Using Protection of Privacy Legislation to Erode Privacy: R. v. Chehil
Bibliographic record
Abstract
The Nova Scotia Court of Appeal here in R. v. Chehil overturns the trial judge's conclusion that the accused had a reasonable expectation of privacy in the information the police obtained from the computer manifest. With respect, their application of the totality of the circumstances test is subject to question at several important points.\nFor example, in assessing the objective reasonableness of an expectation of privacy, the Court of Appeal relies on the fact that the Westjet website informs customers that "information will be disclosed to the authorities without your knowledge and consent as required by law." The court then observes of the Personal Information Protection and Electronic Documents Act (PIPEDA). 7(3)(c.l)(ii) authorizes disclosure of information for law enforcement purposes." They conclude from these facts that it would not be reasonable to expect privacy in information supplied to the airline.\nHowever, this reasoning seems inverted. Section 7(3)(c.l)(ii) actually only authorizes disclosure for law enforcement purposes to a government institution that has "identified its lawful authority to obtain the information." That is also the essential message of the Westjet website — that the rule is non-disclosure and the exception is when disclosure is "required by law." To say that information will be disclosed when there is, for example, a warrant requiring its disclosure, is not to diminish the objective reasonableness of an expectation of privacy. Quite the contrary, the recognition that something like a warrant will be required before the information is released stresses precisely that there is a reasonable expectation of privacy in it.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.026 | 0.020 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".