Stress Test for the Policy-making Capability of Cross-border Spaces? Refugees and Asylum Seekers in the Euroregion Tyrol-South Tyrol-Trentino
Bibliographic record
Abstract
This paper focusses on the role of border regions in the governance of refugee flows. By analyzing the political discourse with regard to refugees and asylum seekers in the Euroregion Tyrol-South Tyrol-Trentino, the paper evaluates the strength of ideational ties and of ideological frames for cross-border, policy-making capabilities in a contested policy field. The paper further develops the framing of the ideational dimension of cross-border cooperation by shifting the focus from the individual to the collective political level and from symbols to political discourse. Due to the favorable and institutionalized framework of cross-border cooperation, we assume strong ideational ties to increase the policy-making capability of border regions in the governance of migration flows independent from national frameworks. We show that regardless of the institutionalization of cross-border cooperation and frequent references to the Euroregion in the political discourse of all sub-state parliaments, the ideational frame for common actions regarding refugees and asylums seekers is eclipsed by the national context that continues to outweigh a local transnational identity. This hinders the capability of common policy making within cross-border regions. Nevertheless, we argue that border regions have the potential to fill a gap in the multilevel governance of migration by becoming mediators across borders and between states.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.008 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".