entende-se que a profissionalização dos acolhedores pode ser uma forma de viabilizar o processo de implementação desta importante política pública. Palavras-chave : Família acolhedora. Direitos da criança. Política pública. Violência na família. ____________ Abstract : The foster family, protective alternative for dealing with cases of domestic violence and violation of rights against children and adolescents, is, according to Brazilian legal provision, priority attention in the cases defined. Foster families become legal guardians for a specified period, and were responsible for providing assistance and care, broadly. This study aims to question the character of volunteer foster families in Brasil. To do so, the legal aspects are brought to give subsidies to this practice, as well as a short cut on the host practices of the foster care in other countries. It is understood that the professionalization of the reception, can be a way of facilitating the implementation process of this important public policy. Keywords : Foster care. Children’s rights. Public policy. Family violence.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".