The Relationship Between Language and Social Competence in 3- to 5-Year-Old Children at Risk of and Without Developmental Language Disorder
Bibliographic record
Abstract
Developmental language disorder (DLD) is associated with persistent language difficulties that may impact social competence. The aim of this study is to describe the relationship between language, pragmatics, and social competence in French-speaking preschoolers and to identify the specific social competence difficulties observed in children at risk of DLD at this age. The sample included 63 children aged between 36 and 59 months, 12 of whom were at risk of having DLD. Children were assessed using measures of vocabulary, morphosyntax, pragmatic skills, and narrative abilities, while childcare educators completed a questionnaire evaluating social competence. Results revealed that children at risk for DLD exhibited more characteristics related to dependence on adults compared to their peers without DLD. No significant group differences were observed for the other components of social competence. The findings also identified a relationship between pragmatic and personal narrative skills, and social adjustment. These findings support the social adaptation model, suggesting that functional social impacts in children with DLD may arise from limited language abilities rather than an intrinsic socio-emotional disorder. This study highlights the importance of early pragmatic and narrative development in supporting social competence from the preschool age.
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 | 0.004 |
| 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 | 0.001 | 0.001 |
| 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".