Restitution in the Context of Criminal Justice
Bibliographic record
Abstract
In 2015, the Canadian Victims’ Bill of Rights, promised to recognize the rights of victims in the criminal justice system and introduced the right to restitution. Restitution, which consists of an amount of money paid by the offender to the victim in order to make redress for the harm suffered, involves numerous advantages, as well as significant disadvantages or limitations for victims. According to the Bill of Rights, “Every victim has the right to have the court consider making a restitution order against the offender,” and, in order to facilitate the victims’ restitution requests, together with the Victims’ Bill of Rights a standard form has been developed. As such, it important to examine the implementation of restitution orders within the criminal justice system in Canada and to question their effectiveness for victims. In this article, we delve into the concept of restitution in order to better understand its use, its function, and its reach in the Canadian criminal justice system. We examine how restitution orders are applied, their advantages and limitations for victims, and we present several alternatives from other justice systems.
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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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.031 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.011 | 0.008 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".