Bibliographic record
Abstract
Luck, Value, and Commitment: Themes from the Ethics of Bernard Williams contains versions of papers presented at a conference entitled Themes from the Ethics of Bernard Williams held at the University of Leeds in the summer of 2009.1 As the book’s title suggests, it does not pretend to provide systematic or definitive expositions of Williams’s work. Instead, the articles collectively illustrate just how wide-ranging and deep Williams’s influence has been, even among those philosophers who disagree fundamentally with some of his claims and who admit to finding some of his arguments less than persuasive. The volume contains an introduction by the editors and 11 papers, arranged across five sections, the first three of which reflect central themes in Williams’s work. The section ‘Ethical Theory’ includes a paper by Brad Hooker (‘Theory versus Anti-Theory in Ethics’) in which he challenges arguments (including some of Williams’s) for the ‘anti-theory’ position in ethics and a paper by Philip Pettit (‘The Inescapability of Consequentialism’) that targets Williams’s objections to consequentialism in particular. Susan Wolf’s paper (‘One Thought Too Many: Love, Morality, and the Ordering of Commitment’) explores what might be involved in upholding or withdrawing an unconditional commitment to morality. The section ‘Moral Luck’ contains three papers, each of which I will discuss at greater length below and all reflecting on the ways in which what we are responsible for and whether our actions are justified can be subject to moral luck. The section ‘Reasons and ‘Ought’’ includes a paper by Michael Smith (‘A Puzzle About Internal Reasons’) in which he defends and develops an internalist account of reasons, in part by showing how imagination can contribute to an agent’s deliberating correctly, and one by Ulrike Heuer (‘Thick Concepts and Internal Reasons’) that argues that Williams’s understanding of ‘thick’ ethical concepts and reasons internalism are incompatible. The third paper in this section (John Broome’s ‘Williams on Ought’) is the most strictly exegetical of the papers, and it focuses on Williams’s account of the normative concept ‘ought’. The last two papers are each granted their own section. Jonathan Dancy’s paper (‘McDowell, Williams, and Intuitionism’) is prompted by Williams’s criticism of the kind of intuitionist epistemology he thinks McDowell is committed to; Gerald Lang argues in ‘Discrimination, Partial Concern, and Arbitrariness’ that speciesism has little in common with racism or sexism.
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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.061 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| 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".