Bibliographic record
Abstract
Cet article essaie de réfuter la thèse de Luc Ferry selon laquelle la formule de Hannah Arendt « la banalité du mal » signifie qu’elle attribue la responsabilité des crimes de Eichmann non pas à Eichmann lui-même, mais au contexte historique dans lequel ce dernier évoluait, c’est-à-dire l’Allemagne nazie. L’auteur démontre que, pour Arendt, Eichmann peut certes évoquer le contexte historique dans lequel il travaillait pour atténuer la portée de ses crimes, mais qu’il est néanmoins responsable de ses actes. Il souligne que la formule d’Arendt ne s’adresse pas tant à Eichmann lui-même, mais qu’elle constitue une critique implacable de la gestion des administrations publiques. Le cas Eichmann illustre les dangers d’une gestion hiérarchique et autoritaire des « ressources humaines » dans les États occidentaux. Rejetant ces rapports autoritaires, l’auteur en appelle au développement de l’éthique organisationnelle.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.006 | 0.008 |
| 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".