End-of-Life Decisions: Physician Assisted Suicide in Canada
Bibliographic record
Abstract
Amongst other countries where physician assisted suicide (PAS) has been legalized, Canada have just decriminalized physician assisted suicide. Most Canadians are in support of change of the Criminal code which forbids persons from aiding or abetting suicide and to give consent to have death inflicted on them, that the law should be legally acceptable and careful regulations should be put in place for patients who are suffering from incurable sickness to be able to request for PAS. \nOn February 6th 2015, the Supreme Court of Canada (SCC) ruled against the law that violates the right of requesting for physician-assisted death for a ‘‘competent adult person who (1) clearly consents to the termination of life and (2) has a grievous and irremediable medical condition (including an illness, disease or disability) that causes enduring suffering that is intolerable to the individual in the circumstances of his or her condition.” The Court suspended its declaration of invalidity so that it would not come into effect for 12 months, and then, on 15 January 2016, granted a further four-month extension to that suspension. \nThe essence of this work is to review and enlighten the public on the issue of PAS in Canada and how far Canadians have come in achieving success in this light. Also, I will be looking at some other countries that have been practicing PAS.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.021 | 0.006 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".