Bibliographic record
Abstract
This article draws attention to the post-Dunsmuir framework regarding the standard of review of administrative action and the Supreme Court of Canada’s reluctance to engage in grand theorizing about the general principles of judicial review. The article explores the uncertainty surrounding the application of the standard of reasonableness and what factors can or should be taken into consideration during its application. The article identifies four key problems — the scope of the post-Dunsmuir framework, the scope of its correctness category, the difficult relationship between the reasons given for a decision and the substantive reasonableness of the decision in question, and the emergence of difficult distinctions bedevilling the application of the reasonableness standard. Through identifying weaknesses in the current administration of reasonableness review, it is hoped that the courts, sooner rather than later, will adopt a unified approach for using the reasonableness standard of review.
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 | 0.148 | 0.214 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.009 | 0.004 |
| Science and technology studies | 0.008 | 0.069 |
| Scholarly communication | 0.023 | 0.019 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.013 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".