Modernizing Judicial Review of the Exercise of Prerogative Powers in Canada
Bibliographic record
Abstract
Despite judicial pronouncements that the source of government power, whether statutory or prerogative, should not affect judicial review, Canadian courts respond much more tentatively when asked to review exercises of prerogative powers than exercises of statutory powers. Courts (1) define prerogative powers in a way that makes it difficult to precisely articulate their existence and scope; (2) frequently avoid judicially reviewing exercises of prerogative powers by applying peculiar justiciability tests; and (3) when they do engage in judicial review, generally limit themselves to a conservative form of procedural review. This article proposes that courts reform judicial review of the exercise of prerogative powers by (1) adopting a principled approach to defining prerogative powers that starts with distinguishing the Crown’s prerogative powers from its natural person powers; (2) abandoning peculiar interest-based and subject matter justiciability tests in favour of a test that turns on the nature of the question, and maintaining a subject matter justiciability test only for exercises of prerogative powers that are integral to the democratic process; and (3) applying standard principles of administrative law to judicial review of the existence, scope, and exercise of prerogative powers.
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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 | 0.019 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.012 | 0.007 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".