Thin-Skull Plaintiffs, Socio-Cultural "Abnormalities" and the Dangers of an Objective Test for Hypersensitivity
Bibliographic record
Abstract
The extent to which “hypersensitivity” can serve as a legal basis for demanding additional compensation has always been a controversial issue in tort law. A key challenge facing courts lies in determining how the “thin-skull rule,” traditionally related to physical conditions that predispose an individual to additional injury, can be applied to claims from “hypersensitive” plaintiffs citing personality-linked vulnerabilities of a religious, socio-cultural, or psychiatric nature. This article critically evaluates the viability of the “ordinary-fortitude test” adopted by the Supreme Court of Canada in Mustapha v. Culligan, and discusses the relative merits of a “multi-factorial test” in determining the admissibility of personalitylinked “thin-skull claims.” In this regard, a fact-specific, contextual approach that considers the causal nexus between the defendant’s negligence and the plaintiff’s injury would provide a more flexible framework with which to measure liability than an artificially-defined “one-size-fits-all” standard of “psychological resilience” in an increasingly multicultural Canada. En droit de la responsabilite civile delictuelle, la mesure dans laquelle l’hypersensibilite peut etre utilisee comme base juridique pour reclamer une indemnite additionnelle a toujours ete une question controversee. Un grand defi que doivent relever les tribunaux est de determiner comment la doctrine de la vulnerabilite de la victime, traditionnellement liee aux affections physiques qui font qu’une personne est predisposee a subir des prejudices additionnels, peut etre appliquee aux reclamations par des demandeurs hypersensibles qui invoquent des vulnerabilites de nature religieuse, socioculturelle ou psychiatrique liees a leur personnalite. L’article evalue de maniere critique la viabilite du critere de la resilience ordinaire adopte par la Cour supreme du Canada dans Mustapha c. Culligan, et discute du merite relatif d’un critere multifactoriel pour determiner l’admissibilite de reclamations liees a la personnalite et fondees sur la doctrine de la vulnerabilite. A cet egard, une approche contextuelle, fondee sur les faits, qui examine le lien de cause a effet entre la negligence de la partie defenderesse et le prejudice subi par la partie demanderesse offrirait, pour mesurer la responsabilite, une structure plus souple qu’une norme de « resilience psychologique » universelle definie artificiellement dans un Canada de plus en plus multiculturel.
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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 | 0.017 | 0.074 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".