Russian-Chinese Relations in the Field of Culture (1990-s – 2000-s)
Bibliographic record
Abstract
The relevance of the study of this problem stems from the fact that the Russian-Chinese relations are one of the most important indicators of the situation in the world. They are the source of dependence not only for political, socio-economic situation in the Asia-Pacific Region (APR), but also the global political climate. In recent years, it has become more and more obvious and urgent to formulate new theoretical and practical approaches to the study of interaction between Russia and China, which both have bright cultural and historical features. Humanitarian ties play a great role in the relationships between these states and have a major impact on the process of their interaction. The article provides an overview of Russian-Chinese relations in the field of culture in the 1990s - 2000s. Particular attention is paid to the coverage of cooperation of intergovernmental organizations of Russia and China in the field of culture and education, as well as reviews the regulatory framework of the cultural partnership between Russia and China. The aim of the present work is a detailed analysis and evaluation of key bilateral humanitarian projects during the study period. The article submissions may be useful for specialists involved in the study of Russian-Chinese relations at the present stage, researchers and university teachers of the humanities. The article is also recommended to undergraduate, graduate and post-graduate students with in-depth research training.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| 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".