Global Value Chains, Risk Perception, and Economic Statecraft
Bibliographic record
Abstract
Many countries, including the United States and China, have come to see economic statecraft as superior to armed conflict. Faced with a trading partner’s economic sanctions, some countries try to avoid risk by complying with or ignoring the coercer’s demands, but others retaliate and escalate conflict. In recent years, sanctions have been applied, not only to “rogue” states, but against trading partners. The United States and China, but also Japan, Australia, and Canada, were either the target or purveyor of economic coercion by or against trading partners in the last five years. However, not all resulted in trade wars. When, then, do economic sanctions lead to trade wars? This policy brief examines the ongoing Japan-South Korea trade dispute with a focus on how policymakers’ risk perceptions regarding global value chains (GVCs) can influence when trade wars take shape.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.041 |
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; both teacher heads agree on what is shown here.
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".