Bibliographic record
Abstract
The strategy of developing an ontology or models of disability as a prior step to settling ethical issues regarding disabilities is highly problematic for two reasons. First, key definitional aspects of disability are normative and cannot helpfully be made value-neutral. Second, if we accept that the contested concept of disability is value-laden, it is far from obvious that there are definitive reasons for choosing one interpretation of the concept over another. I conclude that the concept of disability is better left ethically open-ended or broad enough to encompass the examination of various ethical issues (such as oppression, minority rights, or physical discomfort). Alternatively, the concept of disability could be altogether abandoned in order to focus on specific issues without being hindered by debates about the nature of disability. Only political costs, rather than conceptual considerations internal to the models, could be weighed against such a conclusion.
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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.045 |
| Scholarly communication | 0.012 | 0.022 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.006 | 0.010 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".