Policy Effects of the New Western Land-Sea Corridor from the Perspective of Regional Economic Coordinated Development: An Empirical Study Based on Provincial Panel Data
Bibliographic record
Abstract
The New Western Land-Sea Corridor development enables East and West to benefit from each other through a network of connected land and sea routes. The research period spans from 2014 through 2022 for all regions situated along the corridor. The study determines provincial and municipal economic connection strength through the urban flow intensity model. The research implements a multi-period difference-in-differences (DID) model to analyze how the corridor affects regional economic development coordination. The research demonstrates three main findings: (1) The corridor's operational start brought significant policy-driven improvements to regional economic connections which fostered unified economic growth. The results demonstrate stability through multiple verification procedures. The corridor's ability to drive coordinated economic development strengthens with time while the "13+1" cooperative framework produces better results. The corridor supports economic balance at different levels between northern and southern areas and between regions with varying economic development stages. The research outcomes provide valuable insights to enhance the New Western Land-Sea Corridor development while stimulating economic growth throughout its entire route.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".