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Record W2605920309 · doi:10.22329/wyaj.v30i2.4375

WARMING UP THE “CHILLING EFFECT”: A COMMENT ON THE MOTIVE CLAUSE DISCUSSIONS IN R V KHAWAJA (2010) AND R V KHAWAJA (2012)

2012· article· en· W2605920309 on OpenAlexaffvenueabout
Josephine L. Savarese

Bibliographic record

VenueWindsor Yearbook of Access to Justice · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicLaw, Rights, and Freedoms
Canadian institutionsSt. Thomas University
Fundersnot available
KeywordsCharterRacial profilingTerrorismConstitutionalityLawDeclarationPolitical scienceDignityEnforcementSuspectSociologySupreme court

Abstract

fetched live from OpenAlex

Following the attacks on September 11, 2001, biased surveillance and discriminatory law enforcement approaches gained momentum. In 2003, Reem Bahdi published “No Exit: Racial Profiling and Canada‟s War Against Terrorism.” She analyzed the influence that the declaration of a war against terrorism by Western nations, including Canada, was having on Arabs and Muslims. Other scholars critiqued aspects of Canada‟s anti-terrorism response, including the incorporation of a motive clause into the Criminal Code sections prohibiting terrorist offences. In R. v. Khawaja (2006), the Superior Court reviewed the constitutionality of the motive element in the definition of terrorism. It held that the motive clause facilitated the targeted law enforcement practices that Bahdi and others advocated against. This paper reports on a review of the appellate decisions, R. v. Khawaja (2010) and (2012), which held that the motive clause was consistent with the Canadian Charter of Rights and Freedoms. The appellate decisions are critiqued for their failure to adequately promote human dignity and equality in keeping with the Charter‘s spirit. As a result, the paper concludes by arguing for a return to the insights of Bahdi and others who encourage a rethinking of Canadian social policy after 9/11 to ensure commitment to human rights doctrines, particularly in regard to the racial profiling that the motive clause seemed to animate.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.738

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 studies0.0010.002
Scholarly communication0.0000.001
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 head0.055
GPT teacher head0.329
Teacher spread0.274 · 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 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

Citations1
Published2012
Admission routes3
Has abstractyes

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