Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Medical professional societies have traditionally opposed physician-assisted suicide and euthanasia (PAS-E), but this opposition may be shifting. We present 5 reasons why physicians shouldn't be involved in PAS-E. 1. Slippery slopes: There is evidence that safeguards in the Netherlands and Belgium are ineffective and violated, including administering lethal drugs without patient consent, absence of terminal illness, untreated psychiatric diagnoses, and nonreporting; 2. Lack of self-determination: Psychological and social motives characterize requests for PAS-E more than physical symptoms or rational choices; many requests disappear with improved symptom control and psychological support; 3. Inadequate palliative care: Better palliative care makes most patients physically comfortable. Many individuals requesting PAS-E don't want to die but to escape their suffering. Adequate treatment for depression and pain decreases the desire for death; 4. Medical professionalism: PAS-E transgresses the inviolable rule that physicians heal and palliate suffering but never intentionally inflict death; 5. Differences between means and ends: Proeuthanasia advocates look to the ends (the patient's death) and say the ends justify the means; opponents disagree and believe that killing patients to relieve suffering is different from allowing natural death and is not acceptable. CONCLUSIONS: Physicians have a duty to eliminate pain and suffering, not the person with the pain and suffering. Solutions for suffering lie in improving palliative care and social conditions and addressing the reasons for PAS-E requests. They should not include changing medical practice to allow PAS-E.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it