Bibliographic record
Abstract
Sidgwick famously claimed that an argument in favour of utilitarianism might be provided \nby demonstrating that a set of defensible philosophical intuitions undergird it. This paper \nfocuses on those philosophical intuitions. It aims to show which specific intuitions Sidgwick \nendorsed, and to shed light on their mutual connections. It argues against many rival \ninterpretations that Sidgwick maintained that six philosophical intuitions constitute the selfevident \ngrounds for utilitarianism, and that those intuitions appear to be specifications of a \nnegative principle of universalization (according to which differential treatments must be \nbased on reasonable grounds alone). In addition, this paper attempts to show how the \nintuitions function in the overall argument for utilitarianism. The suggestion is that the \nintuitions are the main positive part of the argument for the view, which includes Sidgwick's \nrejection of common-sense morality and its philosophical counterpart, dogmatic intuitionism. \nThe paper concludes by arguing that some of Sidgwick's intuitions fail to meet the conditions \nfor self-evidence which Sidgwick himself established and applied to the rules of common-sense \nmorality.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.005 | 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".