A longitudinal examination of French and English reading comprehension in French immersion programs in Canada
Bibliographic record
Abstract
Abstract Parental level of education, instruction time, and amount of language practice that children receive have enhanced our understanding of how bilingual and multilingual children learn to comprehend text. Guided by the simple view of reading and the interdependence hypothesis, this longitudinal study conducted in Canadian French immersion programs examined the (a) within- and cross-language association between oral language skills and reading comprehension of bilingual English–French and multilingual children and (b) patterns of growth, while controlling for possible influences of parental level of education and methods of instruction on reading achievement. The sample included 150 children tested once at the beginning of Grade 4 (T1) and again at the end of Grade 4 (T2) and in Grade 6 (T3). Individual growth modeling revealed that bilingual and multilingual children showed similar development in oral language and reading skills across the timeframe. Moreover, growth in English and French reading comprehension was associated with within-language variables. English reading comprehension in Grade 4 was also associated with cross-language variables, including French listening comprehension and vocabulary knowledge. Reading development in the second and third language is enhanced in contexts where classroom instruction, as well as social, economic, and educational opportunities to learn, is equivalent for all students.
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 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 | 0.001 |
| Bibliometrics | 0.002 | 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".