Reading development of Chinese-English bilingual early elementary children: Variations by student sociocultural characteristics during COVID-19 in Canada
Bibliographic record
Abstract
In this two-year longitudinal study, multiple analytical methods of analysis were used to examine the development of reading comprehension, decoding, and oral receptive vocabulary among Chinese-English bilinguals (N = 135) in Canada during grades 2 and 3, as well as the sociocultural factors influencing their academic performance during the COVID-19 pandemic. One-sample t-tests revealed that while Chinese-Canadian children's reading comprehension and decoding skills were comparable to monolingual norms, their English receptive vocabulary significantly lagged behind the normative mean. Independent samples t-tests indicated a pandemic-related decline in reading skills over two years, with significant reductions in decoding, particularly among Mandarin-speaking children. Hierarchical Linear Modeling (HLM) analyses showed that gender significantly moderated reading comprehension development, while family socioeconomic status (SES) was strongly associated with growth in decoding and oral receptive vocabulary. These findings highlight the need for post-pandemic recovery efforts focused on vocabulary development and decoding support, particularly for children from intersectionally disadvantaged backgrounds.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".