Patient responsibility for detrimental health outcomes: the defence of contributory negligence in medical negligence actions
Bibliographic record
Abstract
This thesis examines the increased use and success of the defence of contributory negligence in Canada and the United States. The approach is historical and comparative. First, the thesis considers the causes and effects of the increased use of the defence of contributory negligence in medical negligence actions. Second, the thesis surveys American and Canadian case law to analyze critically the evolving duties to which a patient must adhere in his/her own care. Finally, the thesis advocates a correlative approach to the doctrine of patient responsibility, as the conceptual framework with which to understand and adjudicate patient errors in medical negligence law. This thesis concludes that patients can be held responsible for their medical decisions, but such responsibility must be adjudicated equitably, in order to preserve and promote the integrity of the clinical relationship, and to ensure that patients are not held to an unreasonably high standard of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.013 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.043 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".