Mother‐child interactions in Canada and Italy: Linguistic responsiveness to late‐talking toddlers
Bibliographic record
Abstract
The aim was to examine cross-cultural variation in linguistic responsiveness to young children in 10 English-speaking mother-child dyads and 10 Italian-speaking mother-child dyads. All 20 children were late talkers who possessed delays in expressive vocabulary development but age-appropriate cognitive and receptive language skills. Dyads were filmed in 15-minute free play contexts, which were transcribed and coded for measures of maternal linguistic input (e.g. rate, MLU, labels, expansions) and child language productivity (e.g. utterances, different words used). The results revealed that the Italian mothers used more utterances, spoke more quickly and used a more diverse vocabulary than the Canadian mothers. The Italian children mirrored their mothers and also used more utterances and a more diverse vocabulary than the Canadian children. Mothers in both groups used similar percentages of responsive labels and expansions. However, Italian mothers responded to fewer of their children's vocalizations, using a smaller percentage of imitations and interpretations than the Canadian mothers. Correlations between maternal input and children's language productivity revealed that contingent language measures (e.g. imitations, interpretations, expansions) were related to high levels of productivity in children in both cultural groups. The results support the use of language interventions based on increasing maternal responsiveness for these children at the one-word stage of language development. They also point to differences that may be culturally based. For example, Italian mothers use faster rates of interaction and appear to have higher expectations for their children's verbal participation in interaction. This is reflected in higher rates of language production from their children, even though children in both cultural groups have similar vocabulary sizes.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".