Bibliographic record
Abstract
Closeness in style has always been the highest standard or the supreme goal of translation. A successful translation of Lun Yu is inseparable from the preservation of its original style. This paper examines whether James Legge’s translation of Lun Yu reproduced the original style from the linguistic point of view and the literary point of view respectively. A careful comparative study on the source text and the target text reveals that the stylistic features of Lun Yu have been preserved in Legge’s version in a considerable degree. This pioneer, and at the same time standard translation by Legge has provided us with so many good and useful translation techniques as well as enlightenment that it will continue to benefit the development of translation theory and practice. Key words: Lun Yu; translation; styleResume: La proximite de style a toujours ete le standard le plus eleve ou le but supreme de la traduction. Une traduction reussie de Lun Yu est indissociable de la preservation de son style original. Cet article examine si la traduction de Lun Yu de James Legge a reproduit le style original du point de vue linguistique et litteraire respectivement. Une etude comparative soigneuse sur le texte source et le texte cible revele que les caracteristiques stylistiques de Lun Yu ont ete conservees dans la version de Legge a un degre considerable. La traduction standard de Legge nous a fourni tant de techniques de traduction de qualite et utiles ainsi que de l’eclaircissement qu'il continuera de beneficier au developpement de la theorie de la traduction et de la pratique.Mots-Cles: Lun Yu; traduction; style
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".