A Study of Translation Methods Adopted in the Yangs’ Version of “Master Gao” from the Perspective of Manipulation Theory
Bibliographic record
Abstract
Soon after the founding of the People’s Republic of China in 1949, foreign translation of Chinese culture was put on the agenda. Lu Xun’s short stories were selected as representative works and translated into English by Yang Xianyi and Gladys Yang (hereinafter referred to as “the Yangs”) in the 1950s and 1960s under the special international and domestic environment, and they have played an important role in spreading Chinese culture to the world. Based on André Lefevere’s Manipulation Theory, especially its three elements, namely, poetics, ideology and patronage, this paper examines the translation methods adopted by the Yangs in their translation of Lu Xun’s short story “Master Gao”. Through example analysis, the article concludes that the Yangs mainly adopted literal translation under the influence of poetics, ideology and patronage in the then special social background. It is hoped that the research aims to provide a theoretical and practical reference for future translation and dissemination of Chinese literary works to the world.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.021 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.005 | 0.011 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".