A Study on Semantic and Communicative Translation of Magical Things in Harry Potter
Bibliographic record
Abstract
Developing prosperously in the contemporary, fiercely competitive literary world, fantasy literature, with its mysteries, has attracted the attention of and been admired by readers from every corner of the world. Nevertheless, being worldwide popular regardless of countries and languages, its great success should be attributed to translators who introduced the spectacular works to the target language readers. As the fantasy literature is deeply rooted in Western Culture, in order to conform to the original texts’ meaning and meet with the target language culture as well as be easily understood by readers, the paper chooses Peter Newmark’s semantic translation and communicative translation theories as the guiding principles to analyze the translation of fantasy literature which takes both the Western and Chinese culture into consideration, keeps its mysterious magical mood and realizes the effects of clarity and straightaway. Semantic translation aims at replicating the original texts’ forms within the target language, reproducing the original context, and retaining the characters of the SL culture in the translation. In contrast, communicative translation centers on the specific language and culture and focuses on the TL readers. The translation under this method is clear, smooth and concise. This paper takes the simplified Chinese version of Harry Potter as an example to illustrate the strategies used in the translation of magical things. It finds that there are generally three ways used in the translation of Harry Potter : semantic translation, communicative translation and the combination of the two.
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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 | 0.000 |
| 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".