Assisting Suicide: An Analysis of the Legal (i.e., Moral) Arguments in Judgments of the Supreme Court of Canada in the Sue Rodriguez Case
Bibliographic record
Abstract
The prohibition of assisting suicide has come under challenge in Canada, the United States, and other Western countries. This chapter outlines non-lawyers in the debate that took place in the Sue Rodriguez case in the Supreme Court. When the arguments on which the case was decided are set out, many readers may be surprised to find out that they are not at all "technical legal arguments" comprehensible only to legal experts. It is often assumed by the general public that a competent, intelligent appraisal of a court judgment on the constitutionality of a law would require a great deal of legal training and expertise. It becomes clear in reading judgments, particularly in Charter cases, that the justices are not writing only for other justices and lawyers. To allow assistance in suicide contradicts one of the values which the state has a duty to protect, namely, the intrinsic value of human life or the inherent dignity of the human person.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.020 | 0.010 |
| Scholarly communication | 0.010 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 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".