Bibliographic record
Abstract
In 1913 Russell gave up on the Moorean good. But since naturalism was not an option, that left two alternatives: the error theory and non-cognitivism. Despite a brief flirtation with the error theory Russell preferred the non-cognitivist option, developing a form of emotivism according to which to say that something is good is to express the desire that everyone should desire it. But why emotivism rather than the error theory? Because emotivism sorts better with Russell’s Fundamental Principle that the “sentences we can understand must be composed of words with whose meaning we are acquainted.” I construct an argument for emotivism featuring the Fundamental Principle that closely parallels Ayer’s verificationist argument in Language, Truth, and Logic. I contend that Russell’s argument, like Ayer’s, is vulnerable to a Moorean critique. This suggests an important moral: revisionist theories of meaning such as verificationism and the Fundamental Principle are prima facie false. Any modus ponens from such a principle to a surprising semantic conclusion (such as emotivism) is trumped by a Moorean modus tollens from the negation of the surprising semantics to the negation of the revisionist principle.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".