Home literacy environment and early bilingual vocabulary development among Chinese–Canadian children: a longitudinal study
Bibliographic record
Abstract
This longitudinal study examines the relationship between Chinese-Canadian children’s (N = 173) home literacy environment (HLE) and their bilingual receptive vocabulary development in English and Chinese from grades 1–3. Bilingual receptive vocabulary in Chinese and English and quality and quantity of HLE measures were collected. Sociodemographic information in L1 (Cantonese or Mandarin), gender, socioeconomic status (SES), and immigration status were also collected. Descriptive analyses of data showed that the children’s English receptive vocabulary increased significantly while their Chinese vocabulary decreased substantially over the three grades. There were also gender, SES, and home language (Mandarin or Cantonese) differences in bilingual receptive vocabulary skills. Hierarchical linear modeling (HLM) analysis results indicated that the quantity of home language use was significantly correlated with Chinese receptive vocabulary development but not with English receptive vocabulary. High-quality home literacy activities were significantly associated with vocabulary in both languages. These findings have important implications for parental engagement in early biliteracy and early literacy instruction in schools.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".