A Systematic Literature Review of Chinese-English Euphemism Translation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
To comprehend current research status of Chinese-English (henceforth C-E) euphemism translation, this research conducted a systematic literature review on 147 publications from 1997 to 2025 based on prisma, from aspects of research trend, subjects, applied theories, problems identified, and translation strategies and principles. It shows euphemism translation from Chinese to English has started in 1997, then developed to its climax in 2012 and began to decline until now. Besides, there is a transition in theories application from Skopos and functional equivalence to cultural theory. Furthermore, homogeneity is found in translation problems, strategies, and principles. All of these limitations suggest more diversified perspectives in C-E euphemism translation. Therefore, cross-disciplinary perspectives are welcomed in relevant studies, such as culture, ideology, readers’ cognitive and psychology, and readers’ reception. This research makes a summary of current research status quo, finding some limitations in this regard such as lacking of cross-disciplinary perspectives and homogeneity in translation problems and strategies, which will enrich relevant research diversity and offer more guidance to address relevant problems and fill up the research gaps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it