Comment définir une éthique pour notre civilisation technologique ?
Bibliographic record
Abstract
Y a-t-il une fondation rationnelle ultime à nos obligations morales qui puisse nous permettre de faire face aux exigences de notre situation technologique actuelle et des inquiétudes qu’elle fait surgir ? Ce texte a pour objectif de répondre affirmativement à cette question en examinant les travaux de deux auteurs qui partagent une lecture de l’aspect paradoxal de la réflexion éthique contemporaine, à savoir Karl-Otto Apel et Hans Jonas. Chacun de leur côté, ils se proposent de fonder rationnellement une éthique capable d’affronter l’ampleur des problèmes auxquels fait face la civilisation technologique, mais ils le font par des chemins passablement différents. Ma thèse est que ces deux voies sont nécessaires pour arriver à l’objectif d’une fondation rationnelle ultime de l’éthique, mais qu’elles ne peuvent y arriver qu’à la condition de travailler en complémentarité.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.037 |
| Scholarly communication | 0.013 | 0.023 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
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".