Unilateral Withholding and Withdrawl of Potentially Life-Sustaining Treatment: A Violation of Dignity Under the Law in Canada
Bibliographic record
Abstract
In this paper, I review Canadian law in relation to the unilateral withholding or withdrawal of potentially life-saving treatment, and I look at such questions as whether physicians are legally permitted to unilaterally put a do-not-resuscitate (DNR) order on a patient's chart. I explore who has the legal authority in Canada to decide on withholding and withdrawal of potentially life-sustaining treatment, and I conclude that unilateral withholding and withdrawal is a violation of strong social commitment to dignity as it is understood and reflected in the law by the Supreme Court of Canada. I then offer a concrete proposal for institutional policy with respect to unilateral withholding and withdrawal of treatment in light of the law.
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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 | 0.010 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.016 | 0.024 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.011 |
| 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".