The Difficult Road to Accountability: A Study on Complaints Mechanisms to Investigate and Address Victims’ Rights Violations
Bibliographic record
Abstract
Despite existing scholarship on victims’ rights, there is no empirical research in Canada on enforcement mechanisms that respond to victims’ rights violations. This article analyzes the recent Canadian Victims Bill of Rights, which instructs federal criminal justice agencies to develop enforcement mechanisms to remedy breaches of victims’ rights and encourages provincial agencies to do the same. The first part of this article situates the development of the Canadian victims’ rights and enforcement mechanisms in their wider context by referring to the literature on victim participation and their role in the criminal justice process. Second, this piece proposes nuanced understanding of enforcement and brings together knowledge and frameworks found in two separate bodies of literature, namely the administrative law literature and victimology, to analyze the effectiveness of enforcement mechanisms in the context of crime victims. Applying these frameworks to the study of mechanisms available at the federal and provincial levels in Quebec, this piece discusses a number of limitations and proposes possibilities for improving the existing complaints structures.
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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 | 0.022 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.022 | 0.013 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| 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".