Hand preference for unimanual and bimanual tasks: Evidence from questionnaires and preferential reaching
Bibliographic record
Abstract
The current research compared hand selection in a preferential reaching paradigm with unimanual (i.e., pick-up cup) and bimanual (pick-up cup and pour from pitcher) tasks. In addition, relationships between self-report, questionnaire-based hand preference (unimanual and bimanual) and patterns of hand selection were assessed. Data offer support for a division of labour between the hands in at the midline; however, bimanual selection otherwise reflects consideration of object proximity (i.e., location) and comfort (i.e., biomechanical constraints). When grasping cups in right space, the right-hand was used to stabilize the cup and left-hand to mobilize the pitcher, whereas the opposite pattern was observed in left-space. Unimanual hand selection was also driven by object location. Subsequent analyses revealed a relationship between unimanual measures, but not bimanual measures of hand preference. Overall, findings support the notion that questionnaire data are associated with hand preference for grasping to a certain extent; however, use of a comprehensive battery of assessments is recommended when assessing and/or predicting handedness.
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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 | 0.003 | 0.012 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".