Early motor development and later language and reading skills in children at risk of familial dyslexia
Bibliographic record
Abstract
Relationships between early motor development and language and reading skills were studied in 154 children, of whom 75 had familial risk of dyslexia (37 females, 38 males; at-risk group) and 79 constituted a control group (32 females, 47 males). Motor development was assessed by a structured parental questionnaire during the child's first year of life. Vocabulary and inflectional morphology skills were used as early indicators of language skills at 3 years 6 months and 5 years or 5 years 6 months of age, and reading speed was used as a later indicator of reading skills at 7 years of age. The same subgroups as in our earlier study (in which the cluster analysis was described) were used in this study. The three subgroups of the control group were 'fast motor development', 'slow fine motor development', and 'slow gross motor development', and the two subgroups of the at-risk group were 'slow motor development' and 'fast motor development'. A significant difference was found between the development of expressive language skills. Children with familial risk of dyslexia and slow motor development had a smaller vocabulary with poorer inflectional skills than the other children. They were also slower in their reading speed at the end of the first grade at the age of 7 years. Two different associations are discussed, namely the connection between early motor development and language development, and the connection between early motor development and reading speed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".