The link between maternal and child verbal abilities: An indirect effect through maternal responsiveness
Bibliographic record
Abstract
Language abilities in early childhood show stability over time and play an important role in the development of other cognitive processes. Identifying modifiable environmental risk factors is important to informing prevention and early intervention efforts. Maternal verbal ability has been previously linked to child verbal ability. The current study examined whether maternal and child verbal abilities were linked indirectly through early childhood maternal responsiveness. Data come from a longitudinal birth cohort study. Participants included 133 mothers and their children recruited from maternity wards shortly after birth. Maternal verbal ability was measured using the Vocabulary subtest from the Wechsler Abbreviated Scale of Intelligence, Second Edition (child age 8 months). Child verbal ability was assessed using the Peabody Picture Vocabulary Test (36 months). A latent maternal responsiveness variable was estimated using three developmentally sensitive indicators; one during infancy (child age 8 months) and two when children were 36 months. Results of a structural equation model indicated a significant indirect effect from maternal verbal abilities to child verbal abilities through maternal responsiveness. This indirect path was significant even after inclusion of another indirect path from maternal executive functioning to child verbal ability through maternal responsiveness (which was not significant). Future studies will benefit from experimental, genetically sensitive and/or cross-lagged designs to allow for conclusions related to directionality and causality. This body of research has implications for the study of the intergenerational transmission of verbal abilities and associated skills, behaviours and adaptive outcomes.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".