Bibliographic record
Abstract
À travers le prisme du concept d’hétérolinguisme littéraire, caractéristique d’écrivains vivant entre plusieurs langues, l’article propose une étude des divers degrés de présence des langues étrangères dans les romans et nouvelles publiés d’Irène Némirovsky. Alors qu’une grande partie de son œuvre met en scène des personnages étrangers (juifs et russes en particulier), les langues étrangères subissent généralement une ellipse, absorbées par le français de la narration, mais elles peuvent affleurer par des commentaires ou l’onomastique des personnages. On relève également des emprunts lexicaux et phraséologiques savamment dosés, attribuables soit au narrateur, qui se présente alors comme un passeur de cultures, soit aux personnages. L’anglais en revanche est la langue étrangère la plus largement citée et n’est pas nécessairement l’indice d’une altérité, comme le russe ou le yiddish, mais le signe d’une distinction sociale.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".