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Record W1606285175

Islam and Nationalism in the Formerly Soviet Central Asian Republics

2005· article· en· W1606285175 on OpenAlexaff
James G. Mellon

Bibliographic record

VenueThe Journal of Conflict Studies · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Conflict and Governance
Canadian institutionsDalhousie University
Fundersnot available
KeywordsIslamDemocratizationPolitical scienceAuthoritarianismOpposition (politics)Independence (probability theory)Political economyLegitimacyNationalismState (computer science)DemocracyTerrorismDevelopment economicsEconomic historyLawSociologyHistoryPolitics
DOInot available

Abstract

fetched live from OpenAlex

When the Soviet Union collapsed, the Central Asian republics, which had not really sought independence, found themselves independent. Unlike what happened in some other parts of the former Soviet Union, the regimes in power under the Soviet Union remained in power, and endeavored through authoritarian means and trying to identify themselves with nascent nationalisms to suppress opposition and seek an aura of legitimacy. These regimes sought to suppress expressions of Islam and Islamic revivalism outside of state-sponsored Islam. Particularly in the aftermath of 11 September, it has been expedient for these regimes to label non-state-sponsored Islam as Wahhabi, even though most of this Islam has been of the more moderate indigenous Hanafi school. Progress in democratization has varied among the republics but has been slow in all of them. Until the overthrow of Askar Akayev in Kyrgyzstan in March 2005, only Tajikistan, which had experienced a civil war, had changed leaders since independence. This article expresses concern that a focus on fighting terrorism may lead to a tendency to overlook issues of human rights and democratization in these states.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.008
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.066
GPT teacher head0.383
Teacher spread0.317 · 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 designNot applicable
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

Citations0
Published2005
Admission routes1
Has abstractyes

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