‘Nationalising states’ or nation‐building? a critical review of the theoretical literature and empirical evidence
Bibliographic record
Abstract
This article critically surveys the concept of nationalising states first coined by Rogers Brubaker when referring to the policies implemented by post‐communist states. The concept of nationalising states is placed within the context of the traditional literature on nationalism, which divides Europe into a ‘civic West’ and an ‘ethnic East’. The article discusses the concept of nationalising states and questions if it is really any different to nation building which took place from the late eighteenth century onwards in the ‘civic West’. Polyethnic rights are ignored on both sides of the classic ‘West:East’ divide. All civic states are composed of both civic and ethnic factors and the proportional relationship between them depends upon how much progress there has been in democratisation. The article concludes by arguing that the concept of nationalising states has little theoretical value unless it is equated with nation building and no longer selectively applied to only former communist countries. The traditional division of Europe into a ‘civic West’ versus an ‘ethnic East’ requires revision in the light of recent developments in Central and Eastern Europe.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.005 | 0.009 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".