The Leading Role of Chinese Discourse in Global Context: The Variation Theory of Comparative Literature
Bibliographic record
Abstract
Chinese scholar Cao Shunqing devoted himself to the construction of Chinese Comparative Literature discourse system and successfully established a new discourse of the variation theory of comparative literature in the eponymous book. This is the latest practice of President of the People’s Republic of China Xi Jinping’s advocation to construct Chinese discourse theories. The variation theory of comparative literature is a significant concept that has been accepted and applied by the international society, in which its effects have conducted major contributions to the development of discourse system and literature theory with Chinese characteristics. And it has positively pushed the construction of Chinese soft power in the global context. As a new concept, a new field, and a new statement, the emergence of the variation theory of comparative literature has led to heated discussions and researches at the international academic level and received great feedbacks from various scholars, both national and international.
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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 | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.006 | 0.030 |
| Scholarly communication | 0.008 | 0.011 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".