Hub-Periphery Development Pattern and Inclusive Growth: Case Study of Guangdong Province
Bibliographic record
Abstract
The hub-periphery development pattern of \n the Guangdong economy, to some extent, is a miniature of \n that of the Chinese economy. The Pearl River Delta, drawing \n from its first-nature comparative advantages in factor \n endowments and proximity to Hong Kong SAR, China, and Macau \n SAR, China, and the second-nature advantages as first-movers \n in the reforms in attracting and retaining domestic and \n foreign resources, has developed into a regional economic \n center. This paper examines the pattern of inter- and \n intra-provincial migration and that of the concentration of \n production, to explore the challenges and opportunities for \n the success of “double transfer.” The paper suggests a \n four-prong approach, to improve the business environment, \n support the realization of latent comparative advantages, \n increase the skill level of the labor force to support the \n upgrade of the production structure, and protect the \n vulnerable, to support the inclusive growth of the economy \n in Guangdong in a sustainable manner.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".