The Influence of Dominance and Sociolinguistic Context on Bilingual Preschoolers' Language Choice
Bibliographic record
Abstract
Two-year-old bilingual children can show sensitivity to the language choice of their interlocutor, but do not necessarily achieve perfect separation by discourse context, e.g. speaking only French with a French interlocutor; dominance in one language is often cited as a reason for this. In this study we asked whether older bilingual preschoolers would show more absolute discourse separation than had been established with younger children because their more advanced linguistic development may diminish the constraining role of dominance in language choice. These children resided in an English majority–French minority region of Canada where virtually all francophone adults are bilingual, but not necessarily anglophone adults. Therefore, we also considered the potential interacting effects of the minority French context on children's dominance and language choice. Four French-dominant and four English-dominant bilingual children participated in two free-play situations, in French and in English. The French-dominant children showed discourse separation of the two languages in both English and French contexts, while most of the Englishdominant children spoke a lot of English in the French context. These results suggest that discourse separation of two languages by bilingual preschool children is possible, but not always practised due to the interaction of language dominance and children's sensitivity to the sociolinguistic context.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".