With a Little Help from Too Many Friends? Lessons from TWU and Comeau on Intervening Before the Supreme Court
Bibliographic record
Abstract
Under the Supreme Court of Canada’s (“SCC”) current approach to intervention, the Court grants leave to almost all parties seeking to intervene and allots them 10 pages for their written submissions and five minutes for their oral arguments. The authors argue that these constraints make it difficult for “friends of the court” to meaningfully engage with the SCC. At the heart of the problem is a screening policy that hinders interveners from providing, and the Court from receiving, assistance. The SCC’s approach restricts interveners who are advancing meritorious and nuanced positions to the same limits as those proffering the Court with generic or duplicative viewpoints. The result is one of mutual dissatisfaction: The Court does not get the full assistance that it could from interveners, and interveners — who are keen to assist on cases — cannot adequately fulfil their key objective. Instead, by surveying how the high courts in the United States and the United Kingdom treat interveners, the authors re-imagine the rules of intervention. While the proposed rules continue to be inclusive, they also provide interveners with greater opportunities to contribute to the development of the law and the framing of the issues. Specifically, the authors propose that the Court revise its screening policy in two ways: (1) any actor with relevant interests can file a factum (minimum of 20 pages); (2) only those interveners who provide distinct and helpful perspectives would be invited to make oral arguments, and given more than five minutes to make their arguments.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.058 | 0.050 |
| Scholarly communication | 0.031 | 0.015 |
| Open science | 0.005 | 0.008 |
| Research integrity | 0.022 | 0.024 |
| Insufficient payload (model declined to judge) | 0.008 | 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".