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Record W4396715373 · doi:10.29173/mlj1291

Constitutionalizing Gladue Rights: Critical Perspectives and Prospective Paths Forward

2022· article· en· W4396715373 on OpenAlexaboutno aff
Hardie Rath-Wilson

Bibliographic record

VenueManitoba Law Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Justice and Corrections Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCharterIndigenousLawPolitical scienceJurisprudenceEconomic JusticeSociology

Abstract

fetched live from OpenAlex

While remedial sentencing practices for Indigenous accused in Canada have often been described in rights-based terms, Canadian jurisprudence has been reluctant to characterize s. 718.2(e) of the Criminal Code as an actual “right.” At the same time, front-line judges who are witnesses to — and complicit in — the systemic overincarceration of Indigenous people have created something more out of Gladue than a Criminal Code sentencing guideline. Indeed, they have followed our apex Court’s direction that “application of the Gladue principles is required in every case involving an Aboriginal offender.” Following a few recent expansions of Gladue into yet more spheres of the administration of colonial justice, this paper investigates whether there is utility in reconceiving Gladue as a Charter right. While the substantive and theoretical criticisms of the legal policy mechanism of Gladue are valid, binding judicial and administrative decision-makers with a Charter responsibility to consider the particular circumstances of Indigenous realities when liberty interests of an accused are at stake can serve to strengthen the check on colonial maladministration of justice.

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)0.032
metaresearch head score (Gemma)0.032
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 score0.905
Threshold uncertainty score0.262

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0160.119
Scholarly communication0.0260.028
Open science0.0060.007
Research integrity0.0190.025
Insufficient payload (model declined to judge)0.0060.001

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 head0.017
GPT teacher head0.302
Teacher spread0.285 · 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
Published2022
Admission routes1
Has abstractyes

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