Trump's tariffs: What escalating trade tensions with the US imply for EU exporters and supply chains
Bibliographic record
Abstract
US trade policy has taken a sharp turn away from multilateralism, with sweeping new tariffs posing a serious threat to global supply chains. As the US remains the EU’s largest export market for goods, these measures carry significant repercussions for the bloc. Exports to the US are heavily reliant on a small number of companies and high-value business relationships—making the EU particularly vulnerable to targeted trade measures. In Germany, the top ten business relationships alone account for a fifth of maritime exports to the US. Intra-company trade also plays a crucial role: One quarter of automotive exports from Germany to the US is between business entities with clear common ownership. Simulations further suggest that a transatlantic tariff conflict would halve EU exports to the US and trigger widespread production losses, with Germany’s GDP contracting by approximately 0.33% in the long term. To limit these economic damages and build long-term resilience, the EU should accelerate its export diversification by deepening trade ties with Free Trade Agreement partners and enhancing integration within the single market.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.012 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.015 | 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".