How to Legalize Medically Assisted Death in a Free and Democratic Society
Bibliographic record
Abstract
In 2015, the Supreme Court of Canada struck down the criminal law prohibiting physician assisted death in Canada. In 2016, Parliament passed legislation to allow what it called 'medical assistance in dying (MAID).' The authors first describe the arguments the Court used to strike down the law, and then argue that MAID as legalized in Bill C-14 is based on principles that are incompatible with a free and democratic society, prohibits assistance in dying that should be permitted, and makes access to medically-assisted death unnecessarily difficult. They then propose a version of MAID legislation ('Ideal MAID') that gives proponents and opponents of MAID everything they can legitimately want, contend that it is the only way to legalize MAID that is compatible with a free and democratic society, and conclude that it is the way to legalize MAID in Canada and other similarly free and democratic societies.
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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 | 0.029 | 0.046 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.024 | 0.093 |
| Scholarly communication | 0.016 | 0.013 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.020 | 0.024 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".