Under what conditions will right-handers use their left hand? The effects of object orientation, object location, arm position, and task complexity in preferential reaching
Bibliographic record
Abstract
When reaching to objects, it is known that the preferred hand is selected significantly more often for midline and ipsilateral reaches, although right-handers are more likely to continue to use their right hand to reach for an object in contralateral space (Mamolo, Roy, Rohr, & Bryden, 2006). The current study examined the influence of object orientation, object location, task complexity, and initial position of the hands on a reaching task in a sample of 45 right-handed adults. Participants reached to and picked up a mug oriented in one of three ways (handle to right, left, or neutral position) located in one of three spatial positions (left, right, and midline) from each of two starting hand positions: right hand over left, and vice versa. Along with the expected results, an interesting pattern emerged where both the orientation of the object and the position of the hands had significant effects on hand selection, such that the use of the non-preferred left hand was augmented in conditions where preferred-hand use was awkward and biomechanically inefficient. The results will be discussed in light of current theories accounting for hand selection preferences.
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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 | 0.004 |
| 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) | 0.002 | 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".