The European Neighbourhood Policy: Assessing the EU's Policy toward the Region
Bibliographic record
Abstract
In a relatively short amount of time, the EU has become one of the world's most powerful and important actors on the world stage. Now for the first time this volume explores the goals and effectiveness of the EU's special approach to foreign policy; how its policy is perceived by outsiders and the ramifications of those views; the EU's relations with its neighbors, as well as countries well beyond its borders; and how the EU has and can promote its values abroad. "One of the most comprehensive studies of the EU foreign policy to date. The EU's foreign policy is not an easy subject to tackle, but the contributors do it in an elegant and cogent manner." —Luciano Bardi, University of Pisa and President of the European Consortium for Political Research Contributors include Irina Angelescu (IHEID, Geneva), Elena Baracani (Italian Institute for Human Sciences), Mara Caira (IULM, Milan), Maurizio Carbone (University of Glasgow), Tom Casier (University of Kent), Natalia Chaban (University of Canterbury), Marta Dassù (Aspen Institute Italia), Khalid Emara (Egyptian Foreign Ministry), Laura C. Ferreira-Pereira (University of Porto), Serena Giusti (ISPI and Catholic University of Milan), Luca Gori (Italian Foreign Ministry), Alberto Heimler (SSPA—Italian Public Administration Graduate School), Martin Holland (University of Canterbury), Joseph S. Joseph (University of Cyprus), Stephan Keukeleire (Katholieke Universiteit Leuven and College of Europe), Finn Laursen (Dalhousie University), Francesca Longo (University of Catania), Roberto Menotti (Aspen Institute Italia), Andrew Moravcsik (Princeton University), Philomena Murray (University of Melbourne), Stefania Panebianco (University of Catania), Tomislava Penkova (ISPI, Milan), Lara Piccardo (University of Genoa), Joaquín Roy (University of Miami), Jeremy Shapiro (Brookings Institution), Alfred Tovias (Hebrew University and Leonard Davis Institute for International Relations), Nicola Verola (Italian Foreign Ministry), Bernard Yvars (University of Montesquieu, Bordeaux).
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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 | 0.006 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".