Bibliographic record
Abstract
This article examines the increased use of the murder offense 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of death arm of s. 229(c) was struck down by the Supreme Court of Canada in R. v. Martineau, but still has not been repealed by Parliament.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 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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.014 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.013 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".