Convergence in European Cross-Border Structures: The Case of Spanish Euroregions
Bibliographic record
Abstract
European border regions are considered to be laboratories of the European integration. However, it is not clear whether that integration is an indicator of convergence between the regions, since it can result from similarities as well as from existing differences between border regions. This paper studies the processes of σ, β and spatial convergence in the particular case of the Euroregions, mixed territories with (international) border and non-border regions, with the aim of determining whether the intense cooperation relationships that occur in these particular structures stimulate the convergence as well as contribute to the levelling of the economic inequalities within the Euroregion. Specifically, we focus on the Spanish Euroregions, to analyze how the inherent differences between the border countries could determine the presence or absence of convergence in the Euroregions. The results show that convergence is achieved in the Spanish Euroregions that share a border with Portugal but not in those bordering France.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".