THE ANALYSIS OF THE REGIONAL ECONOMIC GROWTH AND THE REGIONAL FINANCIAL INDUSTRY DEVELOPMENT DIFFERENCE IN CHINA BASED ON THE THEIL INDEX
Bibliographic record
Abstract
Based on the panel data of 31 provinces and cities across China (except Hong Kong, Macao, and Taiwan) from 2003 to 2018, this paper identifies four economic regions i.e., eastern, central, western, and northeast, according to the national development layout. We study the degree of economic and financial disparities and its influencing factors in large economic regions of China. We use Granger causality measure to test whether there is a causal effect between economic and financial development in the regions of China. The relationship between growth, industrial structure, and economic vitality is comparatively analysed. The results of the study find that the economic and financial disparities in the four major regions are generally in a downward trend for these years. In addition, the relationship between the financial development of the four major regions and their economic growth, industrial structure, and economic vitality has obvious regional disparities. Lastly, we conclude that financial development does not necessarily follow economic development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".