Bibliographic record
Abstract
Recent Russell scholarship has made clear the importance of Russell’s contributions to ethical theory. But his provocative two-page 1922 paper, “Is There an Absolute Good?”, anticipating by two decades what has come to be called “error theory”, is still little known and not fully understood by students of Russell’s ethics. In that little paper, never published in Russell’s lifetime, he criticizes the “absolutist” view of G. E. Moore; and, with the help of his own 1905 theory of descriptions, he exposes what he takes to be the fallacy underlying Moore’s (and his own earlier) arguments regarding value judgments and puts forward a new analysis which preserves the “absolutist” meaning at the cost of rendering all value judgments false. This article attempts to: (1) make clear just what Russell was doing in his little paper and how to understand it in the evolution of his metaethical thinking, (2) defend his 1922 theory against some recent criticisms, and (3) suggest the most likely reasons why he so quickly abandoned his new theory.
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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.003 | 0.037 |
| Scholarly communication | 0.005 | 0.013 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.007 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".