Boarding the Euro Plane: Euro Adoption in the Czech Republic and Slovakia
Bibliographic record
Abstract
What explains the euro adoption strategies in the Czech Republic and Slovakia? How have each of these two countries performed under the regime they joined (Czech Republic: flexible exchange rates; Slovakia: in the euro area)? How has that experience affected Czech and Slovak policies towards euro adoption and their performance during the euro crisis? This paper asks these questions and seeks to give an answer to the question why Slovakia adopted the euro while the Czech Republic did not. We address these questions by taking an eclectic approach that draws on constructivism and symbolism, historical institutionalism and domestic politics. The paper examines five explanations based on these theoretical approaches: the inferiority-superiority factor; European identity and the ‘return’ to Europe; symbolic factor of the currency; euroskepticism; and economic structure and trade relations.
 Full text available at: https://doi.org/10.22215/rera.v9i2.232
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".