Bibliographic record
Abstract
Je me propose d'examiner la solution davidsonnienne au problème de la duperie de soi afin de clarifier en quel sens il s'agit d'un acte intentionnel. Après une étude de quelques difficultés liées au concept même de duperie de soi, mon analyse met en lumière que la notion de partition de l'esprit que Davidson emprunte à son traitement de la faiblesse de la volonté ne peut être appliquée de manière satisfaisante à ce nouveau problème. J'indique ensuite que non seulement Davidson mais la majorité des philosophes qui étudient le phénomène ont négligé de donner un traitement adéquat du rôle qui est dévolu aux pro-attitudes dans la formation des croyances. Je reviens finalement à la question fondamentale, celle de savoir s'il est approprié de considérer que la duperie de soi est un acte intentionnel, afin de mettre en évidence le caractère paradoxal de tout raisonnement pratique qui prétendrait rationaliser un tel état ou processus.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.017 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.022 | 0.003 |
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".