Bibliographic record
Abstract
adoption of a policy by some agent, where policies include as limiting cases plans (policies adopted for just one occasion) and actions (plans with only one component), and the agent adopting the policy may or may not be identical to the set of individuals carrying out the reasoning. Philosophers are interested in practical reasoning from two points of view: explanation and guidance; for the distinction, see Raz's introduction to his (1978). The explanatory interest leads them to consider such questions as whether a desire-belief model is the correct explanation of intentional action, whether reasons are causes, how akrasia ("weakness of will") is possible, what is the difference between akrasia and (possibly self-deceptive) hypocrisy, and whether all reasoning-produced motivation is partly derivative from motivation already present in the reasoner ("motivational internalism"). Although the investigation of such questions is sometimes relevant to questions related to guidance, and ind
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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 | 0.009 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.022 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.013 | 0.017 |
| Insufficient payload (model declined to judge) | 0.036 | 0.013 |
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".