Effects of maintaining and redirecting infant attention on the production of referential communication in infants with and without Down syndrome
Bibliographic record
Abstract
The effects of maternal interactive styles on the production of referential communication were assessed in four groups of infants whose chronological ages ranged between 0;6 and 1;8. Two groups of infants with Down syndrome (DS), one (n = 11) with a mean mental age (MA) of 0;8.6, and the other (n = 11) of 1;4.5, were matched on MA with two groups (n = 10 each) of typically developing infants. Infants were seen bi-monthly, for 8 months, with mothers, same-aged peers, and mothers of the peers. Results showed that High MA non-Down syndrome (ND) infants produced more words, and High MA DS infants produced more gestures when playing with mothers than peers. Mothers exhibited more attentional maintaining behaviours than peers, in particular to High MA infants, but they redirected the attentional focus of Low MA infants more. Sequential loglinear analyses revealed interesting contingencies between the interactive strategies of mothers and the referential communicative behaviours of their infants. Whereas maintaining attention increased, redirecting attention decreased the likelihood of the production of gestures and words in children. However, redirecting attention was followed by maintaining attention. Thus, mothers redirect the attentional focus in order to promote joint attention and referential communication. Furthermore, words and gestures of the children also promote joint attention in mothers. This highlights the reciprocal nature of these dynamic communicative interactions.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".