Williams, Scanlon, and the Normativity of Morality
Bibliographic record
Abstract
Most debates about the viability of a given moral theory are won and lost, or at least brought to an end, through resort to a familiar pattern of argument: if a theory calls for that course of action, can it really claim to offer a substantively correct account of morality? This debate operates on the plausible premise that a moral theory rises and falls with the substantive correctness of its prescriptions. But this debate is also premised on the idea that moral theory has a claim to make on us. Not everyone grants this premise. Indeed, Bernard Williams’ work presents a denial of the claim that moral theory has the normative authority to demand anything of us at all. This familiar inversion of the claim that morality is overly demanding is a serious objection to the task of working out a moral theory. It suggests that interlocutors in the debate detailed above claim ground to which moral theory is not ultimately entitled. This thesis details Contractualism’s capacity to answer to this challenge. In particular, this thesis defends the idea that Contractualism offers an account of inter-personal morality that is substantively correct and accessible to integrated agents. Contractualism’s account of inter-personal wrongness, and the powerful reasons we have to avoid wronging others, satisfies the twin conditions of substantive correctness and normative coherence.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".