Bibliographic record
Abstract
Depuis son essai consacré à Victor Hugo en 1970, Victor-Lévy Beaulieu a multiplié les biographies d’écrivains. Ces essais entremêlant souvent l’écriture biographique et l’écriture de fiction, il devient possible de questionner la place qu’ils occupent dans l’oeuvre de Beaulieu et le rôle qu’ils jouent dans l’élaboration de ses textes de fiction. Dans cet article, l’auteur analyse les rapports entre l’écriture biographique et l’écriture de fiction chez Beaulieu, principalement dans Monsieur Melville. Dans un premier temps, il dégage la dialectique de la biographie et de la fiction chez Beaulieu, notamment à la lumière de l’inscription de la figure du golem dans Monsieur Melville. Dans un deuxième temps, à partir des thèmes de la filiation et de l’héritage, l’auteur mesure l’impact de Monsieur Melville sur l’élaboration de l’oeuvre littéraire de Beaulieu dans les années quatre-vingt et quatre-vingt-dix.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.008 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".