Subjectivism, instrumentalism, and prudentialism about reasons: On the normativity of instrumental transmission
Bibliographic record
Abstract
Abstract According to a subjectivist theory, normative reasons are grounded in facts about our desires. According to an instrumentalist theory, reasons are grounded also in facts about the relevant means to desired objects. These are distinct theories. The widespread tendency to conflate the normativity of subjective and instrumentalist precepts obscures two facts. First, instrumentalist precepts incorporate a subjective element with an objective one. Second, combining these elements into a single theory of normative reasons requires explaining how and why they are to be combined. I argue that the most plausible justification for combining the two elements—which appeals to a theory of well‐being—exposes the inadequacy of the instrumentalist theory: The grounds required to justify the instrumentalist combination are also grounds for the normativity of prudential precepts and with them practical reasons that may have no internal connection to an agent's conative, motivational states.
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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 | 0.016 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.049 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".