Bibliographic record
Abstract
This article aims to demonstrate how minority language speakers have udes translation of literacy works as a means to preserve their national identity and to ensure the survival of their language. Five studies related to the subject are herein considered. Judith Woodsworth (1996) analyses the translation into contemporary Scots of Les Belles-soeurs, by Québec playwright Michel Tremblay, and the translation into Romansch of The House at Pooh Corner, by A. A.Milne, a British author of books for children. Michael Cronin (1995) investigates issues concerning an anthology of poems performedby contemporary Irish poets. Harish Trivedi (1997) discusses the translation of Anatole France's Thaïs to Hindi. Nayak & Mohapatra (1997) examine the adaptation of Charles Dickens' A Tale of Two Cities to Oriya. In all these works, translation was not simply a means of communication. It was rather a political act, an attenpt to strengthen the minority language and culture.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.006 | 0.008 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.005 |
| Insufficient payload (model declined to judge) | 0.019 | 0.004 |
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".