Bibliographic record
Abstract
In this article, the administrative law decisions rendered by the Supreme Court of Canada during the 2004-2005 term are reviewed. These decisions addressed four major issues: i) exclusive and concurrent jurisdiction between competing adjudicative bodies; ii) the right to independent adjudication; iii) standard of review; and iv) expertise and deference. Questions relating to exclusive and concurrent jurisdiction occupied the most significant part of the Supreme Court's administrative law energy during the 2004-2005 term. The author analyzes these decisions on jurisdiction, paying particular attention to the many divides between the members of the Court. She argues that the decisions on jurisdiction ratione material between competing tribunals reflect a contest of two administrative law values that have become central to the Canadian administrative state: expertise and expediency. The Supreme Court's approach, which tends to privilege expediency, may have the effect of denying litigants the opportunity to obtain the most appropriate resolutions to their disputes - resolutions that benefit from the expertise and experience of the tribunals themselves. She also highlights the value of including the individual litigant's view of the dispute in the search for its essential character and possible parameters to the essential character test. Finally, the author discusses the issues related to interpreting legislative intent that arise in the cases concerning the right to independent adjudication and core expertise.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.019 | 0.015 |
| Scholarly communication | 0.020 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.010 | 0.009 |
| 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".