Tying Down the Tracks: Severity, Method, and the Text of Section 12 of the Charter
Bibliographic record
Abstract
Recent jurisprudence and academic commentary recognize two different ‘tracks’ for violating section 12 of the Charter. The severity track was developed in the Court’s jurisprudence considering the constitutionality of a host of mandatory minimum sentencing provisions. When assessing the constitutionality of such laws, the Court may consider the mandatory minimum sentence a hypothetical offender would receive and ask whether that penalty is grossly disproportionate when compared to the appropriate sentence for that offender. The methods track considers whether the means used to punish a person are cruel and unusual. Although the distinction between each track brings welcome analytical clarity, a more basic question remains: are both tracks supported by the text of section 12 of the Charter? In R v Hills, Justice Wakeling answered this question in the negative with respect to the severity track. I contend that his argument relies upon an unduly narrow interpretation of the text and purpose of the right not to be subjected to cruel and unusual treatment or punishment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.057 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.005 | 0.034 |
| Scholarly communication | 0.020 | 0.016 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.010 | 0.022 |
| Insufficient payload (model declined to judge) | 0.004 | 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".