A Second Chance for the Harm Principle in Section 7? Gross Disproportionality Post-Bedford
Bibliographic record
Abstract
For what purposes can the state legally imprison its citizens? This basic question has been the source of rich legal scholarship, from Jon Stuart Mill’s harm principle to the storied debate between Sir Patrick Devlin and H.L.A. Hart over the place of legal moralism.1 The Canadian judiciary has not escaped the question. In the 2003 R v Malmo-Levine (“Malmo-Levine”) decision, the Supreme Court of Canada (“SCC”) rejected the notion of the harm principle as a principle of fundamental justice and, thus, a source of protection under section 7 of the Canadian Charter of Rights and Freedoms (the “Charter”).2 In a powerful dissent, Justice Arbour found that the state cannot resort to imprisonment for acts that do not cause or risk harm to others. In subsequent decisions, the Court has identified and elaborated on both the recognized principles of fundamental justice3 and the appropriate frameworks for assessing harm.4 This paper will argue that the gulf between the majority and Justice Arbour’s dissent in Malmo-Levine can best be addressed by adopting a harm sub-rule within the fundamental principle of justice barring ‘grossly disproportionate’ laws. This harm sub-rule will put forward that a criminal law will be found to be grossly disproportionate where the punishment is imprisonment and the object of the law does not include the prevention of non-trivial harm or risk of harm to others. This paper will begin by examining the Court’s exploration of the harm principle in Malmo-Levine, as well as its characterization of gross disproportionality in Bedford. The proposed sub-rule will then be presented, and the case will be made that its adoption would serve to clarify the values guiding the application of the gross disproportionality principle and also address the core of Justice Arbour’s concern in Malmo-Levine. Finally, possible counter arguments will be considered, as well as the special circumstance of morality based crimes.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.012 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".