Bibliographic record
Abstract
RÉSUMÉ Le présent article se propose de montrer à quel point le jugement que Jean-Jacques Rousseau porte sur l’humour et sur le rire peut nous aider à éclairer sa réflexion philoso‐ phique, notamment la genèse de l’émotion et le rôle que celle-ci peut jouer dans la conduite morale de l’individu. L’analyse généalogique de la passion du rire dans l’œuvre de Rousseau—qui s’inscrit de manière cohérente dans sa conception «vectorielle» de l’émotion—nous signale la nécessité de séparer nettement la réalisation positive de la bonne humeur, c’est à dire la gaieté, de sa dégénérescence négative, à savoir la moquerie. Dans le premier cas, il s’agit d’une émotion positive et légitime qui reprend le caractère naturel d’une passion pré-morale en l’élevant à outil d’édification de la socialité humaine; dans le second, il s’agit, au contraire, d’un sentiment artificiel et conventionnel qui fausse l’émotion et la transforme en un instrument de domination sur le prochain.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.015 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".