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Record W1957645886 · doi:10.60082/2563-8505.1218

Normative Foundations for Reasonable Expectations of Privacy

2011· article· en· W1957645886 on OpenAlexaffabout
Hamish Stewart

Bibliographic record

VenueSupreme Court law review · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsExpectation of privacyCharterNormativeSupreme courtPolitical scienceAuthorizationState (computer science)LawLaw and economicsBusinessInternet privacySociologyComputer securityComputer science

Abstract

fetched live from OpenAlex

The right to be “secure against unreasonable search or seizure” in section 8 of the Canadian Charter of Rights and Freedoms applies only where the Charter applicant has a reasonable expectation of privacy in the place searched or the information obtained. The Supreme Court of Canada’s methodology for deciding whether an applicant has such a reasonable expectation appears well settled. The Court asks first whether the applicant had a subjective expectation of privacy, and second whether, in light of a long list of factors, that expectation was reasonable. But the Court’s decisions reveal at least two potentially incompatible ways of orienting the factors. According to what I call the “risk approach”, the focus of the inquiry is on the security of the place searched or the information obtained against the world at large; according to what I call the “surveillance approach”, the question is whether a reasonable person would anticipate that an agent of the state would be able to intrude into the place searched, or obtain the information in question, without legal authorization. I show how the court’s uncertainty about the appropriate approach helps to explain the complex split decision in R. v. Gomboc, and I argue that the surveillance approach provides better protection for the privacy interests that underlie the section 8 guarantee.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.032
metaresearch head score (Gemma)0.057
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.170

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.057
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.001
Science and technology studies0.0060.036
Scholarly communication0.0120.013
Open science0.0030.006
Research integrity0.0100.011
Insufficient payload (model declined to judge)0.0060.001

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.

Opus teacher head0.159
GPT teacher head0.392
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2011
Admission routes2
Has abstractyes

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Same venueSupreme Court law reviewSame topicCriminal Law and EvidenceFrench-language works237,207