The effect of the 2D:4D ratio on right and left hand performance for two versions of the grooved pegboard task
Bibliographic record
Abstract
Digit ratio (2D:4D) between the second and fourth digit has been suggested to correlate to hand preference and prenatal testosterone (Honekopp et al., 2007). The purpose of the current study was to examine right and left digit ratios with their respective performance on two versions of the Grooved Pegboard task. We hypothesized that the hand with higher 2D:4D ratios (i.e. longer index finger) would better perform in the more complex pegboard task and reflect a preferential-hand advantage. Participants completed two versions of the Grooved Pegboard task; the standard pegboard (i.e. more complex task) and a pegboard 2.5 times the size of the original. Participants were required to perform two tasks on each pegboard: place the 25 key-shaped pegs in the oriented holes and remove the pegs from the holes. A digital caliper was then used to measure finger length from the proximal basal crease to the tip. Hand ‘deftness’ or dexterity is typically related to larger digit ratios, with the more dexterous hand being preferred (Manning et al, 2000) coinciding with recent research between hands, revealing that a larger right hand digit ratio relative to the left hand suggests a greater preference for the right hand and vice versa (Beaton et al., 2011; Manning & Peters, 2009). Digit ratios were expected to differ significantly between genders with males showing lower ratios for each hand. Larger ratios found in females may explain a sex advantage in fine motor skills, although this could be attributed to finger diameter (Peters & Campagnaro, 1996). The first age group (4-8 years old) of 30 children was recently collected. Trends reveal that similar ratios between the hands exist, and right and left hand performance is comparable. Furthermore, participants with larger 2D:4D ratios in their right hand show a greater preferred-hand advantage in pegboard performance.
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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 | 0.000 | 0.000 |
| 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) | 0.000 | 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".