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Record W2124879310 · doi:10.24908/ss.v4i4.3444

Privacy Outside the Castle: Surveillance Technologies and Reasonable Expectations of Privacy in Canadian Judicial Reasoning

2002· article· en· W2124879310 on OpenAlexafffundabout
Krista Boa

Bibliographic record

VenueSurveillance & Society · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicPrivacy, Security, and Data Protection
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsPrivacy rightsInformation privacyPolitical sciencePrivacy policyBalance (ability)Privacy lawPrivacy protectionRight to privacyJudicial interpretationElectronic surveillanceCivil rightsTerrorismLawThe Right to PrivacyExclusionary ruleBusinessInternet privacyHuman rightsSupreme courtComputer sciencePsychology

Abstract

fetched live from OpenAlex

In recent years U.S. police have been given greater surveillance powers in response to perceived threats from crime, drugs, and terrorism. Several legal and criminal events have facilitated a reevaluation of the balance between police surveillance authority and civil privacy protection. In the post-9/11 era, changes in federal law, court interpretation of privacy safeguards, and technological advances have expanded the circumstances and methods by which the police may engage in surveillance of civil activities. This paper examines the factors contributing to the escalation in police surveillance and its effects on privacy rights and civil life. The analysis suggests that increasing police surveillance has diminished individual privacy protections and impacted aspects of civil life.

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)0.013
metaresearch head score (Gemma)0.073
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.636

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.073
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0130.023
Scholarly communication0.0120.007
Open science0.0020.004
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.000

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 head0.025
GPT teacher head0.279
Teacher spread0.254 · 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 designQualitative
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

Citations3
Published2002
Admission routes3
Has abstractyes

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