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Record W3164642856 · doi:10.30819/5192

Separatism and Regionalism in Modern Europe

2020· book· en· W3164642856 on OpenAlexaboutno aff

Bibliographic record

VenueLogos Verlag Berlin eBooks · 2020
Typebook
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsRegionalism (politics)Political scienceLawPolitics

Abstract

fetched live from OpenAlex

The end of the Cold War opened a Pandora's box of regionalism and separatism across Europe, and today they once again pose a significant threat to the territorial and political integrity of the traditional nation-states. Yet, the existence of various subnational groups is inevitable in democratic states. The scope of separatism and regionalism in Europe is quite wide. It includes de facto states, such as Kosovo, Transnistria, and North Cyprus; strong separatist movements aimed at achieving independence, like Catalonia, Basque Country, Scotland, Flanders, and Faroe Islands; strong movements aimed at achieving a more regional autonomy, for example, Lombardy and Veneto; and weaker regional movements, which could potentially escalate in the future, such as Transylvania in Romania or Vojvodina in Serbia. This edited volume tackles all the above-mentioned regional moments and even includes Greenland as a bonus. It brings together seventeen prominent scholars from a wide range of European and North American academic institutions who compiled ten chapters to shed light on the revival of regionalism and separatism via a thorough evaluation and analysis of some of the most important current separatist and regionalist/autonomist movements across modern Europe. Chris Kostov is an Adjunct Professor in the School of International Relations at IE University Madrid, Spain. He earned his PhD in History and Canadian Studies from the University of Ottawa, Canada. His main academic interests include Balkan and modern European nationalism and Communist repressions in Cold War Eastern Europe.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.875
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.036
GPT teacher head0.286
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations8
Published2020
Admission routes1
Has abstractyes

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