Articulation Speaks to Executive Function: An Investigation in 4- to 6-Year-Olds
Bibliographic record
Abstract
Executive function (EF) and language learning play a prominent role in early childhood development. Empirical research continues to point to a concurrent relation between these two faculties. What has been given little attention, however, is the association between EF and speech articulation abilities in children. This study investigated this relation in children aged 4-6 years. Significant correlations indicated that children with better EF [via parental report of the Behavior Rating Inventory of Executive Function (BRIEF) inventory] exhibited stronger speech sound production abilities in the articulation of the "s" and "sh" sounds. Furthermore, regression analyses revealed that the Global Executive Composite (GEC) of EF as measured by the BRIEF, served as a predictor for speech sound proficiency and that speech sound proficiency served as a predictor for the GEC. Together, these results demonstrate the imbricated nature of EF and speech sound production while bearing theoretical and practical implications. From a theoretical standpoint, the close link between EF and speech articulation may indicate a common ontogenetic pathway. From a practical perspective, the results suggest that children with speech difficulties could be at higher risk for EF deficits.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 0.001 |
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".