Transatlantic relations challenge and resilience
Bibliographic record
Abstract
This book explains how and why the transatlantic relationship has remained resilient despite persistent differences in the preferences, approaches, and policies of key member states. It covers topics ranging from the history of transatlantic relations, NATO and security issues, trade, human rights, and the cultural sinews of the relationship, to the impacts of COVID-19, climate change, think tanks, the rise of populism, public opinion, and the triangular relationship between the United States, Europe, and China. The book also conceptualizes resilience as a quality arising from myriad forms of interdependence. This interdependence helps shed light on the Atlantic partnership's capacity to withstand serious disagreements, such as those that occurred during the Reagan, George W. Bush, and Trump presidencies. With a principle focus on the US and Europe, the contributors to the volume also employ Canadian case studies to provide a unique and useful corrective. This book will interest all intermediate and senior undergraduate as well as graduate courses on relations between the US and Europe, American foreign policy, and European Union foreign policy. A specialist readership that includes academic and think tank researchers, policy practitioners, and opinion leaders will also benefit from this timely volume
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.010 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".