Beyond Silence and Stigma: Crafting a Gender-Sensitive Approach for Victims of Sexual Violence in Domestic Reparation Programmes
Bibliographic record
Abstract
Our thanks to the victims and survivors who gave their time to speak to us.We are also grateful to all the lawyers, legal representatives of victims, as well as to civil society organisations that spoke to us, allowed us to know their work, the challenges they face but also how important what they do is, to give victims of sexual and gender based violence a voice and to empower them.In particular, we express our appreciation to the victims' groups and civil society associations who helped to facilitate our research and opened up their facilities to us.In Uganda we would like to thank Stephen Oola, the Women's Advocacy Network, the Justice and Reconciliation Project, and the Refugee Law Project.In Peru, we would like to thank the National Coordination for Human Rights (CNDDHH -Coordinadora Nacional de Derechos Humanos) and its Working groups, the Follow-up Group on Reparations for Forced Sterilization and DEMUS.In Colombia, thanks to Ruta de Mujeres, and Red de Mujeres
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".