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Record W177687042 · doi:10.29173/alr183

The Problematic Revival of Murder Under Section 229(c) of the Criminal Code

2010· article· en· W177687042 on OpenAlexvenueaboutno aff
Kent Roach

Bibliographic record

VenueAlberta Law Review · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicLegal principles and applications
Canadian institutionsnot available
Fundersnot available
KeywordsLawCharterConvictionCriminal codeJurisprudenceMens reaSupreme courtJuryHomicidePolitical scienceRecklessnessAccidentalParliamentPretextCriminologyCriminal lawSociologyPoison controlMedicine

Abstract

fetched live from OpenAlex

This article examines the increased use of the murder offence under s. 229(c) of the Criminal Code/. It outlines how the objective foresight of death arm of s. 229(c) was struck down by the Supreme Court of Canada in R. v. Martineau, but still has not been repealed by Parliament. Three unfortunate cases are examined where trial judges erred by leaving the jury a copy of s. 229(c) with its unconstitutional objective arm present. The article examines the pre-Charter jurisprudence on s. 229(c) and suggests that the requirement that the accused have an unlawful object that is distinct from the actions that led to the death of the victim is still an important requirement. It then focuses on the second and most important mens rea requirement of s. 229(c), namely the requirement that the accused know that death was likely to occur. This fault requirement is examined and contrasted with recklessness and objective foresight of death, both of which are not constitutionally sufficient for a murder conviction. It is argued that some recent cases have treated accidental deaths during the pursuit of an unlawful object as murder under s. 229(c) and that such a result violates s. 7 of the Charter, including principles of fundamental justice that accidental deaths not be punished as murder and that unintentional harms not be punished as severely as intentional harms.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.990
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

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

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 head0.030
GPT teacher head0.338
Teacher spread0.307 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations2
Published2010
Admission routes2
Has abstractyes

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