Intimate partner violence in Sri Lanka: a scoping review
Bibliographic record
Abstract
South Asia is considered to have a high prevalence of intimate partner violence (IPV) against women. Therefore the World Health Organisation has called for context-specific information about IPV from different regions. A scoping review of published and gray literature over the last 35 years was conducted using Arksey and O'Malley's framework. Reported prevalence of IPV in Sri Lanka ranged from 20-72%, with recent reports of rates ranging from 25- 35%. Most research about IPV has been conducted in a few provinces and is based on the experience of legally married women. Individual, family, and societal risk factors for IPV have been studied, but their complex relationships have not been comprehensively investigated. Health consequences of IPV have been reported, with particular attention to physical health, but women are likely to underreport sexual violence. Women seek support mainly from informal networks, with only a few visiting agencies to obtain help. Little research has focused on health sector responses to IPV and their effectiveness. More research is needed on how to challenge gendered perceptions about IPV. Researchers should capture the experience of women in dating/cohabiting relationships and women in vulnerable sectors (post-conflict areas and rural areas), and assess how to effectively provide services to them. A critical evaluation of existing services and programmes is also needed to advance evidence informed programme and policy changes in Sri Lanka.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.014 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".