Self-Translation in Transcultural Mode: Francesca Duranti on how to Put ‘a Scent of Basil’ into One’s Translations
Bibliographic record
Abstract
“Who but he... had ever felt what these words expressed?–these words that thundered and howled through his mind translating himself to himself, with such appalling fitness” (Amélie Louise Rives) Francesca Duranti is a creative writer who grew up with several languages and spent much time abroad. Her mother tongue is German but she writes mainly in Italian and translates mostly from French and English. Her particular transcultural sensibility runs through her body of work but is mostly manifest in her novel Sogni mancini (1996), the story of an Italian academic woman living in New York obsessed with the idea of finding a way to get rid of fixed identities and monological perspectives. Subsequently, Duranti decided to self-translate this novel into English, publishing it with the title Left-handed Dreams (2000). What were her reasons for self- translating this book, what self-translation strategies did she adopt, what did she gain and what did she lose in the process of mediating between two cultures and how did readers receive her target text? In this in-depth interview with Arianna Dagnino, Duranti reveals to what extent her acquired transcultural identity affected not only her way of writing but also of self-translating. As a coda to the interview and in light of what emerges from the writer’s answers, Dagnino analyzes Duranti’s self-translation, looking for those elements that mostly reveal the transcultural identity of a writer who decided to translate herself to herself. The article includes introductory paragraphs on the theory of the transcultural and transcultural identities (Dagnino 2015, Epstein 2009, Welsch 2009) as well as on the most recent studies in the field of literary self-translation (Grosjean 2010, Grutman 2016, Saidero 2011).
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.008 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".