Comparing language profiles: children with specific language impairment and developmental coordination disorder
Bibliographic record
Abstract
BACKGROUND: Although it is widely recognized that substantial heterogeneity exists in the cognitive profiles of children with Developmental Coordination Disorder (DCD), very little is known about the language skills of this group. AIMS: To compare the language abilities of children with DCD with a group whose language impairment has been well described: children with Specific Language Impairment (SLI). METHODS & PROCEDURES: Eleven children with DCD and 11 with SLI completed standardized and non-standardized assessments of vocabulary, grammatical skill, non-word repetition, sentence recall, story retelling, and articulation rate. Performance on the non-standardized measures was compared with a group of typically developing children of the same age. OUTCOMES & RESULTS: Children with DCD were impaired on tasks involving verbal recall and story retelling. Almost half of those in the DCD group performed similarly to the children with SLI over several expressive language measures, while 18% had deficits in non-word repetition and story retelling only. Poor non-word repetition was observed for both the DCD and the SLI groups. The articulation rate of the children with SLI was slower than that of the DCD group, which was slower than that of typically developing children. CONCLUSIONS: Language impairment is a common co-occurring condition in DCD. The language profile of children with either DCD or SLI was similar in the majority of, but not all, cases.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".