Bibliographic record
Abstract
lives of more patients without obtaining the informed and considered consent of the patient.1,2 Nor does Somerville ask why, if there is so much serious abuse of euthanasia in the Netherlands, both houses of the Dutch parliament were prepared to vote overwhelmingly, after the publication and widespread discussion of both the 1990 and 1995 studies, to legalize a practice that had, hitherto, merely enjoyed immunity from prosecution.Nor does she consider why the Netherlands' neighbour, Belgium, appears ready to follow the Dutch example and become the next country to legalize voluntary euthanasia.Perhaps Somerville is not much interested in the facts because her opposition to euthanasia rests on something so vague that facts are scarcely relevant.She wants us to "think in terms of the secular sacred."The "secular sacred" is apparently something that we "have allowed science to obscure," but Somerville doesn't do much to dispel this obscurity.She wants us to develop a new sense of community and to focus on "trust and responsibility" rather than on individual rights.But trust is not an argument against voluntary euthanasia.The Dutch trust their doctors not to leave them to their suffering when they can't bear it any more and want to die.Somerville tells us that we "need to sing 'the song of life: the lyrics of love,'" but she never tells us how these lyrics will help those who, terminally ill and in pain or distress, see no point in enduring another month, week, or day of a life that has sunk forever below the level they consider acceptable.Why should they not be allowed to choose their own song?
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.282 | 0.179 |
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".