Hand preference in referential gestures: Relationships to accessing words for speaking in monolingual and bilingual children
Bibliographic record
Abstract
INTRODUCTION: Infants' right-hand preference for pointing is associated with higher vocabulary. It is not clear whether the link between right-hand preference for gesturing and language persists into the preschool years. The primary purpose of the present study was to test whether preschool children's hand preference for referential gestures was associated with their language abilities. Secondarily, we predicted that the children's right-hand preference would be negatively associated with their visuospatial abilities. We also predicted that monolingual children would show a strong right-hand preference while bilinguals might show a reduced right-hand preference. METHODS: Monolingual and bilingual children between the ages of four and six years did a storytelling task. Their referential gestures were coded for hand use (right, left, both). We measured language skills (receptive vocabulary, semantic fluency). RESULTS: We found no difference between bilinguals and monolinguals on hand preference. Semantic fluency was a positive predictor and vocabulary a negative predictor of right-hand preference. Children's visuospatial abilities were not a predictor of right-hand preference. CONCLUSION: These results suggest that right-hand preference may help children select semantically appropriate words out of their existing vocabulary. In other words, this preference may be related to children's construction of the message that they would like to produce. The association between hand preference and language skills persists into the preschool years.
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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 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".