Friends like this: The impact of the US–China trade war on global value chains
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 paper considers the indirect impact the recent tariff increases between the United States and China can have on third countries through links in global supply chains. We combine data from input–output relationships, imports and tariffs, to calculate the impact of the tariff increases by both the United States and China on cumulative tariffs paid by third countries. We show that the tariff hikes increase cumulative tariffs for other countries and thus hurt trade partners further downstream in global supply chains. We also show that this is particularly important for tariff increases on Chinese imports in the United States. These are likely to be used as intermediates in production in the United States, which are then re‐exported to third countries. The most heavily hit third countries are the closest trade partners, namely the EU, Canada and Mexico. We estimate that the tariffs impose an additional burden of around 500 million to 1 billion US dollars on these countries. China's tariffs on US imports have less of an effect.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it