A Study of Translation Strategy in Eileen Chang’s The Golden Cangue From the Perspective of Feminist Translation Theory
Bibliographic record
Abstract
Eileen Chang is an outstanding female writer in Chinese literature history because of her unique writing style. What’s more, she was not only a successful writer but also a translator which was seldom known or studied by others. She self-translated a great number of works including The Golden Cangue and The Rouge of North. Feminist translation theory came into being with the development of feminist movement. As a combination of feminism and translation, it developed under the background of “cultural turn” aiming at enabling the society to hear the voice of women through creating and rewriting strategies by the feminist translators. The feminist translators are devoted to translating the works under the value of feminism. This paper intends to study the translation strategy through comparing the original book and the translation script based on the prefacing and footnoting, supplementing and hijacking strategies proposed by the Canadian translation researcher Louise Von Flotow.
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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 | 0.019 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.014 | 0.024 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| 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".