Is unimanual handedness related to the action hand or the supporting hand in a bimanual task
Bibliographic record
Abstract
Handedness is considered to be a relatively unique characteristic of humans. Typically, handedness is defined as the preferential use of one for most fine unimanual tasks, such as writing, hammering, and using a toothbrush. However, most everyday actions utilize both the preferred and non-preferred hands, with each assuming a particular role in the action. More specifically, consider the unimanual task of hammering: while the preferred clearly is the hand the non-preferred plays a supporting role in stabilizing the nail. Unfortunately, most preference questionnaires solely focus on the preferred and do not consider the role of the non-preferred hand. As such, we created a Bimanual Hand Preference Questionnaire and compared participants' performance on this new questionnaire to the Waterloo Handedness Questionnaire, a traditional measure of handedness. Fifty undergraduate Wilfrid Laurier University students completed both questionnaires, which assessed both direction and degree of handedness for various actions. Overall, the two measures were found to be significantly correlated. Hand preference as determined by the Waterloo Handedness Questionnaire was strongly positively correlated with the used to perform an action and strongly negatively correlated with the used for supporting actions. The findings indicate that the Bimanual Hand Preference Questionnaire is a valid tool, measuring a related construct to the Waterloo Handedness Questionnaire. Future research will next examine performance measures and how they relate to the Bimanual Hand Preference Questionnaire.Acknowledgments: Supported by NSERC (PJB)
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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 | 0.002 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".