A crisis of integration? The development of transnational dyadic trust in the European Union, 1954–2004
Bibliographic record
Abstract
Abstract The healthy functioning and long‐term viability of the European Union (EU) ultimately depend on its citizens finding common cause and developing a shared sense of political community. However, in recent years, scholars and pundits alike have expressed doubts about whether the EU's growing cultural, religious and economic diversity is undermining the development of citizens' shared sense of political community, especially following eastern expansion. In this article, this question is examined using data on a key aspect of political community: transnational dyadic trust. Drawing on a unique set of opinion surveys from the formative years of the EU to the first wave of eastward expansion (1954–2004), the development and sources of dyadic trust among EU Member States is studied. While recognising the importance of diversity for trust judgments in the short‐term, the prevailing viewpoint that it is also a long‐term obstacle to integration is challenged. Instead, it is argued that citizens from diverse cultural and economic backgrounds can learn to trust one another and build a sense of political community over time through greater cooperation and interconnectedness. This theory is tested with data on bilateral trade density, which is seen as a proxy and precursor for other forms of cross‐national interconnectedness. Employing longitudinal models, the article also goes beyond existing research to test the theories over time. The study makes a contribution to the research on European integration, suggesting that over time mutual trust and a shared sense of political community can indeed develop in diverse settings.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.005 |
| 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 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".