Bibliographic record
Abstract
Alexandre Vialatte (1901-1971) a traduit presque toute l’oeuvre de Kafka en français tout en élaborant sa propre oeuvre littéraire. Celle-ci est pourtant loin de se situer dans la dépendance de celle de Kafka. Vialatte a en effet été non seulement le traducteur de Kafka mais aussi un critique avisé proposant plusieurs lectures successives qui sont à l’origine des grandes options de la critique actuelle. Les analogies entre les récits de Kafka et les romans de Vialatte restent souvent très vagues : inquiétante étrangeté, folie du classement, culpabilité sans faute, tandis que les emprunts intertextuels directs sont minces. On peut néanmoins suivre le fil qui conduit de Kafka à Vialatte dans La dame du Job et Le fidèle berger, romans du secret et de la consigne, dans La maison du joueurde flûte, parabole d’inspiration kafkaïenne, et dans Les fruits du Congo, le grand roman de 1951. On perçoit ainsi plus précisément ce que Vialatte appelle « l’idée fausse qui m’est nécessaire » en parlant de sa lecture personnelle de Kafka mise au service de sa propre création romanesque.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.018 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".