A Comparative Study on the Abstractness Presented in Chun Xiao and its Four Translated Versions
Bibliographic record
Abstract
This paper sets out to discuss the abstractness created by Meng Haoran in Chun Xiao and its reproduction in four translated versions by four different translators. Through the analysis in three functions of abstractness, namely, to reach accuracy, create ideorealms and to induce association, it is found that the four versions tend to two ways of translation: one is to reproduce abstractness; the other is to make abstractness concrete. The two ways are both adequate in its adaptation to different readers. Key words: abstractness, Chun Xiao, accuracy, ideorealms, association Resume: L’article present analyse l’expression de la beaute suggestive dans le poeme L’Aube du printemps et sa representation dans ses quatre traductions. L’article examine les traductions dans les perpectives des trois fonctions de la beaute suggestive : precision de l’expression, creation de l’ambiance et suggestion. Il en resulte qu’il y a deux tendance de traduction quant a la beaute suggestive, a savoir la traduction equivalente et la traduction diminutive. Chacune de ces deux techniques de traitement a ses qualites face aux differents lecteurs, ainsi ne peut-on pas juger aveuglement les merites et les defauts des traductions. Mots-cles: beaute suggestive, L’Aube du printemps, precision, ambiance, suggestion 摘要：本文討論和分析了朦朧美在唐詩《春曉》中的表現及其四個不同譯文中的再現。通過朦朧美的作用在三個方面的表現，即表達精確、營造意境和引發聯想對譯文進行考察，得出兩種翻譯趨向，即對原文朦朧美的等化處理和淺化處理。這兩種不同的處理方法，針對不同的讀者群，各有千秋，因此不能盲目片面比較譯文的優劣。 關鍵詞：朦朧美；《春曉》；精確；意境；聯想
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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".