Bibliographic record
Abstract
Eric Nelson has recently argued that John Rawls’ interpretation of the maxim to respect persons as ends in themselves which grants priority to our least-advantaged citizens violates the liberal commitment to neutrality towards each person’s capability to choose her or his conception of the good. This violation is revealed by the sectarian character of Martha Nussbaum’s list of capabilities, her Aristotelian extension of Rawls’ distributive ethics. I argue that Nelson advances an elitist interpretation of the non-violability of persons, in which the capabilities of oneself are set in opposition to those of an other. He thus overlooks for his purposes the anti-sacrificial telos of the Rawlsian principles of justice which articulates the capabilities of oneself as another. Nelson’s elitism may itself be traced to Nussbaum’s rejection of Rawls’ distributive figuration of capability, the Aristotelian heritage of which is developed by Paul Ricoeur and which underwrites civic phronēsis on societal norms of reciprocity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.004 |
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; both teacher heads agree on what is shown here.
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".