Bibliographic record
Abstract
When facing a dilemma about what to do, rational agents will often encounter a conflict between what they ought to do, morally speaking, and what they most want to do. Traditionally we think that when there is a moral imperative for an agent to do something, even if she does not want to do it, she nevertheless ought to do it. But this approach inevitably fails to be able to explain why agents often choose to do what they most want, in many cases flouting such moral imperatives. The purpose of this thesis is to offer a plausible alternative to this way of understanding these deliberative dilemmas. I argue that communitarian moralism, the account according to which genuine moral imperatives are only imperatives on communities, rather than agents, and according to which agents’ moral conduct is necessarily bound up with her particular preferences, projects and commitments, is the most plausible way to understand dilemmas in which agents must choose between doing moral and self-interested actions.
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 | 0.009 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.013 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.056 | 0.010 |
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".