Bibliographic record
Abstract
Literary translators are often too shy to discuss their own practice. As the penury of translators’ prefaces would attest, they have assimilated the fidelity imperative only too well and, even though they may be masters at transforming the literal into the literary, they prefer to remain invisible behind their author as if only the latter were real and they merely fiction(al) workers. Such doesn’t appear to be the case for two translators of Tres Tristes Tigres by the Cuban writer Guillermo Cabrera Infante: the first, Albert Bensoussan, working in French and the author of Confessions d’un traître (PU de Rennes, 1995); the second, Suzanne Jill Levine, working in English and the author of The Subversive Scribe (Graywolf Press, 1991). While it is undeniable that their respective collaboration with authors of the calibre of Cabrera Infante must have played a large part in their desire to write of what must have been an unforgettable experience, this paper will focus on different questions in order to gain insight into the theorization by translators of their own practice: Why and how do both Bensoussan and Levine produce prize-winning translations of famously difficult and considered “untranslatable” works? Why, in spite of their success and ability to push translational creativity to its limits, are they ultimately incapable of dispelling a sense of betrayal? Rather than providing definitive answers, exploring these questions leads to reflect on possibly constant factors in literary translation and on teaching or evaluating translations as well as training translators.
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 | 0.003 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.006 | 0.012 |
| Insufficient payload (model declined to judge) | 0.044 | 0.027 |
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".