Assisted dying for non-terminal suffering: a legal analysis of existential distress as a threshold condition in Canada
Bibliographic record
Abstract
Canada’s medical assistance in dying (MAiD) framework has transitioned from a complete prohibition to a regulatory scheme that permits access for individuals whose conditions are not imminently life-ending. This article examines whether persistent existential distress, including psychological or spiritual suffering associated with illness, may satisfy the eligibility criteria under the current legal regime. While the analysis recognises that such suffering can fall within the statutory threshold, it maintains that inclusion should remain narrow and guided by strong procedural safeguards. The central concern is how law and policy can acknowledge non-physical suffering without weakening protections for those who may still recover or require support. Through doctrinal analysis, it traces the evolution from the Supreme Court’s Carter decision to subsequent statutory amendments, with particular attention to the tension between safeguarding individual autonomy and protecting those considered vulnerable. Psychological literature is employed to delineate the clinical features of existential suffering and the complexities of assessing irremediability. Comparative insights from Belgium and the Netherlands illuminate procedural safeguards and mechanisms for error reduction. The article recommends statutory clarification, comprehensive psychosocial assessment protocols, and enhanced oversight to maintain ethical consistency and minimize foreseeable risk.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.024 | 0.011 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".