The Functions of Literature Works Translation Versions Under Cross-Cultural Background: Taking Uncle Tom’s Cabin as an Example
Bibliographic record
Abstract
As one of cross-cultural communication actions, translation is a kind of human society cross-cultural communication and exchanging process at the same time. Since the generation of culture, the communication activities have never ended, and it has always promoted the continuous growing of culture. The exchanging of different language and the communication of their background culture can only be realized under the assistance of translation activities, and translation is the required conditions for cultural cohesion and shock, as well as communication and developing of different languages. When overlooking the overall developing history of the human society, the role of translation played in the cultural change can not be ignored. This paper has taken the translation of Uncle Tom’s Cabin as an example, discussed the functions of translation versions for literature works, and also set forth the significance of literature works translation versions in social culture from the perspective of macroscopic.
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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 | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.011 | 0.020 |
| Scholarly communication | 0.021 | 0.018 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".