Bibliographic record
Abstract
This history of the modern introduction of assisted suicide in North America follow a tortuous course, with complete rejection of the idea, to implementation in many of its jurisdictions. North America was not a leader in this approach to end-of-life care, with the Netherlands and Belgium playing that role. Tracing the path from a felonious and ethically anathematic place in North American society it was resurrected into a legally and ethically acceptable practice over a period of two decades. The historical course of PAS (Physician Assisted Suicide) and MAID (Medical Assistance in Dying) in many ways mimicked the evolution of other major changes in our view of the world, and like assisted suicide, experienced almost universal rejection and ultimately the embrace of those people and institutions that initially rejected the ideas first expressed by thoughtful and heroic persons. Galileo Galilei was one of the icons of science and discovery: he was almost burned at the stake during the Inquisition only to be “resurrected” to his place in the pantheon of great thinkers – but it took almost four hundred years to reach that pinnacle. We must be very careful how we interpret new ideas and thoughts about the process we apply and the consequences if we reject them.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.008 |
| Insufficient payload (model declined to judge) | 0.021 | 0.008 |
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".