The youngest bilingual Canadians: Insights from the 2016 Census regarding children aged 0-9
Bibliographic record
Abstract
This study used the 2016 Canadian Census data to examine home bilingualism amongst children aged 0–9 years. Across Canada, 18 percent of children used at least two languages at home, which rose to more than 25 percent in large cities, and the Canadian territories. English and French was the most common language pair in Quebec and Ontario, and various other pairs were spoken in most provinces. In the territories, 17 percent of children spoke an Indigenous language and English, and we discuss specific opportunities and challenges for Indigenous language revitalization. The presence of bilingual adults in the home, and immigration generation were the strongest predictors of children's home bilingualism. We conclude by discussing how policies can encourage child bilingualism, such as by supporting children’s home language in early and primary education settings. Such policies must be tailored to the needs of the specific communities to optimally support bilingual children and their families.
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 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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.539 | 0.312 |
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; both teacher heads agree on what is shown here.
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".