Hand Preference in Children’s Referential Gestures During Storytelling: Testing for Effects of Bilingualism, Language Ability, Age, and Sex
Bibliographic record
Abstract
Adults, preschool children, and infants gesture more with their right hand than with their left hand. Since gestures and speech are related in production, it is possible that this right-hand preference reflects left-hemisphere lateralization for gestures and speech. The primary purpose of the present study was to test if children between the ages of 6 and 10 years show a right-hand preference in referential gestures while telling a story. We also tested four predictors of children’s degree of right-hand preference: 1) bilingualism, 2) language proficiency, 3) age, and 4) sex. Previous studies have shown that these variables are related to the degree of speech lateralization. Twenty-five English monolingual (17 girls; M age = 8.0, SD age = 1.4), 21 French monolingual (12 girls; M age = 7.3, SD age = 1.4,) and 25 French-English bilingual (11 girls; M age = 8.5, SD age = 1.4) children watched a cartoon and told the story back. The bilinguals did this once in each language. The referential gestures were coded for handedness. Most of the participants showed a right-hand preference for gesturing. In English, none of the predictor variables was clearly related to right-hand preference. In French, the monolinguals showed a stronger right-hand preference than the bilinguals. These inconsistent findings across languages raise doubts as to whether the right-hand preference is linked to lateralization for speech.
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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 | 0.003 |
| 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) | 0.002 | 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".