Section Seven and the Right to Die: A Critical Analysis of the Issue of Doctor-Assisted Suicide in Canada
Bibliographic record
Abstract
This research project attempts to answer the question of whether or not those who are terminally ill, of sound mind, and have a physical disability preventing them from taking their own life should have the moral and legal right to assisted dying in Canada, if they so choose. The study reviews how the Canadian Charter of Rights & Freedoms (1982) and the Criminal Code of Canada affect the right to die and provides a summary and analysis of two of the most prominent legal cases in Canada related to assisted dying: Rodriguez v. Canada (Attorney General) & British Columbia (Attorney General) [1993], in which ALS sufferer Sue Rodriguez was denied the right to assisted dying, and Carter v. Canada (Attorney General) [2012], in which plaintiff Gloria Taylor, also an ALS sufferer, was the only person in Canada to be granted a constitutional exemption to seek out assistance in dying—a case later referred to the Supreme Court of Canada. The research project also offers a moral analysis of assisted death from a variety of perspectives and scholarly backgrounds. It concludes by appealing to the Dutch example, in which assisted death is legalized and heavily regulated, and calls for a change to recognize the right to die.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 | 0.038 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.021 | 0.023 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.005 | 0.009 |
| 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".