Assisted Death and the Slippery Slope — Finding Clarity Amid Advocacy, Convergence, and Complexity
Bibliographic record
Abstract
This paper unpacks the slippery slope argument as it pertains to assisted death.The assisted-death regimes of the Netherlands, Belgium, Luxembourg, Switzerland, and the states of Washington and Oregon are discussed and examined with respect to the slippery slope analytical rubric.In addition to providing a preliminary explanation of how the slippery slope argument has been academically defined and constructed, the paper examines assisted-death models from the perspective of considering what might exist at the top and at the bottom of the slippery slope. It also explores the nature and scope of safeguards implemented to avoid slippage, and shows that what lies at the top and bottom of the slippery slope may be different from jurisdiction to jurisdiction.After identifying some of the recent concerns that have arisen within each of the jurisdictions (concerns that might be viewed by some as evidence of slide), the paper concludes by making note of certain critical issues in the current assisted-death debate that merit deeper examination.
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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 | 0.059 | 0.090 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.017 | 0.129 |
| Scholarly communication | 0.025 | 0.036 |
| Open science | 0.004 | 0.029 |
| Research integrity | 0.015 | 0.021 |
| Insufficient payload (model declined to judge) | 0.003 | 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".