The Policy Diffusion of Civil Asset Forfeiture in Canada
Bibliographic record
Abstract
Since 2001, eight Canadian provinces have enacted civil asset forfeiture statutes, with Prince Edward Island and Newfoundland and Labrador abstaining. These policies allow provincial governments to seize property that has been used for, or is the result of, unlawful activity. Due to their novel nature, this paper explores the manner in which civil forfeiture policies have diffused across the Canadian federation, their changes over time, and their resemblance to one another. Through a content analysis of relevant policy documents, as well as interviews with key policy actors, this research finds that the provinces have learned from jurisdictions both domestically and abroad when developing their own policies. Additionally, despite the potential for considerable policy variance, adopting provinces have adhered to a relatively consistent legislative framework, though more recent policy innovations, including administrative forfeiture and unexplained wealth orders, illustrate more pronounced differences amongst jurisdictions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".