Can There Be Too Much Context In Administrative Law? Setting the Standard of Review in Canadian Administrative Law
Bibliographic record
Abstract
The Supreme Court of Canada has periodically altered its approach to judicial review in order to make it more coherent and easier for courts and litigants to understand. Central to judicial review is the choice of the standard of review a court is to apply in a particular case. The standard of review determines how deferential the court is to be to the executive decision-maker. The Court has shifted over time from a formal to a contextual approach to this choice and, most recently, at least partly towards a categorical approach. This most recent approach has been criticized as overly formalistic, neglecting important aspects of the context of particular decisions. This paper examines this shift in the process for choosing the standard of review from an institutional perspective. It discusses the factors that are important in selecting an approach to choosing the standard of review in a particular case. These factors include both the implications for the actual decision at issue as well as the effect on the decisions of other executive decision-makers, lower courts, individuals seeking to challenge decisions and the legislature.
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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 | 0.059 | 0.153 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.043 | 0.071 |
| Scholarly communication | 0.039 | 0.016 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.008 | 0.014 |
| 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".