Simplifying Canadian Negligence Actions Against Public Authorities – Or Maybe Not
Bibliographic record
Abstract
Many lawyers and judges believe that despite the unique statutory origins of public authorities, they should be held liable in negligence exactly like any private party. This article suggests that public authority negligence law could be remarkably simplified without any adverse consequences by adopting precisely such a test for recognizing a duty of care- recognizing a prima facie duty of care whenever a duty would lie in private party negligence in the same or meaningfully analogous situations. The more challenging case is the one in which the plaintiff seeks to establish a unique duty of care owed by a public authority on grounds that would not support a cause of action against a private defendant. The article suggests that it is time to acknowledge that such cases do exist, and time to justify them, if they can be justified, as unique efforts to expand judicial control of governments and public authorities. Proximity as we know it provides no such justification.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.010 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".