'Pulling the Patches' on the Patchwork Defence of Duress: A Comment on R. v. Aravena
Bibliographic record
Abstract
In R v Aravena, the Ontario Court of Appeal held that the common law defence of duress is available to persons charged as parties to a murder. In reaching this conclusion, the Court examined both the history and the purpose of the defence of duress and was guided by a “bedrock principle” of criminal law: “Criminal liability requires voluntary conduct.” Ultimately, the Court’s conclusion rests on a consideration and balancing of “the nature of duress defence, basic criminal law policies, and the operative principles of fundamental justice.” The result is a judgment that significantly contributes to “pulling the patches” of the patchwork mess4 of the defence that is duress, conducing to the further harmonization of the common law, codification, and the constitutional dimensions of the defence.
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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 | 0.019 | 0.048 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.017 | 0.026 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.011 | 0.005 |
| Research integrity | 0.092 | 0.074 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".