Bibliographic record
Abstract
La notion d’éthicisation est le plus fréquemment utilisée pour désigner un processus suivant lequel une préoccupation éthique est intégrée à une réflexion ou à un corps doctrinal d’une autre nature. L’auteur se propose ici d’examiner l’idée d’une déséthicisation de la liberté d’expression et ses conséquences sur l’analyse du débat public. Il préciserai d’abord ce qu’est sa déséthicisation et quelle conception de la liberté d’expression en découle. Il analysera ensuite quelques implications de la déséthicisation de la liberté d’expression sur l’analyse de débats publics qui la mettent en jeu ou dont elle fait elle-même l’objet. Finalement, il examinera en quoi la déséthicisation de la liberté d’expression affecte le projet de son encadrement éthique et la qualification qu’il convient de donner des jugements moraux qui la mettent en jeu.
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 | 0.027 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.072 |
| Scholarly communication | 0.014 | 0.013 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.007 | 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".