Réflexions à l'usage des traducteurs d'œuvres autochtones écrites en anglais : pour une décolonisation de la traduction, suivies de "Le club des Premières Épouses : à la façon salishe de la côte" de Lee Maracle
Bibliographic record
Abstract
Since the majority of Indigenous writers in North America write in English and since the majority of their translators are non-Indigenous, I started thinking about an ethical and decolonized translation, towards French, of Indigenous literary works written in English. The premise of this thesis is that a story written in English by an Indigenous author cannot be translated the same way a story written by a Canadian or American author is. This is explained by the fact that Indigenous literary works are often political, that their authors come from cultures and worldviews that are very different from the ones of western authors and that there is a power relationship between Indigenous and non-Indigenous Peoples. My reflection is based on the critical and theoretical work of certain western intellectuals, such as the translation scholar Antoine Berman, but mainly on the work of Indigenous writers, intellectuals, and scholars such as Craig S. Womack (Creek/Cherokee) and Kristina Fagan (Labrador Metis). In the first chapter of my thesis, I take an interest in the translation of literary works by Indigenous authors in Canada, in the two official languages. Since 2010, more and more Indigenous works have been translated, mostly from English to French. I study the political aspect of Indigenous stories and explain the aim of several Indigenous stories, which are healing, compassion, and reappropriation. I also draw attention to certain pitfalls that are often found in the translation of Indigenous literatures: ethnocentrism, rationalization, clarification, the “destruction of the vernacular networks”, and exoticisation which are, in the opinion of Berman, frequent “distorting tendencies” in translation. To these pitfalls, I add the desire to respond to the readers’ horizon of expectation, the lack of knowledge of Indigenous cultures, the desire to reveal everything, and the difficulty of translating Indigenous humour. I explore the relationship of Indigenous writers with the language of the colonizers before looking into Rez Englishes, these dialects that are found in some Indigenous works. In the second chapter, I highlight practical translation problems in two books of the Salish-Stó:lō author Lee Maracle as well as a few particularities of her writing. Finally, in the last chapter, I apply the result of my reflections to a translation of Maracle’s short story collection, First Wives Club: Coast Salish Style (2010), that is resolutely attached to the letter of the text
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.017 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".