Contemporary ethnographic translation of traditional Aboriginal narrative : textualizations of the Northern Tutchone story of crow
Bibliographic record
Abstract
This thesis is designed as an encounter between translation studies and ethnography. It demonstrates how a cross-fertilization between those two disciplines can be achieved for the benefit of both. If several of the research methods employed to gather the data analysed are those currently used by translation studies specialists investigating all manner of translation, others, such as field research, are typical of ethnography. And while some of the theoretical framework upon which the thesis builds its argumentation is essentially that of translation studies, translation theories formulated by practitioners of anthropology have not been ignored. The thesis takes the form of a case study. Its object of inquiry is an ethnographer's recording of the telling of an age-old narrative by an Aboriginal elder in his own Northern Tutchone language, and the subsequent translation, textualization and publication of this narrative into English and into French. It establishes why and how this elder and this ethnographer agreed to collaborate to transform this traditional narrative into two learned publications. The central question that the thesis asks is this: How did a combination of linguistic, social, cultural, historical, institutional and political constraints operate on each state of the text of this traditional Tutchone story cycle to make it such as we find it in the published books? Manifestations of those limiting factors are identified and their effects are assessed in each state of the text as well as in the paratext of the forewords and afterwords of the English and French publications. Such restrictions are moreover shown not to be confined to this particular case since analogous forces are demonstrated to have similarly informed other recent Yukon ethnographic encounters
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.010 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".