Mothers' talk to children with Down Syndrome, language impairment, or typical development about familiar and unfamiliar nouns and verbs
Bibliographic record
Abstract
This study investigated how forty-six mothers modified their talk about familiar and unfamiliar nouns and verbs when interacting with their children with Down Syndrome (DS), language impairment (LI), or typical development (TD). Children (MLUs < 2·7) were group-matched on expressive vocabulary size. Mother-child dyads were recorded playing with toy animals (noun task) and action boxes (verb task). Mothers of children with DS used shorter utterances and more verb labels in salient positions than the other two groups. All mothers produced unfamiliar target nouns in short utterances, in utterance-final position, and with the referent perceptually available. Mothers also talked more about familiar nouns and verbs and labelled them more often and more consistently. These findings suggest that mothers of children in the early period of language development fine-tune their input in ways that reflect their children's vocabulary knowledge, but do so differently for nouns and verbs.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".