How big is the 'German locomotive'? A perspective from Central and Eastern European countries' unemployment rates \n \n \n
Bibliographic record
Abstract
Countries from Central and Eastern Europe have undergone a process of transition from communism to markets economies. The economic convergence, in terms of income, that these countries have achieved in recent years has been one of the cornerstones in the economic integration with Western Europe. In this paper we aim to analyze the degree of co-movement of unemployment rates in a sample of Central and Eastern European transition economies, and the role of German as the 'locomotive' in this process. We intend to test two hypotheses; first, is it possible to identify common patterns that are possibly linked to the economic convergence process in the unemployment rates cycles for this group of countries? And, second, is it possible to identify one of the main economic fundamentals that has acted as an attractor towards economic convergence? By means of nonlinear logistic smooth transition autoregressions and co-movement analysis we found that the German business cycle has acted as a common factor affecting the cyclical behavior of the unemployment rates in these countries. \n
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".