Bibliographic record
Abstract
introduction 'I do not myself think very well of what I have said on ethics', wrote Russell in extreme old age ( Dear Bertrand Russell , p. 132). And most subsequent philosophers have agreed with him. Either they do not think very well of what he said or they do not think of it at all. Until very recently, Russell hardly rated a mention in most books and bibliographies on twentieth-century ethics. His most anthologised paper on the subject is 'The Elements of Ethics' (1910) in which he expounds, not his own ideas, but the ideas of his colleague and sometime friend, G.E. Moore. Even dedicated Russell fans such as John Slater ( Bertrand Russell (1994)) and Anthony Grayling ( Russell 1996) are a bit lukewarmabout his theoretical ethics, whilst R.M. Sainsbury in his 'Arguments of the Philosophers' book Russell (1979), is positively dismissive: 'I have left aside his work on moral philosophy, on the grounds that in both its main phases, it is too derivative to justify a discussion of it'. In the first phase, represented by 'The Elements of Ethics' (1910), Sainsbury suggests that Russell's ideas were derived from G.E. Moore, and in the second, represented by Human Society in Ethics and Politics , they were 'close to Hume's, with a dash of emotivism' (Sainsbury 1979, p. x).
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.069 | 0.032 |
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".