The Pragmatics of Chinese Proverb Quoting in the English and the Russian-Language Mass Media of PRC
Bibliographic record
Abstract
Mass media of PRC in languages others than Chinese native (in the present research English and Russian) are aform of cross-cultural communication between China and the rest of the world. In other-language mass mediaChina not only presents its views and attitude to the events described, but also reveals China “the whole self” byemploying the fragments of its traditional verbal culture, proverbs in particular being the ways of self-expression.However, the research provided evidence that the foreign-language press of China carefully considers theappropriateness of proverb quotations, and thoroughly estimates the degree of transmitted by them informal andindirect culture-based information, which the target audience is capable or incapable to grasp, share, and abideby. Proverbs generally being among the most indirect strategies of reasoning and persuasion in some contextualuse may convey straightforward and strict judgments. The paper studies significant theoretical issues andapplication aspects of proverb quoting in the foreign-language press of PRC which depends on crucial questionsof cross-cultural pragmatics: first, the addressor’s natural urge for culture-based self-expression alongside withstriving for intelligibility to the foreign target audience, and second, the addressor’s choice of higher / lowercontext in communication with different cultures-addressees. This accounts for the discrepancy betweenpresentation of information in the English-language press of PRC and the Russian-language periodical of China. Both questions suggest a wide range of options in proverb quoting (preserving/omitting a proverb, originalproverb with glossing / loan translation, meaning / connotation modulation of a proverb, etc).
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How this classification was reachedexpand
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".