Spelling acquisition in French children with developmental language disorder: An analysis of spelling error patterns
Bibliographic record
Abstract
The aim of this longitudinal study was to examine spelling acquisition in French children with developmental language disorder (DLD) over a school year. Through a fine-grained spelling error analysis, we investigated whether spelling profiles could be established in the DLD population. This study comprised three groups: a typically developing (TD) group ( n = 16), a group of DLD children matched on spelling skills with the TD group ( n = 8), and a group of DLD children matched on chronological age and phonological awareness skills with their DLD peers ( n = 8), but showing weaker spelling skills. Results indicated that the DLD group matched on spelling skills with the TD group tended to produce more phonologically accurate spellings than the other DLD group. However, the two DLD groups did not differ on phonological awareness skills or vocabulary. Throughout the school year, the TD group and their DLD peers matched on spelling skills tended to add more silent letters in their spelling attempts than the other DLD group. With respect to phase models of spelling acquisition, our findings suggest that more advanced phases – like the orthographic and morphographic literacy phases – can be acquired even if the foundation processes are not well developed.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".