From "Sisters" to "Comadres": Translating and Transculturating Tomson Highway's The Rez Sisters
Bibliographic record
Abstract
Since theNative Canadian playwright Tomson Highway imagines his plays in Cree beforetranslating them into English, his dramatic texts are, in the words of Gayatri Spivak, “a history of the languagein-and-as-translation. “ As he acknowledges, Highway’s English is permeatedwith the rhythm of the Cree language: “I am actually using English filteredthrough the mind, the tongue and the body of a person who is speaking inCree” Highway’s text introduces Cree orOjibway words and phrases, providing English translations for them infootnotes. The other characteristic which makes Highway’s plays distinct istheir sexual content, as transmitted both in the spoken text and in the stagedirections. Highway explains in an article titled “Why Cree is the Sexiest ofAll Languages,” that talking about sex in English is a terrifying experience, whereasin Cree it is the funniest, most hysterical and most spectacular thing in theworld.” In addition, visceral and sexual language is an essential component ofthe play, This paper will explore the process of translation andtransculturation involved in the translation of Highway’s play The Rez Sisters, in the light of translationstudies theories and the notion of transculturation as coined by Fernándo Ortizand expanded by Norman Cheadle in his book CanadianCultural Exchanges.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.018 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.011 | 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".