A Study on Defamiliarization in the Translation of The Last Quarter of the Moon
Bibliographic record
Abstract
The Last Quarter of the Moon is a novel written by Chi Zijian, which describes the life of the Ewenki ethnic minority in northeast China.The novel has received wide attention for its profound theme and unique narrative style.Defamiliarization is a technique commonly used in literary creation.By breaking the conventional expression mode and changing the conventional view, readers can have new feelings and understandings.The original text of The Last Quarter of the Moon describes the life of the Ewenki minority in China, which has a strong defamiliarization effect.In the English version, the translator adopts various methods to reproduce this defamiliarization.Through the analysis of its English translation, this paper discusses the defamiliarization embodied in it and the two translation methods used by the translator to reproduce the defamiliarization of the original text: alienizing translation and hybridization.It is found that the translation successfully retains the unique charm of the original text by means of language and cultural defamiliarization, enabling English readers to obtain a new reading experience, and revealing the important reasons why the English translation of The Last Quarter of the Moon can be successfully translated and spread in the Western world.
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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 | 0.006 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.010 | 0.012 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".