Reconsidering the 'Recognizable Psychiatric Illness' Requirement in Canadian Negligence Law
Bibliographic record
Abstract
Courts have generally required litigants to prove that they have experienced a “recognizable psychiatric illness” (RPI) in order to be compensated for stand-alone mental harm resulting from negligent acts. This was not always the case. Before the 1970s, courts were traditionally content to work with the “no compensation for mere upsets” rule or to link mental harm to physical injury. But when the English Court of Appeal articulated the RPI requirement in Hinz v. Berry, Canadian courts were quick to adopt it as the threshold for plaintiffs’ claims, and have relied on it ever since. In the author’s view, however, the term “recognizable psychiatric illness” was not intended to denote a new, higher threshold.In the 2008 case, Mustapha v. Culligan of Canada Ltd, the Supreme Court of Canada did not use the term “recognizable psychiatric illness” in commenting on the threshold for compensable mental harm. The author argues that by avoiding the term, the Supreme Court invited courts to reconsider the matter, perhaps by adopting the lower, more flexible threshold that the injury be “serious and prolonged”, or more likely, by reverting to the “mere upsets” threshold. At the very least, the author contends, the Court’s comments suggest that the RPI requirement is too high.Subsequent jurisprudence reveals that courts have been reluctant to agree with the author’s view of the importance of Mustapha, due to the fact that the Supreme Court did not explicitly reject Hinz and another foundational case, Guay v. Sun Publishing. The author argues that despite the iconic status of these two cases, neither one provides a compelling basis for the RPI requirement. Continuing to deny compensation to plaintiffs who cannot meet the RPI requirement is not only unfair but is also unsupported by precedent.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.022 | 0.019 |
| Scholarly communication | 0.011 | 0.004 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.021 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".