The Overlap of Poor Reading Comprehension in English and French
Bibliographic record
Abstract
This study examined overlap and correlates of poor reading comprehension in English and French for children in early French immersion. Poor comprehenders were identified in grade 3 in English and French using a regression method to predict reading comprehension scores from age, non-verbal reasoning, word reading accuracy, and word reading fluency. Three groups of poor comprehenders were identified: 10 poor comprehenders in English and French, 11 poor comprehenders in English, and 10 poor comprehenders in French, and compared to 10 controls with good reading comprehension in both English and French. There was a moderate degree of overlap in comprehension difficulties in English and French among poor comprehenders with equivalent amounts of exposure to French, with a prevalence rate of 41.7% in our sample. Children who were poor comprehenders in both English and French consistently scored the lowest on English vocabulary in grade 1 and grade 3 and in French vocabulary in grade 3 suggesting that poor comprehenders' vocabulary weaknesses in English as a primary language may contribute to comprehension difficulties in English and French.
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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 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".