Use of a modified scoring of the Wathand Cabinet Test And Waterloo Handedness Questionnaire to measure hand preference in young adults
Bibliographic record
Abstract
Handedness can be assessed using preference, performance and observational measures. Handedness is multidimensional and thus the measurement tools should reflect this. The calculation of total scores when using handedness measures gives a picture of overall hand use however it does not give any indication of hand use within the various elements of the measure, such as differences between skilled and unskilled tasks. To further investigate the relationship of scores between and within measurement tools we modified the scoring of the Waterloo Handedness Questionnaire (WHQ) and the WatHand Cabinet Test (WHCT)(Bryden, Roy & Spence, 2007) to include total, skilled, unskilled, and bimanual scores. Young adults completed the WHQ, grooved pegboard (GP) and WHCT. Analysis showed that the total, skilled and bimanual scores between the WHQ and WHCT were positively correlated. No significant correlations were found between the WHQ and WHCT unskilled scores, suggesting that there were differences between the performance and self-report of unskilled tasks. Based on laterality quotients, participants over-reported the frequency they use their preferred hand. The GP skilled score positively correlated with the WHQ and WHCT skilled scores however the GP unskilled score did not correlate with the WHQ or WHCT unskilled scores. These findings support the view that handedness is multidimensional. The modified scoring of the WHQ and WHCT allows for a greater depth and understanding of handedness.Acknowledgments: Research support from NSERC (PJB) and FOSSA (AC)
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".