Reframing assisted dying through the civil law: possibilities and challenges for the UK
Bibliographic record
Abstract
BACKGROUND: Current proposals for assisted dying in the UK are based on embedding it within a medical, healthcare model. This model is revealing challenges in safeguarding, monitoring and the impact on healthcare. OBJECTIVE: To explore if a different model is a safer, pragmatic and realistic alternative. METHODS: Existing medical models of assisted dying are reviewed and previously suggested alternatives are considered. The option of a socio-legal model is explained and examined in detail, including costs and likely numbers. FINDINGS: The authors propose that a socio-legal, civil law model that sits outside of healthcare is the most socially nuanced and ethical mode of regulation. CONCLUSIONS: A socio-legal model retains the choice to end life, but would ensure greater social safeguarding of vulnerable persons. It also enables healthcare professionals and organisations to focus on healing and care.
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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 | 0.031 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.049 |
| Scholarly communication | 0.022 | 0.020 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.019 | 0.020 |
| 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".