A Study on the Metaphor Translation Strategies in Selected Modern Chinese Essays 1 by Zhang Peiji from the Perspective of Conceptual Blending Theory
Bibliographic record
Abstract
According to the analytical framework of the three basic network models in Conceptual Blending Theory, this thesis dynamically presents the metaphor translation process and the choice of translation strategies in Selected Modern Chinese Essays 1 translated by Zhang Peiji. The study finds out that in Mirror Network Model, Zhang usually adopts literal translation while preserving the metaphorical image since the original metaphor shares the same organizational framework in both source culture and target culture; when it comes to One-scope Network Model, a majority of metaphorical images are omitted to achieve better readability while still some others are preserved to spread Chinese culture and introduce more cognitive models to target readers. And in both ways, paraphrases are added to deepen target readers’ understanding of the source text; with regard to Two-scope Network Model, Zhang mainly adopts the translation strategy of replacement with metaphors that accord with the target language, which enables him to build a bridge between the cultures of the source language and the target language.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".