Impact of Peru’s women’s emergency centres on the reporting of physical, psychological and sexual intimate partner violence
Bibliographic record
Abstract
BACKGROUND: Violence against women is a global problem with serious consequences. In response, Peru established women's emergency centres or Centros de Emergencia Mujer (CEMs) in 1999, offering support services like psychological and legal counselling for women suffering from violence. CEMs also implemented preventive activities such as educational programmes and community outreach to prevent domestic violence. This study aimed to assess the impact of CEMs on physical, psychological and sexual intimate partner violence (IPV) in Peru. METHODS: We conducted a secondary analysis of the Peru Demographic and Health Surveys' domestic violence module, from 2004, the first year of available data, to 2016. We use a difference-in-differences approach with the Callaway and Sant'Anna estimator to account for the staggered introduction of CEMs across districts. RESULTS: Our findings showed that CEMs lead to an average increase of 3.00 percentage points (pp) (95% CI: 0.61 to 5.39) in the probability of reporting any form of physical, psychological or sexual IPV, primarily driven by psychological violence reporting (3.07 pp, 95 %CI: 0.60 to 5.55). Analyses of the effect of CEMs on physical and sexual violence were inconclusive but indicate that the CEMs did not have large impacts on these forms of violence. DISCUSSION: CEMs may have increased the reporting mainly of psychological IPV to the Demographic and Health Survey (DHS). This increase in psychological IPV could be due to heightened sensitisation, leading to more individuals reporting to the DHS than before, or to a rise in incidence stemming from unaddressed root causes of violence or potential backlash effects. Our results are inconclusive regarding the impact of CEMs in IPV incidence and highlight the need to refine CEM preventive services and adopt comprehensive strategies to combat and to measure the impact of interventions in IPV. Further research is essential to understand the complexities of IPV prevention and measurement to continuously monitor the progress of such interventions.
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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 | 0.003 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".