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Record W4311063134 · doi:10.29173/wclawr77

Conviction Integrity: The Canadian Miscarriages of Justice Commission

2022· article· en· W4311063134 on OpenAlexvenueaboutno aff
Carrie Leonetti

Bibliographic record

VenueThe Wrongful Conviction Law Review · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicCriminal Law and Evidence
Canadian institutionsnot available
Fundersnot available
KeywordsCommissionInnocenceEconomic JusticeAppealLawPolitical scienceGovernment (linguistics)ConvictionCriminal justiceScope (computer science)

Abstract

fetched live from OpenAlex

Recently, the Canadian Government has committed to creating an independent Canadian Criminal Cases Review Commission. Minister Lametti initiated a consultation process with stakeholders, led by Justice Harry S. LaForme of the Ontario Court of Appeal and assisted by retired Judge Juanita Westmoreland-Traoré of the Court of Quebec, to precede the implementation of the Commission. The resulting report recommends a visionary innocence commission for Canada that is more independent, better funded, more systematic, proactive, and inclusive, has scope to review far more potential miscarriages of justice, and has broader referral grounds and more remedies than existing innocence commissions in other countries. Hopefully, the Canadian Government will seize this singular opportunity to implement a monument to justice and place Canada as the global leader in addressing wrongful convictions.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.977
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0040.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.084
GPT teacher head0.366
Teacher spread0.282 · 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.

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 routes2
Has abstractyes

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