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Record W2340367441 · doi:10.1177/0888325415599192

Conceptualizing Party Representation of Ethnic Minorities in Central and Eastern Europe

2015· article· en· W2340367441 on OpenAlexaff
Harry Nedelcu, Joan DeBardeleben

Bibliographic record

VenueEast European Politics and Societies and Cultures · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean and International Law Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsEthnic groupPoliticsPolitical scienceRepresentation (politics)Political economyEliteDemocracyDemocratizationEast-Central EuropeCommunismSociologyLaw

Abstract

fetched live from OpenAlex

The political representation of ethnic minorities in the party systems of Central and Eastern European states remains understudied despite the consolidation of democracy in these countries following their accession to the EU. This paper asks what institutional factors influence the way ethnic minorities are represented in the party systems of Central and Eastern European states. It does so based on a comparison of ethnic minorities in two paired cases (Slovakia/Romania and Estonia/Latvia), each of which shows similarities in some regards but have different outcomes in terms of party representation. The paper specifically examines explanations for the diverse forms through which minorities are represented in these four countries with a focus on three distinct types: ethnic particularist minority parties, integrationist minority parties, and accommodative majority parties. We examine two institutional/political factors that influence specific minority party types: (1) electoral systems and (2) political strategies of the dominant ethnic elite. We argue that while electoral systems do play a role in explaining differences in the party representation of minorities, they become particularly important in the broader political institutional context that emerged in the first decade following the collapse of communism. The manner in which dominant ethnic political-elites approached minority representation in the early years of democratization is critical in explaining different types of party representation that ensued.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.282

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 integrity0.0000.000
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 head0.079
GPT teacher head0.333
Teacher spread0.254 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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

Citations6
Published2015
Admission routes1
Has abstractyes

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