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Record W4416290318 · doi:10.29173/alr2826

Licencing State Misconduct: Revisiting Nasogaluak and Ward

2025· article· W4416290318 on OpenAlexvenueaboutno aff
Sonia Anand Knowlton, Sylvia Rich

Bibliographic record

VenueAlberta Law Review · 2025
Typearticle
Language
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)MisconductCharterCompensation (psychology)State (computer science)Section (typography)

Abstract

fetched live from OpenAlex

A legal right only has meaning if, when the right is infringed, it can be vindicated in some way. Section 24 of the Canadian Charter of Rights and Freedoms (Charter) provides a basis for courts to provide remedies for Charter violations, but the case law demonstrates the need for more robust remedies in the criminal context. Courts have restricted the application and meaning of section 24(1), resulting in an overreliance on stays of proceedings and sentence reductions. These remedies often fall short of censuring state misconduct and providing sufficient vindication. The authors suggest an alternative approach: under section 24(1), criminal courts, where appropriate, should provide monetary compensation to victims of police misconduct at the conclusion of criminal proceedings.

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)0.016
metaresearch head score (Gemma)0.050
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 score0.121
Threshold uncertainty score0.241

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0060.004
Science and technology studies0.0020.005
Scholarly communication0.0050.005
Open science0.0030.002
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0040.001

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 head0.034
GPT teacher head0.352
Teacher spread0.319 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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