Bibliographic record
Abstract
The 2024 U.S. presidential campaign in the United States crowned with and Donald Trump’s victory bid to come back to the White House, have has had a significant impact on the debate within the U.S. about the state of relations with NATO allies and the future of NATO. Keeping in mind the crisis of those relations during Trump's first term, and taking into account the need to maintain NATO's viability and political will necessary to counter Russia’s warfare in Ukraine, the debaters are pondering possible options for reforming the American-European alliance and radically reducing the U.S. role in it. Reviewing a host of expert opinions in the US and Europe, the article concludes that, regardless of who holds the supreme power, the sentiments in the United States in favor of shifting the main burden of the European security onto Europeans themselves will grow, albeit without dissolving NATO. Russia's determination to revise, even by force, the unfavorable geopolitical architecture of Europe will contribute to such sentiments. The author dwells on some specific proposals by Western experts for a gradual “de-Americanization” of NATO and argues that, although these proposals do not entirely appear realistic, they serve as a warning that the future of the American “security umbrella” above Europe is not guaranteed.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.019 |
| Scholarly communication | 0.024 | 0.030 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.015 | 0.019 |
| Insufficient payload (model declined to judge) | 0.007 | 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".