The Origins, Evolution and Puzzling Irrelevance of Jury Recommendations in Second-Degree Murder Sentencing
Bibliographic record
Abstract
Section 745 of the Criminal Code is currently the only area of Canadian sentencing law that contemplates a role for juries. It grants juries the ability to recommend periods of parole ineligibility immediately following a guilty verdict in second-degree murder cases. This power is a remnant of a 1961 amendment to the Criminal Code that empowered juries to recommend clemency in capital murder cases. Although capital punishment has long since been repealed, jury involvement in sentencing persists — at least on paper. This article demonstrates that despite the codification of jury recommendations, Canadian courts have shown remarkable reluctance to give them meaningful weight in sentencing. A survey of the jurisprudence reveals that courts have several concerns related to jury recommendations, including the jury’s limited understanding of the legal principles of sentencing and the undue burden that the additional responsibility places on the already exhausted jurors. Although some courts pay lip service to jury recommendations, it is evident from the jurisprudence that the courts consider the power to be irrelevant. After weighing the potential benefits of retaining jury recommendations, this article argues that they have been judicially repealed for sound reasons of principle and policy, and accordingly should be formally removed from the Criminal Code.
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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 | 0.025 | 0.100 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.019 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".