On C-E Translation of Campus Public Signs: from the Perspective of Functionalist Translation Theory
Bibliographic record
Abstract
A public sign is a vocative text. The most important criterion for the translation of public sign is the realization of functionality. At present, there are many poorly-translated public signs on university campus, the reason for which lies in the over-emphasis on form as well as the neglect of the communicative purpose and effect. The C-E translation of public signs should realize the communicative function, and convey the illocutionary and perlocutionary meaning of the source-language text. Key words: functionalist translation theory, public sign, function, purpose Resume: Le terme d’affiche est un texte dote de la fonction d’appel. Le critere cle de la traduction du terme d’affiche est que le texte de traduction resalise la fonction prevue. Actuellement, il existe un grand probleme de qualite dans la traduction du terme d’affiche dans des universites, et la raison principale reside dans ce que le traducteur, recherchant partiellement la correspondance de forme du texte, neglige le but et l’effet de communication. La traduction des affiches doivent representer la fonctoin communicative du texte original et fait grand cas de la signification profonde et de sa communication. Mots-cles: theorie de la traduction fonctionnelle, terme d’affiche, fonction, but 摘要：公示語是具有呼喚功能的文本。公示語翻譯的最重要標準是使譯文實現預期功能。目前一些高校的公示語翻譯存在嚴重的品質問題，主要原因在於譯者片面追求文本的形式對應而忽視了交流的目的與效果。公示語翻譯應體現源語文本的交際功能，注重原文本的言外之意和言外效果的傳達。 關鍵詞：功能翻譯理論；公示語；功能；目的
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.004 | 0.027 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".