The (Re)Discovery of the Proportionality Principle in Sentencing in Ipeelee: Constitutionalization and the Emergence of Collective Responsibility
Bibliographic record
Abstract
This paper discusses two important developments following the Supreme Court’s decisions in Ipeelee/Ladue. First, it suggests that the Court’s first-time recognition of the proportionality principle in sentencing as a principle of fundamental justice under section 7 of the Charter is likely to have tremendous impact on sentencing the ory and practice by offering new constitutional grounds to challenge mandatory minimal sentences and arbitrarily disproportionate sentences. Second, this paper builds on the Court’s development around the notion of degree of responsibility to propose a new conception of shared and collective responsibility that includes the responsibility of state agents and of the state in the perpetration of crime and allows sentencing judges to reduce or nullify offenders’ sentences accordingly.
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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 | 0.028 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.025 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.007 | 0.018 |
| Insufficient payload (model declined to judge) | 0.002 | 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".