Inside Out or Outside In? Translating Margins, Marginalizing Translations. The Case of Francophone Pacific Writing
Bibliographic record
Abstract
The concepts of centre and margins are of course, or ought to be, interchangeable: where we are is, in that sense, always the centre. However, no one would deny that in terms of culture, some 'centres' are more dominant than others. As a translator of Pacific texts, both from French into English and from English into French (as a co-translator), I have become acutely aware of what is at stake in the 'centre' of the Pacific, in particular on the islands of New Caledonia and French Polynesia. Focusing on texts from French Polynesia, I look at some of the ways in which indigenous Pacific authors writing in French 'deterritorialise' both genre and language conventions to create new forms of expression. Chantal Spitz, for example, employs a highly poetic style, even including traditional poetic forms in her prose. How can the translator respond to these strategies in such a way as to promote a reading 'from the inside out'?
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.041 |
| Scholarly communication | 0.012 | 0.009 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".