Care, Compassion, or Cost: Redefining the Basis of Treatment in Ethics and Law
Bibliographic record
Abstract
There are in two assumptions inherent in this issue's theme, both inimical to the traditional goals of medicine and to the standards of care it proposed. First, the idea that treatment must be limited for some (but not others) on the basis of cost was born in the early literature of bioethics. Second, that there is a quantifiable and diagnostically predictable period at the "end-of-life" where treatment is "futile," and therefore not worth supporting in a context of scarcity grew out of bioethics's construction of allocative protocols in the 1990s. This paper traces the history of these ideas as constructs grounded in neither natural scarcity nor in firm diagnostic categories. Their relation to issues of care is therefore suspect.
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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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.138 |
| Scholarly communication | 0.013 | 0.028 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.015 | 0.015 |
| Insufficient payload (model declined to judge) | 0.002 | 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".