New speakers of Ukrainian: Ideologies of linguistic conversion
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.
Bibliographic record
Abstract
Abstract The article examines ideologies behind linguistic conversion —a widespread transition to Ukrainian from Russian—which intensified in Ukraine after the onset of Russian aggression in 2014, and particularly after the 2022 full-scale invasion. Employing ‘new speakerness’ as a theoretical lens, the study draws on biographical interviews with twenty-one new full-time Ukrainian speakers recruited among participants in informal language-learning initiatives in Ukraine. The primary focus is on the ways in which the new speakers legitimise their ownership of the Ukrainian language: how they imagine their positions in the socially constructed traditional hierarchies of Ukrainian speakers, based on the mastery of the standard language, and what new ideologies arise out of their challenges. The findings reveal that, in most of the cases, traditional hierarchies are deconstructed as new ideologies prioritising fluency and elevating translingual practice emerge in the linguistic safe spaces of grassroots language courses and community clubs. (New speakers, language ideologies, linguistic conversion, suržyk , linguistic safe spaces, Russo-Ukrainian war)
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it