Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
I explore a connection between Robert Nozick's account of decision value/symbolic utility in The Nature of Rationality 1 and F. P. Ramsey's discussion of ethically neutral propositions in his 1926 essay ‘Truth and Probability’, 2 a discussion that Brian Skyrms in Choice and Chance 3 credits with disclosing deeper foundations for expected utility than the celebrated Theory of Games and Economic Behavior 4 of von Neumann and Morgenstern. Ramsey's recognition of ethically non-neutral propositions is essential to his foundational work, and the similarity of these propositions to symbolic utility helps make the case that the latter belongs to the apparatus that constructs expected utility, rather than being reducible to it or being part of a proposal that can be cheerfully ignored. I conclude that decision value replaces expected utility as the central idea in (normative) decision theory. Expected utility becomes an approximation that is good enough when symbolic utility is not at stake.
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.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it