Análise espacial da violência doméstica contra a mulher entre os anos de 2002 e 2007 em João Pessoa-PB
Bibliographic record
Abstract
This is a quantitative study, ecological, exploratory, transversal, using spatial analysis of areal data, whose population was composed of all occurrences reported by women victims of domestic violence, living in the city of João Pessoa , in the period 2002 to 2007, at the Police Service specialized in Women´s violence in João Pessoa. The aim of this study was to investigate the spatial distribution of domestic violence against women to support managers in decision-making process in the development and implementation of public policies on women's health in specific areas of the city. The results identified areas of high and low incidence of domestic violence against women, and also the risk of each quarter when compared to the city of Joao Pessoa. From the Ord and Getis index a decision was produced of wich are the priority areas that need intervention on domestic violence against women. Given this reality, we emphasize the need for changes in practice with regard to attention to women victims of violence, linking health services, the Public Security Bureau, the Secretariat of Policies for Women and Education Institutions, in order to reorient the work process of professional practices, promoting skills in the logic of continuing education services, as well as vocational training that includes discussions on gender and violence against women.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".