Bibliographic record
Abstract
This paper seeks to address and analyze forms of resistance to self-translation, mainly as exhibited by two contemporary writers who have chosen to publish in Italian. Italian is the Algerian-born Berber Amara Lakhous’ fourth language and the London-born Bengali Jhumpa Lahiri’s third language. Beyond the fact that both have a connection to Rome and that both are (im)migrant writers (albeit not in the same literary field, Lahari being an American writer who lived in Rome and Lakhous an Italian citizen living in New York), they display quite divergent attitudes toward language, translation and self-translation. These attitudes are discursive “stances” or “position-takings” (Bourdieu: prises de position) that should not be taken at face-value but deconstructed on their own terms. Questo lavoro ha lo scopo di indagare forme di resistenza all’autotraduzione esibite da due scrittori contemporanei che hanno deciso di pubblicare in italiano. L’italiano è la quarta lingua per l’autore berbero di origine algerina Amara Lakhous, e la terza lingua per l’autrice londinese di origine bengalese Jhumpa Lahiri. Oltre al fatto di avere entrambi un legame con la citta di Roma, e di essere entrambi scrittori migranti (benché non nello stesso ambito letterario, dato che Lahiri è una scrittrice americana vissuta a Roma, mentre Lakhous è un cittadino italiano che vive a New York) i due autori mostano atteggiamenti piuttosto divergenti nei confronti della lingua, della traduzione e dell’autotraduzione. Questi atteggiamenti si producono in “posizioni” o meglio “prese di posizione” (Bourdieu: prises de position) che non vanno prese alla lettera ma decostruite nei loro stessi termini.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.016 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".