Traduire un roman de l’extrême contemporain: tesi magistrale e opportunità editoriali
Bibliographic record
Abstract
Seynabou Sonko – scrittrice, cantante e compositrice franco-senegalese, classe 1993 – è una delle voci letterarie più interessanti nel panorama francofono contemporaneo. Ha studiato scrittura creativa presso le università di Montreal, di Bruxelles e di Paris Vincennes-Saint-Denis. Il suo primo romanzo, Djinns (Paris, Grasset, 2023), è stato acclamato con entusiasmo dalla critica come un’opera «tragicomica sulle gioie e i dolori del multiculturalismo» (Gl. Marivat, Le Monde des Livres 28/07/2023). Piero Della Vedova traduce per la prima volta in italiano l'opera prima di Sonko, non solo con la verve di un traduttore appassionato, ma soprattutto con lo sguardo attento del cercatore di parole, conducendo un’analisi minuziosa del lessico e di quel che lui definisce 'lingua generazionale'. Si tratta del primo contributo in lingua italiana dedicato a Sonko, nell’attesa che la prima traduzione completa sia pubblicata.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 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".