A REPORT ABOUT INTIMATE PARTNER VIOLENCE IN SOUTHERN AND WESTERN RWANDA
Bibliographic record
Abstract
The present paper reports on intimate partner violence (IPV) in 3 districts of Southern Province and Western Province in Rwanda. Qualitative data were obtained via 3 focus group discussions conducted at the headquarters of each district, and 10 individual interviews with key informants, community leaders who worked in the districts. The types of IPV discussed were physical, economic, sexual, and psychological harassment. Community leaders stated that the women in their communities had no hesitation in reporting economic abuse and physical violence, but noted that the women needed support from other people to report sexual violence, and generally did not report psychological harassment, perhaps because they accepted it as the norm. They also noted that men generally did not report IPV and that the main victims of IPV in all its forms were children and women. The community leaders suggested a number of measures to reduce IPV: empowering females so that they are financially independent; educating and sensitizing family members about their responsibilities and community leaders about laws and human rights; educating all community members about gender equality and IPV, including premarital instruction; increasing access to services; putting in place a law that protects free unions by giving them legal status after a period of cohabitation; setting up a specific institution to deal with IPV; improving both support to the victims and follow-up of reported cases, along with instituting punitive responses to deter potential new perpetrators.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".