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Record W2604611331 · doi:10.60082/2563-8505.1319

A Step Forward or Just a Sidestep? Year Five of the Supreme Court of Canada in the Digital Age

2015· article· en· W2604611331 on OpenAlexaboutno aff
Nader R. Hasan

Bibliographic record

VenueSupreme Court law review · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsnot available
Fundersnot available
KeywordsSearch and seizureWarrantSupreme courtCharterLawProbable causeContext (archaeology)Law enforcementPolitical scienceReasonable suspicionScope (computer science)Privacy lawInternet privacyInformation privacyPrivacy policyBusinessComputer scienceHistory

Abstract

fetched live from OpenAlex

Over the past five years, the Supreme Court of Canada has released a series of decisions meant to bring section 8 of the Canadian Charter of Rights and Freedoms into the Digital Age. These decisions acknowledged the unique privacy interests that people have in the information stored on their digital devices and the potential for modern technology to eviscerate privacy if the law of search and seizure does not keep pace with technological development. There is a danger, however, that recent victories for privacy in the courts will be illusory unless the courts develop additional manner of search limits on the search and seizure of digital devices. In the case of searches conducted pursuant to a search warrant, this article suggests that the only way to achieve the appropriate balance between law enforcement needs and privacy rights is for issuing justices to impose a set of search protocols that constrain and limit the scope of the search. Outside the search warrant context (i.e., where the police conduct a warrantless search of a digital device pursuant to the “search-incident-to-arrest” power), this article suggests that the only way to protect privacy interests, and to achieve meaningful after-the-fact judicial review, is to require that police electronically record all warrantless searches of digital devices.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.839
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.061
GPT teacher head0.311
Teacher spread0.251 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2015
Admission routes1
Has abstractyes

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