Distinguishing Charter Rights in Criminal and Regulatory Investigations: What’s the Purpose of Analyzing Purpose?
Bibliographic record
Abstract
This article critically evaluates one of the main justifications for affording persons accused of regulatory offences constitutional protections different from those afforded to persons accused of criminal offences. It is only the latter who enjoy robust constitutional protection against self-incrimination and to privacy. This difference has been justified on the basis that there are different purposes behind regulatory and criminal investigations. The former are supposedly intended to ensure compliance with the law whereas the latter are supposedly intended to gather evidence for prosecution. This article challenges the validity of the justification based on purpose. The author suggests that focusing on investigatory purpose has no relevance to the interests protected by the right to privacy, offers no real protection against the admission of unreliable evidence, and undermines the very principle it is said to protect: the principle against self-incrimination. Moreover, the justification based on purpose misunderstands the purposes of both regulatory and criminal investigations and ignores the reality that in many instances they share the same purpose.
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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 | 0.105 | 0.185 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.006 | 0.075 |
| Scholarly communication | 0.021 | 0.041 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.016 | 0.012 |
| Insufficient payload (model declined to judge) | 0.002 | 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".