The Oral Translator’s “Visibility”: The Chinese Translation of David Copperfield by Lin Shu and Wei Yi
Bibliographic record
Abstract
An important feature in the translation history of China in the early 20th century was the collaboration between a Chinese monolingual and a Chinese bilingual in a large-scale translation of Western fiction. Such a collaboration pattern lasted for almost two decades before more Chinese bilinguals were trained in the 1920s. The partnership of Lin Shu (1852-1924) (a prominent written translator) and Wei Yi (1880-1933) (one of Lin Shu’s oral translators) lasted for 10 years, during which they translated over 40 English novels into Chinese. Through textual analyses of their co-translation of Charles Dickens’s David Copperfield in 1908, this article unravels the long-neglected contribution of Wei Yi in the work, and points to the importance of “orality” in their translation process in shaping Lin Shu’s translations. The article is structured into two parts: first, the background of Lin Shu and Wei Yi, and their collaboration; second, evidence of Wei Yi’s visibility in the translation in terms of textual changes from indirect speech to direct speech, the use of annotations, and the characteristics of the translation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.013 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".