Rethinking the Ramifications of Reasonableness Review: Stare Decisis and Reasonableness Review on Questions of Law
Bibliographic record
Abstract
The recent fashion in the Canadian law of judicial review is to apply the reasonableness standard of review to virtually any decision rendered by an administrative decision-maker. Reasonableness review is a deferential standard of review that requires a court to ensure that the administrative decision falls within a range of reasonable outcomes that are defensible in light of the facts and law. When reasonableness review is applied to questions of law, the Supreme Court has occasionally ruled that the question admits of only one reasonable interpretation and has affirmed or quashed an administrative decision on that basis.This article addresses the difficult question of whether a judicial decision affirming that a provision admits of only one reasonable interpretation is strictly binding on an administrative decision-maker interpreting that provision in the future. If reasonableness review is premised on deference, then deference ought to apply to an administrative decision-maker’s interpretation of that question in the future, even if it differs from the court’s interpretation. After situating this issue within the principled foundation of the Canadian law of judicial review, this article explores possible solutions to this problem, attempting to balance the need to protect the rule of law against the rationale for deference to administrative interpretations of law in the first place. It ultimately concludes by suggesting that, should Canadian courts continue to apply reasonableness review to virtually all questions of law, a uniquely administrative law approach to stare decisis will need to be developed in order to maintain a coherent and principled system of judicial review.
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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 | 0.047 | 0.093 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.018 | 0.115 |
| Scholarly communication | 0.027 | 0.020 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.015 | 0.023 |
| 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".