Le libéralisme de la prudence : contribution à un minimalisme politique
Bibliographic record
Abstract
Il s’agit ici de présenter une version raffinée du libéralisme de la peur de Judith Shklar : le libéralisme de la prudence. Après en avoir brièvement présenté les grandes lignes et les principales faiblesses, j’esquisse les contours du libéralisme de la prudence et montre comment il réalise, mieux que libéralisme de la peur, le programme minimaliste poursuivi par Shklar. Je montre ensuite comment le libéralisme de la prudence nous permet de sortir du dilemme libéral posé par la tradition postrawlsienne : justifier le libéralisme sur des bases morales, au risque de le priver de neutralité, ou le justifier sur des bases réalistes hobbesiennes, au risque d’en faire l’otage des rapports de force changeants. Enfin, j’examine comme le principal défaut apparent du libéralisme de la prudence – à savoir son ascétisme programmatique – est en fait son principal mérite.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.026 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 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".