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Record W2896164668 · doi:10.29173/alr2494

Consent Searches for Electronic Text Communications: Escaping the Zero-Sum Trap

2018· article· en· W2896164668 on OpenAlexaffvenueabout
Steven Penney

Bibliographic record

VenueAlberta Law Review · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExpectation of privacyDissenting opinionCommunication sourceSupreme courtAdjudicationLawDoctrineCharterPolitical scienceComputer scienceComputer securityInternet privacyTelecommunications

Abstract

fetched live from OpenAlex

In R. v. Marakah, a majority of the Supreme Court of Canada decided that senders of electronic text communications maintain a reasonable expectation of privacy over their messages even after they are copied to recipients’ devices. The dissenters argued, in contrast, that any such expectation is objectively unreasonable given senders’ inability to control the messages after delivery. The Supreme Court did not settle the question, however, of whether this expectation can be defeated by a recipient’s voluntary decision to allow police to search his or her own device. Indeed, each side intimated that such a consent would be difficult, if not impossible, to obtain.This article argues, nonetheless, that courts can and should use consent doctrine to avoid the “zero-sum” model of section 8 adjudication that characterizes the majority and dissenting reasons in Marakah. Properly interpreted, that doctrine preserves Marakah’s core holding — that senders do not reasonably expect unfettered state access to their received text communications — while also giving effect to recipients’ autonomous decisions to assist police.However, as with oral communications, a recipient’s consent to disclose a sender’s text communications to police should only defeat the sender’s expectation of privacy over preexisting messages. Contrary to several lower court decisions, this article argues that the acquisition of future, incoming communications from recipients’ devices (with or without consent) invades senders’ reasonable expectations of privacy under section 8 of the Charter and constitutes an “interception” requiring judicial authorization under section 184.2 of the Criminal Code.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.972
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
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 head0.173
GPT teacher head0.426
Teacher spread0.253 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2018
Admission routes3
Has abstractyes

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