Value, Structure and Spatial Distribution of Interprovincial Trade in China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract This study uses two different datasets to explore the stylized facts of interprovincial trade in China during the recent two decades. One dataset provides the magnitude of bilateral interprovincial goods trade calculated using firms' value‐added tax invoices. The other supplies estimates of interprovincial trade using provincial input–output tables. We find that China has both a large value and a high growth rate of interprovincial trade, but there still exists a home bias in internal trade for most provinces. In addition, disaggregation by product shows that the manufacturing sector has the largest share of interprovincial trade and this share continues to grow. Finally, the spatial distribution of trade suggests that all provinces can be clustered into a smaller number of trade areas with large intra‐cluster trade. Therefore, China's central government should make more effort to reduce local protection, stimulate domestic demand and coordinate interregional trade among local jurisdictions.
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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 | 0.000 | 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 | 0.000 | 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 it