Bibliographic record
Abstract
RÉSUMÉ \n \n« Écrire » une traduction \n \nMona Sacui Catrinescu \n \n \nLorsqu’il traduit, l’auteur-traducteur est, selon Richard Vautour, atteint de « l’angoisse de l’écriture », affliction touchant tout écrivain. Son œuvre personnelle est relancée par le texte à traduire, ce qui crée une tension lors de la traduction. À partir de cela, on pourrait présumer que l’auteur-traducteur diffère considérablement du traducteur littéraire conventionnel à cause de son identité d’écrivain. \n\tPourtant — et c’est ce que la partie critique de ce mémoire vise à démontrer —, l’auteur-traducteur se distingue en fait peu du traducteur littéraire conventionnel. C’est en explorant la relation entre écriture et traduction, ainsi que les caractéristiques du traducteur qui écrit, que nous verrons à quel point ces deux types de traducteurs sont similaires. De plus, grâce à notre propre expérience de traduction de deux nouvelles du recueil The Beggar’s Garden du jeune Canadien Michael Christie, nous verrons si notre propre identité d’auteure-traductrice a eu une incidence sur le processus et le résultat de la traduction. La première partie de ce mémoire est donc consacrée à l’analyse de la traduction en tant qu’écriture, suivie par une enquête sur les similarités entre l’auteur-traducteur du traducteur littéraire conventionnel. Nous nous penchons également sur notre propre expérience de traduction de « The Extra » et « Goodbye Porkpie Hat » afin de déterminer quels ont été les effets concrets de notre double identité sur le texte d’arrivée. La deuxième partie du mémoire consiste quant à elle en la traduction des deux nouvelles. \n \n-- \n \nABSTRACT \n \n« Écrire » une traduction \n \nMona Sacui Catrinescu \n \nWhen at work, the writer-translator suffers from what Richard Vautour calls the “anguish of writing” (l’angoisse de l’écriture), an affliction known to all writers. Indeed, the piece that must be translated stimulates the writer-translator and awakens his or her own oeuvre, thus creating tension during the translation. Taking this into account, one could easily presume that, because of his or her identity as a writer, the writer-translator is very different from the average literary translator. \n\tThis thesis aims, however, to show that the writer-translator is in actual fact not all that different from the average literary translator. By exploring the relationship between writing and translating, as well as the characteristics of the translator who writes, we have discovered just how similar these two types of translators are. The personal experience of translating two shorts stories from The Beggar’s Garden by young Canadian author Michael Christie has also served as a means to determine if being a writer-translator has had any effect on the process and result of the translation. The first part of this thesis consists of an analysis of translation as writing, and is followed by an investigation on the similarities between the writer-translator and the literary translator. We also look at my translation of “The Extra” and “Goodbye Porkpie Hat” in order to see what effects (if any) my double identity has had on the target texts. The translations themselves are featured in the second part of the thesis.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.008 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.038 | 0.008 |
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".