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Record W3195498398 · doi:10.3138/cjwl.33.1.04

Section 28’s Potential to Guarantee Substantive Gender Equality in <i>Hak c Procureur général du Québec</i>

2021· article· en· W3195498398 on OpenAlexaboutno aff
Cee Strauss

Bibliographic record

VenueCanadian Journal of Women and the Law/Revue Femmes et Droit · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Issues in South Africa
Canadian institutionsnot available
Fundersnot available
KeywordsSection (typography)Gender equalityCharterDoctrineJurisprudenceLawPolitical scienceAction (physics)Order (exchange)SociologyConstitutional courtLaw and economicsGender studiesConstitutionComputer scienceEconomics

Abstract

fetched live from OpenAlex

Hak c Procureure générale du Québec is an action that has combined four distinct challenges to An Act Respecting the Laicity of the State . In this article, I canvass section 28 doctrine and jurisprudence to outline the purpose and role of section 28 in order to understand how it might operate in the challenge undertaken in Hak . To do so, I conduct a purposive analysis of section 28. In my opinion, section 28 has two distinct purposes: first, it acts as a “gender equality interpretive tool” that requires judges to choose constitutional interpretations that favour substantive gender equality and, second, it ensures that substantive gender equality cannot be overridden by anything else in the Canadian Charter of Rights and Freedoms . Within these broad purposes, I also discuss section 28’s status as an interpretive provision that confers the substantive right to substantive equality, and I offer illustrations of the gender equality tool in case law. I conclude with the potential of section 28 to operate as a gender equality tool in Hak , including its potential to do so intersectionally.

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)0.009
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.102
Threshold uncertainty score0.304

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0160.020
Scholarly communication0.0080.002
Open science0.0020.004
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0080.001

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 head0.026
GPT teacher head0.268
Teacher spread0.242 · 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 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

Citations1
Published2021
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Women and the Law/Revue Femmes et DroitSame topicLegal Issues in South AfricaFrench-language works237,207