Inquiry into FDI Pattern of China and the Economies along the Belt & Road
Bibliographic record
Abstract
This paper empirically analyzes the FDI Pattern of China and the other economies along the Belt & Road Initiative. The analysis results show that 1) the mutual FDI between China and the economies along the Belt & Road regions has continuously increased, and the mutual dependence of FDI continues to deepen, but there still is some imbalance existing in FDI dependence and distribution; 2) the Belt & Road Initiative has its objective material basis and subjective willingness for regional FDI cooperation; 3) China and the other economies along the Belt & Road Initiative, need to further utilize the complementary advantages in their industrial and economic structures for deepening the bilateral and multilateral FDI cooperation; 4) China and the countries along the Belt & Road need to clear the investment barriers and achieve a win-win situation for international investment and cooperation, in order to promote the continuous deepening of the Belt & Road Initiative and realize regional common prosperity.
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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 | 0.000 | 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 | 0.001 | 0.007 |
| 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 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".