Bibliographic record
Abstract
In the context of globalization, as China is becoming an important character on the world stage, Chinese literature’s mission is to be known by the world, and Chinese literature is poised to change the shared cultural landscapes in the world. However, contemporary Chinese literature is not as popular in the world as Western literature in spite of the implementation of “going out” strategy. Chinese literature, in the age of globalization, is increasingly marginalized by world literature. Some scholars hold the idea that for Chinese literary seeking recognition in the realm of world literature, the most formidable challenge to improve the status of Chinese literature at present is either ensuring the proper translation into English or securing the target readers’ access to them. The most important point is that the target readers’ need to be contextually activated and to become actively present in the world literary system. Based on the current international situation, the paper introduces a brief introduction of modern Chinese literature, some performances of the marginalization of modern Chinese literature and analyses the reasons why Chinese literature is not well received as Western literature. The paper is rounded off with suggestions from certain aspects as to what we can do to improve the status of Chinese literature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.015 | 0.021 |
| Science and technology studies | 0.008 | 0.007 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".