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Record W4411585669 · doi:10.29173/alr2834

Legal Ethics for Crown Attorneys on Appeal

2025· article· en· W4411585669 on OpenAlexafffundvenue
Elizabeth Matheson, Andrew Martin

Bibliographic record

VenueAlberta Law Review · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicLegal Education and Practice Innovations
Canadian institutionsDalhousie University
FundersFondation pour la recherche juridique
KeywordsAppealCrown (dentistry)LawLegal ethicsLaw and economicsPolitical scienceSociologyMaterials science

Abstract

fetched live from OpenAlex

While there is extensive legal literature and case law addressing the role and ethical responsibilities of Crown attorneys, questions about that role and those responsibilities at the appellate stage are largely absent from the literature and somewhat scattered across the case law. In this article, the authors seek to address this gap by answering four key questions. The first is whether the ethical obligations of the Crown, as expressed in R. v. Boucher, apply at the appellate stage. Against the backdrop of this first question, the authors discuss when an appellate Crown may bring an appeal from an acquittal or from a sentence, when an appellate Crown may make concessions or abandon an appeal, and when an appellate Crown may take a different position than the Crown attorney at trial or upon sentence. The answers to these questions are important, though not especially surprising. The authors argue that both Boucher and prosecutorial discretion require appellate Crowns to resolutely — but fairly — seek justice on appeal, as at trial, even when this means taking a different position than the trial Crown or conceding an error by the trial Crown or the trial judge.

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)0.042
metaresearch head score (Gemma)0.127
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 score0.042
Threshold uncertainty score0.221

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0420.127
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0100.026
Scholarly communication0.0160.006
Open science0.0020.006
Research integrity0.0230.013
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 head0.115
GPT teacher head0.483
Teacher spread0.367 · 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 routes3
Has abstractyes

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