Rethinking Damages for Personal Injury: Is it too late to take the facts seriously?
Bibliographic record
Abstract
It is just a little over thirty years since the Supreme Court of Canada took Canada’s assessment of personal injury damages on a different tack in the trilogy.1 In hindsight, the view then taken on damages for non-pecuniary loss was prescient, for it foreshadowed movements now taken legislatively in the United States2 and Australia,3 and has parallels in the English Court of Appeal decision in Heil v. Rankin.4 The Supreme Court did not tackle the issue of lump sum verses periodic payment/reassessment in the trilogy, although it did express its views on this issue many years later.5 For obvious constitutional and jurisprudential reasons touching on the appropriate limits of judicial activism, and, one suspects, out of personal belief, the Supreme Court did not question the underlying premise of providing compensation for personal injury as a result of tortious conduct. The success of the Supreme Court’s intervention is perhaps best revealed by the fact that apart from some minor skirmishes over automobile insurance, there has
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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 | 0.016 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.032 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.021 | 0.032 |
| 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".