Quiet Diplomacy, the European Union and Conflict Prevention: Learning from the HCNM on Issues of Social Cohesion
Bibliographic record
Abstract
This article examines the issue of social cohesion inside the European Union (EU). While the organisation is currently experiencing an economic crisis the article argues that issues surrounding minority rights are deeper and more troubling. Within the EU’s current and prospective borders there remain issues surrounding national minorities, traditional migrants and intra-EU migrants. The intra-EU migrants are of particular interest in that they bridge the gap between the other two groups as they are migrants – with EU protected rights. This article argues that the EU itself must become involved in the maintenance of social cohesion. It recommends the use of quiet diplomacy, best illustrated by the Organization for Security and Co-operation in Europe High Commissioner on National Minorities. After an examination of the use of quiet diplomacy by the various High Commissioners the article outlines the issues of social cohesion facing the EU. It concludes with the recommendation that the European Commission adopt the tenets of quiet diplomacy as a means of influencing dialogue and to promote minority protection within the union.
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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 | 0.025 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.038 |
| Scholarly communication | 0.017 | 0.018 |
| Open science | 0.001 | 0.015 |
| Research integrity | 0.006 | 0.008 |
| 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".