The Moral Permissibility of Providing Medical Assistance in Dying in Canada: An Ethical Framework for Professional Practice
Bibliographic record
Abstract
Although medical assistance in dying (MAiD) is legally permitted in Canada under defined statutory conditions, this legal framework does not determine when it is morally permissible for a healthcare professional to provide MAiD. This paper explicitly examines the normative distinction between legal and ethical MAiD practice. It argues that the medically related eligibility criteria, such as incurability, irreversible decline, and intolerable suffering, do not function as objective medical criteria but instead presuppose and reinforce patient autonomy. As a result, MAiD assessments are often reduced to procedural confirmations of autonomy rather than substantive medical assessments. Thus, autonomy has become the de facto justification for the provision of MAiD, even though Canadian law does not regard autonomy alone as a sufficient condition. This paper examines the discretionary structure of MAiD practice and demonstrates that every decision to provide MAiD involves a normative judgment on the part of the healthcare professional. To guide that judgment, an ethics framework grounded in the fiduciary duties of healthcare professionals is proposed. Using the four core principles of healthcare ethics, this framework holds that it is morally permissible for a healthcare professional to provide MAiD only when: 1) the patient is autonomous, understood in terms of capacity, voluntariness, and informed consent; 2) the intervention satisfies the principles of beneficence and nonmaleficence; and 3) the request arises from a context of justice, in which a medical condition renders the patient unable to act on their autonomous wish to die without assistance.
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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 | 0.016 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.025 | 0.056 |
| Scholarly communication | 0.016 | 0.004 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.009 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 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".