Mathematical Abilities in Children With Developmental Language Disorder
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose This review article provides a scoping review of the literature on mathematical abilities in developmental language disorder (DLD). Children with DLD typically struggle with learning in school; however, the mechanism by which DLD impacts academic success is unclear. Mathematics involves demands in the multiple domains and therefore holds potential for examining the relationship between language and academic performance on tasks mediated by verbal and nonverbal demands. Method A scoping review was performed via computerized database searching to examine literature on mathematics and DLD. The 21 review articles meeting inclusion criteria compared children with typical development or DLD on various tasks measuring numerical cognition. Results Children with DLD consistently performed below peers with typical development on number transcoding, counting, arithmetic, and story problem tasks. However, performance was similar to peers with typical development on most number line, magnitude comparison, and conceptual mathematics tasks. Conclusions The findings suggest a relationship between DLD and mathematics was characterized by more detrimental performance on tasks with higher verbal demands. Results are discussed with respect to typical academic curricula and demonstrate a need for early identification and intervention in DLD to optimize academic outcomes.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it