MAiD in Canada: Ethical Considerations in Medical Assistance in Dying
Bibliographic record
Abstract
Medical assistance in dying (MAiD) is unique among the arsenal of medical therapeutics though it does return us to a dilemma Hippocrates addressed 2400 years ago. It provides welcome relief for suffering patients and their families, but MAiD is not suicide – it is invited homicide. It is more like a death ritual than a therapeutic procedure. Unlike medical interventions, MAiD cures no diseases and true informed consent cannot be obtained. It separates the body from the soul and perceived doctors’ errors are punishable through criminal prosecution. If badly administered, it could undermine trust in the medical profession. The providers are also at risk for delayed remorse. As the inclusion criteria for MAiD become more relaxed, doctors who currently decide on candidates for MAiD should have access to established panels for guidance. The panels should include legal and ethical specialists.
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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 | 0.024 | 0.059 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.043 | 0.025 |
| Scholarly communication | 0.015 | 0.004 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.016 | 0.023 |
| 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".