Bibliographic record
Abstract
Rising global political tensions and increasing use of trade policies are popularly seen as potential threats to globalization. Will these factors lead to the ‘decoupling’ of affected economies, or reshape relations between trade partners in more complex ways? We consider this question by studying the recent evolution of the economic relationship between China and the US, in the context of a sharp fall in direct China-US trade. Using firm-level and product-level data, we show that Chinese manufacturing investment and Chinese-produced parts have increasingly flowed to third-country ‘winners’ who have simultaneously increased their US market share. This suggests that Chinese economic actors have continued to participate in reorganized China-US supply chains. We present evidence that our findings capture expanding indirect relationships linking China and the US rather than broader economic trends within the ‘winners’ themselves. • The share of Chinese goods in US imports has fallen sharply in recent years. • However, we find evidence of expanding indirect China-US economic relations. • ‘Winners’ of US import share have hosted more new Chinese manufacturing affiliates. • Chinese parts have increasingly flowed to ‘winners’ of downstream US market share. • Rising political tensions and activist trade policy might not imply ‘decoupling’.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".