Across the Rubicon and into the Apennines: Privacy and Common Law Police Powers after A.M. and Kang-Brown
Bibliographic record
Abstract
In A.M and Kang Brown the Supreme Court of Canada both answered some of the questions surrounding whether odours emanating from individuals' belongings are constitutionally protected from police sniffer dogs and raised other questions about the future of privacy and common law police powers in Canada. This article examines the judgments in A.M. and Kang Brown, with an emphasis on the lines of reasoning relating to two issues: the reasonable expectation of privacy and the standard underlying common law search powers. The author suggests that these Supreme Court of Canada decisions seem to give with one hand while taking away with the other; while offering enhanced opportunities for protecting reasonable expectations of privacy by insisting that the inquiry be placed in context, the decisions also appear to expand common law police powers outside of matters involving threats to public safety.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.033 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.003 | 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".