Bibliographic record
Abstract
A Psalm of Life, the representative work of the famous American poet Henry Wadsworth Longfellow, is taken as the first English poem translated into Chinese. It was in the year 1865 that Thomas Francis Wade first translated it into Chinese and after that various versions with distinctive features have been turning up. This thesis endeavors to analyze three typical versions from three aspects, namely, the “form beauty”, the “sound beauty” and the “sense beauty”, according to the “three-beauty” principle of poem translation proposed by Professor Xu Yuanchong. The basic principles and methods of poem translation are concluded on the basis of the comparative analysis and the “Dynamic Equivalence” theory proposed by Eugene A. Nida. Key Words: poem translation, spiritual resemblance, formal resemblance, “three-beauty” principle, dynamic equivalence Resume: Le Psaume de la vie, oeuvre reputee du poete americain Henry Wadsworth Longfellow, est considere comme le premier poeme anglais traduit en chinois. Depuis que Thomas Francis Wade l’a traduit la premiere fois en chinois en 1865, de nouvelles versions ne cessent d’apparaitre dont chacune a son originalite. L’article present, en vertu du principe de « trois beautes » dans la traduction du poeme preconise par le professeur Xu Yuanchong, entreprent une analyse comparative de ses trois versions les plus representatives sur les plans de « beaute de forme », « beaute de son» et « beaute de signification ».A partir du resultlat d’analyse, se referant a la theorie de l’ « equivalence dynamique » du theoricien de traduction tres connu Eugene A. Nida, l’auteur propose les principes fondamentaux de la traduction de la poesie. Mots-Cles: traduction de la poesie, similitude d’esprit, similitude de forme
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".