Early reading development of plurilingual children: a longitudinal study
Bibliographic record
Abstract
As the cultural and linguistic diversity within Canadian society steadily increases, there arises a need to gain a deeper understanding of early reading development in children within this context. To address this issue, the current study used a longitudinal design to evaluate whether intensive experience using languages represented by either alphabetic or logographic scripts in addition to English benefited rates of English reading development of 136 plurilingual children from kindergarten to grade 2. Participants were assigned to three groups that represented their experience with English and languages and writing systems in their homes and communities. The first group had intensive experiences with English and another Alphabetic writing system, the second group had intensive experience with English and a language represented by a Logographic writing system; and the third group used mostly English in their communicative interactions. Consistent with a script dependent hypothesis, the findings showed that word reading development from kindergarten to grade 2 was accelerated for plurilingual children with experience using English and another alphabetic language compared to children who spoke primarily English, or English and a logographic language. This reported benefit for English word reading did not appear to generalise to English reading fluently or reading comprehension.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".