Pathways From Early Vocabulary to School‐Age Social Skills: Findings From a Large Prospective Cohort Study
Bibliographic record
Abstract
This study investigated developmental pathways between early language and later social skills in a large, prospective cohort consisting of 3387 mother-child dyads. Mediational pathways were examined between parent-reported expressive language (at 2 years of age) and social skills (at 8 years of age), via core language and pragmatic language (at 5 years of age). The analyses accounted for biological and environmental factors known to be associated with language development (i.e., child sex at birth, child birthweight, family income, mother's level of education, primary language spoken in the home, and perinatal health factors). Results indicated that pragmatic language, but not core language, acted as a significant partial mediator in the pathway of interest. These results support a developmental chain from early expressive language in toddlerhood to subsequent social skills in middle childhood via pragmatic language skills around school entry. Implications for theory and practice, and limitations are reviewed. SUMMARY: Using a large prospective cohort study, we investigated developmental pathways between early language at 2 years and social skills at 8 years. Pragmatic language at age 5, but not core language, acted a significant partial mediator in pathway of interest. These results support a developmental chain from early expressive language in toddlerhood to social skills in middle childhood via pragmatic language skills around school entry.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".