Seeking Leave to Appeal to the Supreme Court of Canada for Personal Injury Cases
Bibliographic record
Abstract
Advocates contemplating seeking Leave to Appeal to the Supreme Court of Canada in personal injury cases face a unique decision calculus. The strategy at this Court is different from that of other appellate courts because the Supreme Court of Canada uses a particular test for granting Leave: “public importance.” One must first ask for Leave from the Supreme Court to even get to a hearing on the merits. When one’s personal injury appeal is competing on the Supreme Court’s Leave docket with other cases bringing issues such as unconstitutional search and seizure, equality rights, the separation of Quebec, and freedom of expression, the task of imbuing one’s case with “public importance” becomes a challenge. This article aims to offer some strategy behind the Leave process by removing some of the mystery so that personal injury lawyers and their clients can make informed decisions about this potentially important step.
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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 | 0.011 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.033 | 0.008 |
| Scholarly communication | 0.014 | 0.004 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.018 | 0.016 |
| Insufficient payload (model declined to judge) | 0.010 | 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".