“I just only speak English English”: stakeholders’ language ideologies and multilingual children’s monolingual becoming
Bibliographic record
Abstract
This qualitative inquiry explores the impact of language ideologies and their associated practices on multilingual children’s language choices. Informed by Bakhtin’s (1981) theory of ‘ideological becoming’ and Bronfenbrenner’s (1979) Bioecological Model, this study examined 32 critical stakeholders’ (9 classroom teachers, 13 parents, and 10 volunteer tutors) perspectives and practices in three ideological contexts (i.e. mainstream classrooms, an after-school reading programme, and the home) and their effects on 20 multilingual children in British Columbia, Canada. Analyses of interviews and participant observations revealed that stakeholders in the three social spaces within students’ mesosystems, including teachers, volunteer tutors in the after-school programme, and parents, shared monoglossic ideologies and practices in sustaining English as the dominant language for literacy and schooling. Consequently, multilingual students internalised these ideologies and were in the process of becoming English monolinguals. The findings have important implications for teacher and staff professional development, parental education, as well as explicit and implicit language policies and practices in formal and informal learning spaces. We advocate for special attention to multilingualism in formal education that is separate from official Canadian bilingual policies.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.015 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".