Preferential reaching across regions of hemispace in adults and children
Bibliographic record
Abstract
The purpose of the current study was to examine hand selection during reaching in children utilizing a developmental version of the preferential reaching paradigm (Bryden, Pryde, & Roy, 2000). A cross-sectional sample of eighty right-handed participants (ranging in age from 3 to 20 years) were asked to reach to objects located in different regions of hemispace. Each participant was asked to carry out two different actions, varying in degree of complexity, on the objects while the experimenter observed, which hand was used to perform each of the tasks. A repeated-measures ANOVA revealed that reaching towards the midline and ipsilateral positions in hemispace resulted in significantly more preferred hand reaches than reaching towards contralateral hemispace, regardless of age and task. With respect to age group effects, it was found that the 6 and 7 year olds and the 9 and 10 year olds relied heavily on their preferred hand to perform the task, indicating that hand selection in these children was driven primarily by motor dominance. In comparison, the youngest children and adults used their nonpreferred hand more frequently in contralateral space, indicating that object proximity cues or a hemispheric bias was driving hand selection. The implications of these findings for understanding hand preference and skill were discussed in terms of motor dominance versus spatial reasoning theory of hand selection in unimanual reaching.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".