Bibliographic record
Abstract
Dans cette thèse en psychologie morale, je m’intéresse au rôle de l’imagination dans la perception morale. Je soutiens que l’imagination y a une fonction épistémique dans la mesure où – en s’accompagnant ou non d’émotions – elle nous révèle des normes, des valeurs ou des vertus morales qui seraient autrement passées inaperçues. En simulant des croyances et des perceptions, l’imagination nous permet d’accéder à ces caractéristiques d’une situation moralement pertinentes, mais perceptuellement non saillantes. J’identifie trois modes de « perception morale imaginative » : 1) la prise de perspective qui consiste à endosser le point de vue d’autrui, 2) le cadrage imaginatif qui désigne le fait de voir un élément d’une situation comme autre qu’il n’est et, 3) la comparaison imaginative qui, grâce à la pensée contrefactuelle, éclaire le monde actuel à partir d’un monde possible imaginé. Chacun de ces modes contribue à enrichir notre connaissance morale, et partant, à améliorer notre délibération morale. J’appuie ma démonstration sur des travaux récents en philosophie de la psychologie, en psychologie cognitive et sociale, en neuropsychologie et, bien évidemment, en psychologie morale.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.020 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.011 | 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".