Factors affecting athletic ability: The 2D:4D ratio analyzed
Bibliographic record
Abstract
The second to fourth digit ratio is considered a sexually dimorphic trait with lower finger ratios being linked to increased levels of masculinity (Griffin, Kennedy, Jones, & Barber, 2012). Therefore, a reason for researching the ratio is its probable link to genetic foetal testosterone levels (Manning, et al., 2014). Males and females with lower 2D:4D ratios have been shown to display greater amounts of physical fitness and athletic ability (Hönekopp, Manning, & Müller, 2006; Bailey, & Hurd, 2005). In the current research study we set out to analyze how genetics, measuring the 2D:4D ratio, may influence athletic ability in University students (expert, recreational and non-athletes). We hypothesized that much like results found specifically by Giffin et al. in 2012 that expert level athletes would display the smallest 2D:4D ratios in comparison to recreational and non-athletes. We also hypothesized that males would display a smaller ratio than females given increased levels of foetal testosterone levels. 87 young adults from Wilfrid Laurier University were administered two questionnaires; one being the Waterloo Handedness Questionnaire, and another being the deliberate practice questionnaire. The latter was developed specifically for this study to determine the level of athletic expertise through deliberate practice (Ericsson, 2006). Lastly, 2D:4D measurements were taken from the preferred hand of each participant directly using a vernier caliper. Our results showed that not considering gender, expert level athletes had significantly smaller 2D:4D ratios than recreational athletes and non-athletes. Only at the recreational level were there significant differences between genders. A negative correlation existed between 2D:4D ratios between all athlete groups for males. In contrast, significant differences were only found in the expert level athlete group among females, while no significant differences were found between non-athletes and recreational level athletes.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".