A Former Crown’s Vision for Empowering Survivors of Sexual Violence
Bibliographic record
Abstract
Our method for combatting sexual violence in Canada is failing. Survivors of sexual violence have lost confidence in the criminal justice system as evidenced by the extremely low reporting rate to the police. While victims generally wish to hold perpetrators accountable, their reluctance to engage the criminal justice system is a clear indication that the cost (psychologically and emotionally) is too high. Survivors need more protection from re-traumatization and something must change in order to hold perpetrators accountable and deter sexual violence. In this article I propose a fully funded confidential trauma-informed model of victim representation for survivors of sexual violence to better protect their rights and facilitate equal access to justice. I find support for my proposed model by looking to systems of victim representation internationally, in the U.S. Military and in the International Criminal Court. Studies of these models demonstrate that they more meaningfully engage victims with the justice system and mitigate harm in various ways. I also demonstrate why the criticisms of these models are unwarranted. Finally I provide an analysis regarding equality rights under the Canadian Charter and outline why our current process is discriminatory and undermines the equality of women. I conclude that allowing legal representation offers overwhelming value and empowerment to survivors of sexual violence by improving their protection from harm and increasing their access to justice. I further postulate that providing this support to survivors could increase the reporting rate for sexual violence and thereby contribute to reducing the rate of sexually offending with impunity.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".