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Record W1547212481 · doi:10.60082/2563-8505.1121

The Charter and Protection against Wrongful Conviction: Good, Bad or Irrelevant?

2008· article· en· W1547212481 on OpenAlexaffabout
Christopher Sherrin

Bibliographic record

VenueSupreme Court law review · 2008
Typearticle
Languageen
FieldPsychology
TopicDeception detection and forensic psychology
Canadian institutionsWestern University
Fundersnot available
KeywordsConvictionCharterLawPolitical scienceJurisprudenceCriminal lawLaw and economicsSociology

Abstract

fetched live from OpenAlex

This paper asks whether the Canadian Charter of Rights and Freedoms, as interpreted over the past 25 years, has made a positive contribution to the protection afforded in Canadian law against wrongful conviction. The paper argues that while the Charter has made a positive contribution in a couple of areas, its overall impact is not clear. It is, in fact, arguable that the Charter has made things worse for the innocent. The paper proceeds in four parts. First, the paper describes the two areas where the Charter has made a positive contribution, namely, disclosure and reverse onuses and presumptions. The paper next reviews many of the remaining areas of criminal Charter jurisprudence and concludes that the Charter has done little if anything to protect the innocent. This conclusion is reinforced in the third part of the paper by an examination of the Charter’s lack of impact on the major documented causes of wrongful conviction. The fourth part of the paper offers two reasons why the Charter may have actually made it harder for the innocent to avoid conviction: it may have diverted attention and resources away from defence investigations into factual innocence, and it may have provoked an embattled reaction by the police resulting in greater subversion of the existing rules and practices that do protect against wrongful conviction. The paper concludes that, while an overall assessment of the Charter’s impact is difficult to make, it is plausible that at least at the margin there has been a trade-off between enhanced constitutional fairness and adjudicative accuracy for the innocent.

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)0.015
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 score0.173
Threshold uncertainty score0.394

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.050
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0130.051
Scholarly communication0.0140.008
Open science0.0030.005
Research integrity0.0060.011
Insufficient payload (model declined to judge)0.0070.000

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 head0.319
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 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
Published2008
Admission routes2
Has abstractyes

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