MétaCan
Menu
Back to cohort
Record W4415213925 · doi:10.1017/nps.2025.10110

Ukrainian Russophones’ Engagement with Language Education Policies

2025· article· en· W4415213925 on OpenAlex
Anna Vozna

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNationalities Papers · 2025
Typearticle
Languageen
FieldArts and Humanities
TopicLinguistics, Language Diversity, and Identity
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsUkrainianFraming (construction)Unitary stateLanguage policyAccountabilityStandardized testSubject (documents)

Abstract

fetched live from OpenAlex

Abstract The study explores the engagement of Russophone Ukrainians with educational policies that increase the status of the Ukrainian language, the standardized tests of Ukrainian, and the subject tests that could be passed in Ukrainian. It argues that this centralized unitary language policy has received support from Russophones. It does so by analyzing the language choices of Russophone students when taking standardized tests in various subjects, as well as admission policies and discussions of relevant policies in local media and social media of the Russophone city of Kharkiv. It shows that following the introduction of standardized tests, the value of Ukrainian has increased across various actors: students have been choosing Ukrainian more, universities have valued Ukrainian in the admission process, and local citizens have defended the status of Ukrainian, relying on decolonial rhetoric. It shows that the decolonial framing of the Ukrainization policies resonated with Russophones enough for them to support them, and not to result in a backlash.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.013
GPT teacher head0.257
Teacher spread0.244 · 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