Des fous rires autour du Führer chez Timur Vermes et François Saintonge
Bibliographic record
Abstract
La représentation comique d’Adolf Hitler n’est pas un phénomène nouveau puisque des exemples de ridiculisation du Führer s’observent dès le début des années 1940, notamment dans des films de propagande antinazie comme The Great Dictator de Charlie Chaplin. Ce qu’il y a de plus troublant, trois quarts de siècle après la fin de la Seconde Guerre mondiale, c’est le traitement frivole et décontextualisé que suscite le tyran nazi. Pour en rendre compte, nous avons choisi d’analyser deux romans récents – Il est de retour de Timur Vermes et Dolfi et Marylin de François Saintonge – parce qu’ils permettent de réfléchir aux principaux enjeux qui émanent de cette forme particulière d’humour noir. Rire d’Hitler, ou autour de lui, ne fait pas que nous amener aux limites de l’acceptabilité sociale en matière comique; cela vient également tester notre lucidité devant les dangers que l’Histoire se répète.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.032 | 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; both teacher heads agree on what is shown here.
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".