Bibliographic record
Abstract
Part I: Before EMU: Some Historical Perspectives 1. Alison Meek Building Europe Brick by Brick 2. Xavier de Vanssay Monetary Unions: an Historical Perspective 3. Tim Le Goff Monetary Unification Under the French Monarchy Part II: Before EMU: Reflecting on the Debate 4. Amy Verdun Why EMU Happened: a Survey of Theoretical Explanations 5. James Dean The Economic Case Against the Euro 6. Patrick Crowley International Implications of EMU Part III: Beyond EMU: Lessons for EMU 7. Mitchell Smith EMU and Political Mobilization: Lessons from the Single Market 8. Malte Kruger Some Canadian Lessons for EMU 9. Patrick Crowley European Integration After EMU: What Next? Part IV: Beyond EMU: Evaluating Success 10. Eric Helleiner One Money, One People: Political Identities and the Euro 11. David Long The European Union and the Transformation of International Relations
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.008 | 0.011 |
| Scholarly communication | 0.011 | 0.017 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.022 | 0.004 |
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".