Employing Older Prisoner Empirical Data to Test a Novel s 7 Charter Claim
Bibliographic record
Abstract
This article builds the case for expanding s 7 of the Charter of Canadian Rights and Freedoms to apply to prison regulations and decisions in the specific context of an aging prison population. As original empirical data shows, prisons are highly insensitive to age-related problems, and inappropriate or insufficient medical treatment receives official sanction from a wide range of correctional documents. The stark inadequacies of the current system endanger older prisoners’ security of the person, and sometimes their lives, in ways that violate their rights under s 7, since the deprivations they suffer result from legislative policies and state conduct that are by turn arbitrary, overbroad, and grossly disproportionate. While s 7 has not been used to review such administrative documents or actions before, such a review is both feasible and highly desirable given the current lack of substantial access to justice by prisoners, their heightened vulnerability, and the evolution of the section 7 jurisprudence.
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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 | 0.089 | 0.215 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".