On Two Interpretations of the Desire-Satisfaction Theory of Prudential Value
Bibliographic record
Abstract
This article considers two different ways of formulating a desire-satisfaction theory of prudential value. The first version of the theory (the object view) assigns basic prudential value to the state of affairs that is the object of a person's desire. The second version (the combo view) assigns basic prudential value to the compound state of affairs in which (a) a person desires some state of affairs and (b) this state of affairs obtains. My aims in this article are twofold. First, I aim to highlight that these are not mere notational variants, but in fact have quite different implications, so that this distinction is not one that the theorist of prudential value should ignore. More positively, I argue that the object view is better able to capture what is distinctive and appealing about subjective theories of prudential value, on any plausible account of what the central subjectivist insight is.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.034 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 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".