Comparative Studies on English Translation of the Four Main Characters’ Titles in “Xiyouji”
Bibliographic record
Abstract
The study aims to compare Anthony C. Yu’s and W. J. F. Jenner’s translations of the four main characters’ titles in “Xiyouji.” By categorizing the main characters’ titles using a statistical methodology and determining what the characters’ personalities are embodied in the main titles, the study analyzes which translation is more appropriate from the perspective of cultural communication. The most frequently used titles for “孙悟空(Sun Wukong)” are “(孙)行者(Pilgrim/Moneky)” and “(齐天)大圣(Great Sage),” accounting for 48% and 14% of his 119 titles. For “唐玄奘(Tang Xuanzang),” the predominant titles are “师父(Mater)” and “三藏(Sanzang/Tripitaka),” making up 40% and 25% of his 17 titles. “猪悟能(Zhu Wuneng)” is most commonly called “(猪)八戒(Eight Rules/Pig)” and “呆子(Idiot),” constituting 73% and 18 % of his 11 titles. As for “沙悟净(Sha Wujing),” the prevalent titles are “沙和尚(Sha Monk)” and “悟净 (Wujing),” encompassing 90% and 7% of his seven titles. Whether Sun Wukong’s justice, braveness and supernatural ability and his role as the crisis solver of the pilgrimage, Tang Sanzang’s wisdom, leadership and enlightenment and role as the leader, Zhu Wuneng’s transgressive nature and role as the rule breaker or Sha Wujing’s devoutness and role as the follower, their titles reflect their personalities and positions in the narrative. By comparing Yu’s and Jenner’s translations of these titles, the paper observes that Yu’s translation conveys the implied meanings. In contrast, Jenner’s translation is straightforward and simplified. Yu’s translation is more beneficial for the target language readers to understand Chinese Culture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".