Narrowing the Gap in Early Literacy for French Immersion Students: The Effects of a Family Literacy Intervention on Grade 1 Childrenâs English and French Literacy Development
Bibliographic record
Abstract
The study evaluated the effects of a Family Literacy program on Grade 1 French Immersion (FI) children’s language and literacy development. Family Literacy programs aim to encourage parents’ involvement in their children’s early literacy development and are associated with children’s increased performance on measures of early literacy. FI students typically lag behind their English program (EP) peers in English reading. It was hypothesized that a Family Literacy program for FI children would assist them in developing their English and French language and literacy skills. The study involved 71 Grade 1 children. The sample included both FI and EP children and their parents. The FI sample included a group of families who participated in the Family Literacy program and a control group of families who did not receive the intervention. The EP sample acted as a second control group. All children were administered a battery of language and literacy measures in English and in French (FI only) at three time points throughout Grade 1. \t\n\tResults showed that FI children who participated in the program made significantly larger gains in English writing than the FI control group. In addition, findings suggest that gains made by FI children following their participation in the program did not differ from those made by their EP peers who did not attend the program. Qualitative findings provide evidence that FI families who participated in the Family Literacy program increased their engagement in home literacy activities throughout the program, indicating that they adopted the strategies and techniques that were promoted by the program.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".