Investigating children and adults' hand selection tendencies in a motor planning task
Bibliographic record
Abstract
Left- and right-handers show stronger end-state comfort for the right-hand compared to the left-hand; therefore left-hemisphere dominance for motor planning has been suggested, regardless of hand preference (Janssen et al., 2011). This study aimed to assess hand selection during unimanual and bimanual tasks designed to analyze motor planning via end-state comfort. Typically-developing children (n = 92) and adults (n = 20) completed this study; 94 right- and 18 left-handers. Participants were asked to pick-up a cup and pour a glass of water and pick-up a cup and pass it to the research to pour a glass of water. Cup placement altered between right side up and inverted. The hand used to pick-up the cup was recorded using a video camera. Results revealed preferred hand selection to manipulate the pitcher and non-preferred hand selection to pick-up the cup; suggesting the pitcher requires the active, manipulating hand, while the cup has a more passive, supporting role. When only the cup was manipulated, preferred hand selection dominated. That said, regardless of the task, when manipulating the inverted cup, dominance in preferred hand-selection was further highlighted. Interestingly, left-handers showed an increase in right-hand selection when manipulating the inverted cup. Results will be discussed in light of current theories of motor control and motor planning involved in the development of hand preference.Acknowledgments: Research Support: Natural Sciences and Engineering Research Council of Canada (P.J.B)
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".