The Language Abilities of Children Considered At-Risk for Academic Difficulties Enrolled in Early French Immersion
Bibliographic record
Abstract
Children with additional learning needs are disproportionately excluded from dual language education programs, in part because of concerns that bilingualism will exacerbate existing difficulties with language (Marinova-Todd et al., 2016). To address these concerns, this thesis investigates syntactic and morphosyntactic development in children with additional learning needs, who are registered in early French immersion (EFI). Participants were children who are often considered at-risk for academic difficulty (AR) enrolled in EFI (n = 13), children who were AR enrolled in an English-only program (ELoI; n =15), and children who were not AR enrolled in EFI (n = 10). No group differences were found between participant groups. The grammatical errors produced by children in each group were also examined and similar error patterns were observed across the three groups. These findings illustrate that children with additional learning needs are developing both English and French abilities when enrolled in EFI.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".