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Record W4541742

Section 7 of the Charter and National Security: Rights Protection and Proportionality versus Deference and Status

2012· article· en· W4541742 on OpenAlexaffabout
Kent Roach

Bibliographic record

VenueSSRN Electronic Journal · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicInternational Law and Human Rights
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDeferenceCharterPolitical scienceJurisprudenceHuman rightsProportionality (law)National securityLawInternational human rights lawSovereigntyFundamental rightsStandard of reviewLaw and economicsJudicial reviewPoliticsSociology
DOInot available

Abstract

fetched live from OpenAlex

This paper examines section 7 jurisprudence in the context of national security cases involving collective security considerations and/or Canada’s interactions with other states on security-related matters. National security, like section 7 of the Canadian Charter of Rights and Freedoms, spans the traditional divides between administrative, criminal, extradition and international law. The paper identifies two distinct strands in the jurisprudence: one associated with rights protection and a requirement that any limits on rights be justified as proportionate, and another based on an a priori deference to governments, consideration of the status of individuals — notably non-citizens — and respect for the sovereignty of other nations. The paper concludes that despite some post-9/11 attraction to deference and status concerns, rights protection and proportionality concerns may eventually win out, especially when supported by concerns about compliance with international human rights commitments and the reconciliation of rights protection with the fulfillment of various national security goals.

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)0.008
metaresearch head score (Gemma)0.009
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 score0.617
Threshold uncertainty score0.770

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0100.034
Scholarly communication0.0090.003
Open science0.0020.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0030.000

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 head0.020
GPT teacher head0.284
Teacher spread0.264 · 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
Published2012
Admission routes2
Has abstractyes

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