Bibliographic record
Abstract
January 20, 2025 is the formal start date of a Trumpian world.Given the character of Donald Trump and his recent wild announcements ranging from ambitions with Greenland to threatening tariffs on even the closest US allies like Canada, it is anybody's guess what he will do next.However, one issue that Donald Trump has been consistent about for decades is trade policy.He is the self-declared "tariff man" -nearly 40 years ago, Trump went public with a proposal to tax imports from the perceived main competitor at the time, Japan (CNN, 1987).A second consistency is his disdain for legal niceties like the rules of the World Trade Organisation.This has understandably created anxieties in Brussels.The EU is the largest exporter in the world, even larger than China.EU exports account for about 25% of EU GDP, much more than for the US.The US is also the largest export market for the EU.All this seems to suggest that Europe has much to fear on the trade front.However, upon closer inspection, the Trump II Administration could, if handled well, present more opportunities than threats for Europe.
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.005 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.015 | 0.012 |
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".