Can Norman Daniels Help You Get a Wheelchair? A Commentary on Durocher et al.
Bibliographic record
Abstract
Durocher and colleagues (2019) argue that Norman Daniels’s notion of just health could provide a useful framework for decreasing inequities in access to assistive technology. I argue that it would provide limited help for two reasons. First, Daniels’s reliance on normal species functioning as the goal of health care and his assumptions regarding the impact of normal species functioning on reasonable life projects create substantial difficulties for application to assistive technology. Second, although Daniels’s requirements for distributive justice provide a critical starting point for any discussion of health equity, these requirements appear already met within current assistive technology funding schemes.
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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 | 0.015 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.018 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.007 | 0.005 |
| Research integrity | 0.062 | 0.072 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".