Research on the Problems and Countermeasures in the Economic Integration of the Yangtze River Delta
Bibliographic record
Abstract
At present, under the background of the rapid development of the world economy, the emergence of various multilateral or organization makes it more and more closely with the economic coordination mechanism.In the process of China’s economic development, the Yangtze River Delta region, as an important part of China’s economic development, is an important factor to promote the development of domestic market economy. However, under the influence of the novel coronavirus pneumonia epidemic, the problems of market development and planned economy are more obvious, and the development resistance between cities is also large.Starting from the actual situation of China’s national conditions, this paper studies the market-oriented reform and the transformation of capital economy existing in the regional integration of the Yangtze River Delta, summarizes the current situation faced by the Yangtze River Delta, the development goals and ideas, the improvement of the coordination system of funds, finance and taxation and the development prospects, and puts forward some targeted countermeasures according to these problems. The Yangtze River Delta region can better promote its own high-quality development under the new development pattern with the domestic great cycle as the main body and the domestic and international double cycles promoting each other.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".