Prevention of domestic violence against women and children in low-income and middle-income countries
Bibliographic record
Abstract
PURPOSE OF REVIEW: Violence against women and children is increasingly recognized as an important and urgent public health, social and human rights issue cutting across geographical, socioeconomic and cultural boundaries. There is a large and growing body of literature that demonstrates the negative impact of such violence on the victim's mental and physical health, as well as several other consequences on them, their families and communities. However, this literature for the most part comes from the so-called 'developed countries'. This review, at the opposite, focused on current literature on prevention of domestic/family violence against children and women in low and middle income countries (LMICs). RECENT FINDINGS: Establishing effective prevention programmes for domestic violence against women and children in LMICs requires an understanding of the sociopolitical, economic and cultural settings and a multilevel collaboration among various stakeholders. SUMMARY: This review confirms the lack of research in the so-called 'developing countries' and provides suggestions for further research and prevention efforts in this setting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".