Bibliographic record
Abstract
Abstract Smith (Philosophy and Phenomenological Research, 55, 1995, 109) and Manne (Philosophical Studies, 167, 2014, 89), both following Williams (Making sense of humanity, Cambridge University Press, Cambridge, 1995), have developed advice‐based models of practical reasons. However, advice is not an apt model for reasons. The case for such pessimism is made by examining the positions of Smith and Manne first as attempts to explain the nature of reasons, then as suggestions for reforming our conception of reasons for action. The explanatory projects fail: both views either omit or distort ordinary reasons. The reforming project fails because insufficient reason is provided for thinking that the significant extent of revision offered by these models is worth it. Overall, the advice‐based approach to understanding reasons fails because advising is a social practice to aid with decisions, whereas reasons are considerations that favour action regardless of whether these considerations are inputs to or outputs from such a practice.
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.
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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.035 |
| Scholarly communication | 0.010 | 0.017 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".