Unreasonable Disagreement?: Judicial–Executive Exchanges about Charter Reasonableness in the Harper Era
Bibliographic record
Abstract
Assessments of “reasonableness” are central to adjudicating claims under several Charter rights and the section 1 “reasonable limits” clause. By comparing Supreme Court of Canada rulings to facta submitted by the Attorney General of Canada to the Court, this article examines the federal government’s success under Prime Minister Harper at persuading the Supreme Court of Canada that its Charter infringements in the area of criminal justice policy are reasonable, and when they fail to do so, on what grounds. The evidence reveals that the Conservative government adopted a consistently defensive posture in court, never conceding that a law was unreasonable, and that this government was almost never able to defend an impugned criminal justice law under section 1. While several of those losses concerned pre-Harper era laws, the Court did reject several Conservative criminal justice policies, most notably some mandatory minimum sentencing laws. The article’s novel systematic analysis also shows that the Court sometimes rejected the federal government’s characterization of the legislative objective.
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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 | 0.034 | 0.081 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.023 | 0.025 |
| Scholarly communication | 0.021 | 0.009 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.003 | 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".