An Analysis of Textless Back Translation of Fifth Chinese Daughter
Bibliographic record
Abstract
Based on acculturation theory as well as both English and Chinese texts of Fifth Chinese Daughter , this paper aims to study the textless back translation in terms of the four most typical acculturation strategies—assimilation, integration, separation and marginalization. This paper holds that assimilation and integration strategies are the mainstream regarding the textless back translation of Fifth Chinese Daughter . In translating China-themed works, the employment of assimilation strategy—a significant indicator of works for textless back translation—prevails and can be further divided into “accurate assimilation” and “imprecise assimilation” according to the degree of restoration. With regard to the translation of English-specific expressions or expressions that are unique to the English culture, the integration strategy marked by annotations and the separation strategy marked by foreignization are respectively adopted to some extent. The employment of marginalization strategy may result from either the translator’s misunderstandings or the culture gap between two cultures and should be avoided as much as possible.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".