Bibliographic record
Abstract
This paper defends the doctrine that moral requirements are categorical in nature. My point of departure is John McDowell’s 1978 essay, “Are Moral Requirements Hypothetical Imperatives?”, in which McDowell argues, against Philippa Foot, that moral reasons are not conditional upon agents’ desires and are, in a certain sense, inescapable. After expounding McDowell’s view, exploring his idea that moral requirements “silence” other considerations and discussing its particularist ethos, I address an objection that moral reasons, as McDowell conceives them, are fundamentally incomplete in ways only a full-bloodedly Kantian appeal to pure practical reason can remedy. I conclude that the objection fails: ordinary moral reasons do not stand in need of a grounding in Reason. There is no prospect of deriving them from a supreme principle of morality or other canons of rationality. Ordinary reasons are sufficient in themselves, though their significance can be elucidated and illuminated by various strategies — some broadly Aristotelian, some drawing inspiration from Kant’s formula of humanity — in ways that can strengthen and vindicate them. Notwithstanding the failure of the objection, I conclude by reflecting on how Kantian insights can yet play a significant role in a McDowellian view of moral deliberation and moral education.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".