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Record W4411710533 · doi:10.1515/ijsl-2025-0019

Language beliefs, attitudes and practices in contemporary Kyrgyzstan with particular reference to English

2025· article· en· W4411710533 on OpenAlexaff
Feruza Shermatova, Maksat Totobayev, Stephen A. Bahry

Bibliographic record

VenueInternational Journal of the Sociology of Language · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsLinguisticsSociologyPhilosophy

Abstract

fetched live from OpenAlex

Abstract Kyrgyzstan’s language ecology is shaped by its Turkic roots, with Kyrgyz as the state language and Uzbek as a key minority language. Russian, historically dominant, remains the most widespread foreign language and continues to play a central role in the country’s linguistic hierarchy. Since independence in 1991, English is the most widely taught foreign language, often in English-medium instruction (EMI). Increasing English use reflects broader global trends linked to World Englishes and raises questions about evolving language ideologies in the region. This article traces the development of English in Kyrgyzstan, analyzing its position within a linguistically hybrid and hierarchical setting. It presents new research on university language majors, focusing on their language beliefs, attitudes, and practices regarding English in relation to Kyrgyz and Russian. The study highlights emerging patterns of Kyrgyz-Russian-English trilingualism and explores how English functions – whether competitively, subtractively, or complementarily – within this multilingual environment, calling for further research and reflection on language and education policy.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.257
Threshold uncertainty score0.374

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.070
GPT teacher head0.493
Teacher spread0.423 · 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

Citations1
Published2025
Admission routes1
Has abstractyes

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