Success in small places: NCB forfeiture thrives in Manitoba, a small but mighty Canadian jurisdiction
Bibliographic record
Abstract
Purpose This paper shows how a small jurisdiction can apply well-designed non-conviction-based (NCB) forfeiture provisions with a dedicated team to have a meaningful impact on financial crime. This paper aims to examine developing jurisprudence, legislation and case law to explore how the NCB laws work. Finally, this paper examines a relatively new area of law for Canada, unexplained wealth orders (UWOs). This paper discussed three recent cases in Western Canada currently before the courts. Design/methodology/approach This paper considers legislative and jurisprudential developments relevant to NCB or civil asset forfeiture and in particular considers very recent developments involving UWOs. Findings This paper shows how a small jurisdiction can apply well-designed NCB forfeiture provisions with a dedicated team to have a meaningful impact on financial crime. Research limitations/implications Some jurisdictions, like the UK, have experienced court losses with their UWO process. Canadian law may have a modest pathway to success in this area, although our jurisprudence is very much in development. Practical implications Manitoba is a small jurisdiction with limited resources who are finding ways to have an effective impact on financial crime through the careful application of use of conviction-based forfeiture. Social implications Financial crime has an outsized impact on society. This paper shows some of the techniques available to disrupt financial crime. Originality/value This paper incorporates developments in 2024 that have not yet been examined.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".