The bidirectional association between maternal speech and child characteristics
Bibliographic record
Abstract
Our aim was to assess whether infants influence the quantity and quality of their mothers' speech to them and, in turn, whether this maternal speech influences children's later language. As 189 mothers interacted with each of their twins at age 0;5, we calculated the number of utterances, the proportion of sensitive utterances, and the proportion of self-repeated utterances they produced. We later assessed the twins' language comprehension and production when they were 1;6, 2;6, and 5;2. Quantity of maternal speech predicted child language at 5;2, whereas sensitivity predicted child language at 2;6 and 5;2 and partial self-repetition predicted child language at 1;6. Conversely, sensitivity and partial self-repetition in maternal speech at 0;5 were associated with genetic factors from the child, indicating that infant characteristics influence the quality of maternal speech. Overall, our findings stress the importance of considering both directions in the association between maternal speech and child characteristics.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".