Arbitrary Disproportionality: A New Charter Standard for Measuring the Constitutionality of Mandatory Minimum Sentences
Bibliographic record
Abstract
The development of section 12 jurisprudence began in 1987 with R. v. Smith. Since that time, any potential refinement of the “cruel and unusual” standard has been distracted by two methodological debates: The scope of “reasonable hypotheticals” and the role of constitutional exemptions. As a result, the jurisprudence has not moved beyond “gross disproportionality” and “outraging standards of decency”. In the process, any room for arbitrariness as a factor has evaporated. A few recent mandatory minimum sentence decisions have breathed some life into section 12 for sentencing purposes. Perhaps more importantly, the concept of arbitrariness has been embedded in section 7 whenever the right to life, liberty or security of the person is in jeopardy. This may provide more traction in mandatory minimum sentence challenges since it requires an analysis that includes identifying the societal interest that the sentence is intended to promote.
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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 | 0.059 | 0.207 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.016 | 0.007 |
| Science and technology studies | 0.005 | 0.010 |
| Scholarly communication | 0.009 | 0.013 |
| Open science | 0.004 | 0.010 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".