Like mother like child: Differential impact of mothers' and fathers' individual language use on bilingual language exposure
Bibliographic record
Abstract
Language exposure is an important determiner of language outcomes in bilingual children. Family language strategies (FLS, e.g., one-parent-one-language) were contrasted with parents' individual language use to predict language exposure in 4-31-month-old children (50% female) living in Montreal, Quebec. Two-hundred twenty one children (primarily European (48%) and mixed ethnicity (29%)) were learning two community languages (French and English) and 60 (primarily mixed ethnicity (39%) and European (16%)) were learning one community and one heritage language. Parents' individual language use better predicted exposure than FLS (explaining ~50% vs. ~6% of variance). Mothers' language use was twice as influential on children's exposure as fathers', likely due to gendered caregiving roles. In a subset of families followed longitudinally, ~25% showed changes in FLS and individual language use over time. Caregivers, especially mothers, individually shape bilingual children's language exposure.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".