An Analysis of the Translation Choice of Henryk Sienkiewicz’s Works in The Collected Works of Foreign Fictions Translated by the Zhou Brothers from the Perspective of André Lefevere’s Three Factors Theory
Bibliographic record
Abstract
In The Collected Works of Foreign Fictions, the Zhou brothers translated three short stories written by Polish writer Henryk Sienkiewicz as translation materials, but not any of his more popular novels. This article discusses such a translation choice made by the Zhou brothers from the perspective of Three Factors Theory proposed by André Lefevere. Firstly, because of a lack of stable patronage, the Zhou brothers intentionally chose obscure materials to translate, in order to get access to publication and avoid retranslation. Henryk Sienkiewicz’s short stories, compared with his novels, were obscure materials. Secondly, from the perspective of poetics, the Zhou brothers were influenced by the poetics of Georg Brandes and believed that “Henryk Sienkiewicz’s novels were driven by profit” and denied the literary value of his novels. Lastly, from the perspective of ideology, the Zhou brothers, especially Lu Xun, emphasized the ideological factors and paid attention to themes such as “small and weak nations” and “being oppressed.” As Poland was a real oppressed nation, the ideology reflected in the Polish writer Henryk Sienkiewicz’s three short stories were consistent with that of the Zhou brothers.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".