Liberalism and cultural claims in Central and Eastern Europe: toward a pluralist balance†
Bibliographic record
Abstract
ABSTRACT. This article relies on cases from new EU member states in postcommunist Europe to integrate two overlapping debates about majority–minority relations. Since the Second World War, political theorists and international institutions have tended to discourage group-rights approaches in favour of individual rights; meanwhile, policy-makers who achieved interethnic peace in postcommunist Europe have often opted for group-rights approaches. On the basis of political theory, international norms and the conduct of political elites in this region, we argue that both the individual-rights and group-rights approaches can be differentiated internally along the dimension of pluralism – that is, their willingness to accommodate multiple processes of cultural reproduction. Moreover, both group-rights and individual-rights approaches can offer justifications for restricting minority cultural opportunities; furthermore, restrictive group-rights approaches sometimes cloak their efforts behind ‘Western-sounding’ individual-rights rhetoric. Likewise, both group-rights and individual-rights approaches can permit group accommodation that can lead to political integration. We find that de facto pluralist approaches to minority accommodation – often spearheaded by moderate parties of the majority in coalition with minority-group parties – encourage ethnic peace, regardless of their foundation in individual or group rights.
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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 | 0.013 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.051 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.001 | 0.013 |
| Research integrity | 0.004 | 0.005 |
| 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".