Medical Assistance in Dying in Canada: An Ethical Analysis of Conscientious and Religious Objections
Bibliographic record
Abstract
Background: The Supreme Court of Canada (SCC) has ruled that the federal government is required to remove the provisions of the Criminal Code of Canada that prohibit medical assistance in dying (MAID). The SCC has stipulated that individual physicians will not be required to provide MAID should they have a religious or conscientious objection. Therefore, the pending legislative response will have to balance the rights of the patients with the rights of physicians, other health care professionals, and objecting institutions. Objective: The objective of this paper is to critically assess, within the Canadian context, the moral probity of individual or institutional objections to MAID that are for either religious or conscientious reasons. Methods: Deontological ethics and the Doctrine of Double Effect. Results: The religious or conscientious objector has conflicting duties, i.e., a duty to respect the “right to life” (section 7 of the Charter) and a duty to respect the tenets of his or her religious or conscientious beliefs (protected by section 2 of the Charter). Conclusion: The discussion of religious or conscientious objections to MAID has not explicitly considered the competing duties of the conscientious objector. It has focussed on the fact that a conscientious objection exists and has ignored the normative question of whether the duty to respect one’s conscience or religion supersedes the duty to respect the patient’s right to life.
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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 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.029 | 0.032 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.007 |
| 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".