Quantitative Assessment of Handedness and Cerebral Lateralization
Bibliographic record
Abstract
Handedness is the most studied human asymmetry due to its connection to various lateralized behaviours and hence many studies have focused on developing a valid assessment. One of the most popular is the Edinburgh Handedness Inventory (EHI), however, its psychometric properties have been questioned and due to its complex response format, various modified versions of EHI are in use. One of them is a 7-item questionnaire produced by Dragovic and Milenkovic (2013), which seeks to reduce a potentially continuous variable to a categorical one by clearly classifying people as right- or left- handed. The purpose of this study was to develop a questionnaire to more accurately quantify mixed-handedness as a continuous variable, and to investigate the correlation between Dragovic’s modified 7-item EHI, new items created for this study, and three performance measures (grooved pegboard, finger-tapping and grip strength/dynamometer). A total of 113 self-reported right-, left- and mixed-handed participants were randomly recruited to complete the questionnaire and behavioural measures. The questionnaire data was submitted to exploratory factor analysis and resulting factor scores were examined for correlations with behavioural tests. Compared to the modified EHI, the questionnaire showed a more continuous grading of handedness. Moreover, the degree of handedness on the questionnaire showed a stronger correlation with all the performance measures than the performance measures had amongst themselves. These findings show that the novel questionnaire with modern-day items can provide an accurate estimate of the degree of mixed-handedness in both right- and left-handed individuals. Future studies should examine these measures on a larger sample of left-handed and ambidextrous people, who tend to be more variable than right-handers in their usage. The questionnaire can also be suitable for studying the relationship between variable handedness and other aspects of brain lateralization.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".