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Record W2152854229 · doi:10.1017/s1755048310000076

Defining Nation and Religious Minorities in Russia and Turkey: A Comparative Analysis

2010· article· en· W2152854229 on OpenAlexaff
Laman Tasch

Bibliographic record

VenuePolitics and Religion · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicTurkey's Politics and Society
Canadian institutionsColumbia College
Fundersnot available
KeywordsIslamEthnic groupTurkishPolitical scienceReligious identityChristianityPoliticsFace (sociological concept)SociologyReligious diversityDiversity (politics)National identityGender studiesIdentity (music)Political economyReligious studiesSocial scienceReligiosityEthnologyLawHistory

Abstract

fetched live from OpenAlex

Abstract Many countries today face the challenges posed by their ethnic and religious diversity. This article comparatively analyzes how defining nation in Russia and Turkey affects what groups constitute religious minorities and what their prospects of integration into the Russian and Turkish societies are. It conceptualizes religious minorities as those religious groups that are excluded from the prevailing and institutionalized definitions of nation. This article studies what role religion, comprising Orthodox Christianity, and Sunni Islam, respectively, has played historically and until nowadays in Russia and Turkey in the definitions of their national identities and what kind of religious minorities each of these definitions created. It argues that a position of religious minorities depends not only on the informal association of national identity of the majority with certain religion, but also on the institutionalized support for the dominant religion by the ruling political forces.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.304
Teacher spread0.290 · 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 source (direct Gemma or distilled Codex), 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

Citations9
Published2010
Admission routes1
Has abstractyes

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