Restoring victims’ confidence: Victim-centred restorative practices
Bibliographic record
Abstract
Victimization, and in particular sexual violence, undermines victims’ confidence and self-esteem. Victims often feel guilty and blame themselves for what happened. Fearing negative reactions, victims of sexual violence are often reluctant to report the crime to police. When victims do report to the police, the criminal justice process is often difficult and most sexual violence cases do not end in a conviction. Restorative practices (hereafter RP) have been presented both as a possible alternative and a complement to the criminal justice process, which could improve victims’ experiences. However, there is also considerable resistance to the use of RP in cases of gender-based violence. Using a victim-centred lens, in which it is seen as a reaction to victimization that aims to address the needs of the victim and allow them to advance in their healing process, we examine RP. Based on semi-structured interviews with 18 victims of sexual violence in Canada who participated in RP, we explore the healing potential for victims. We conclude that for victims of sexual violence, victim-centred RP should be viewed as a tool for victim support and not only as another tool in the criminal justice toolkit.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.005 | 0.014 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".