Political Metaphors in English Version of “Report to the 20th National Congress of the Communist Party of China”
Bibliographic record
Abstract
With China’s growing influence, many countries are eager to know about China, and China also wants foreign countries to have a correct understanding of itself, so translations of political discourse are important. And because metaphor can reflect the thinking of the authors and translators, it is widely used in the translation process to transmit the ideology. Since now, many researches have been done to study the types of metaphors and the translation strategies of metaphors in the translations of the CPC literature, but few of them focus on how metaphors in the translation version convey the ideology. Therefore, this paper, aiming to study how political metaphors in the translation help transmit the ideology and governance thought of China to the world, applies Critical Metaphor Analysis as the analytical framework to investigate the political metaphors in English version of “Report to the 20th CPC National Congress”. The results show that journey metaphors, building metaphors, plant metaphors, life metaphors, and war metaphors are especially prominent. Compared with literal translation, the English version of the Report utilizes the imagery and concepts familiar to the readers to lead them to understand the Chinese theories and thinking that they are unfamiliar with. And the political metaphors explain and publicize the governance philosophy in a way that foreign readers can understand, highlight the Party’s attitude, and correctly display the image of China. This study deepens the study of the role of metaphors in the transmission of governments’ principles and policies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".