Bibliographic record
Abstract
Bioethics theories are supposed to develop ethical principles, which allow for the governance of science, technology, and biomedical research. This article presents evidence for the lack of a disability rights approach, or even an acceptance of one, in the development of bioethics theories. The author also describes the debate on bioethics issues as they relate to disabilities, using as an example the debate over sex selection and disability “deselection.” Characteristics labeled as disabilities, a term that often is used as a synonym for defects, diseases, and subnormal abilities, are seen as “medical problems” in need of medical solutions. An “animal farm” philosophy appears to dominate the debate over bioethics issues and the development of bioethics theories as they pertain to disabilities. In this philosophy, characteristics labeled as medical problems are treated differently from characteristics labeled as societal problems, making the acceptance of a disability rights approach impossible because such an approach perceives disability within a social justice framework rather than a medical one.
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.
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 | 0.022 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.064 |
| Scholarly communication | 0.019 | 0.020 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.020 | 0.020 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".