Strength and competitiveness are more strongly predictive of retrospective sport participation than 2D:4D in university-aged women
Bibliographic record
Abstract
Objective: Females continue to participate in sport at lower rates than males. Girls who participate in sport gain many advantages. Even with programs designed to emphasize participation, some females continue with sport participation while others do not. Given the advantages and controversies surrounding testosterone and female sport, it is possible that testosterone may predispose females toward sport participation. Our objective was to determine if the second to fourth digit (2D:4D) ratio, a proxy for prenatal androgen exposure, correlates with sport participation throughout female adolescence and young adulthood. Methods: A cross-sectional analysis of indirect prenatal androgen exposure (i.e., 2D:4D) was completed on 18–30-year-old women ( n = 92) using demographics, anthropometrics, sport-specific behaviour tendencies, and retrospective sport participation. Results: 2D:4D was not significantly correlated with total sport participation (TSP) ( r = −0.065, p = 0.538). Secondary analyses revealed significant correlations between TSP and maximum hand grip ( r = 0.406, p = 0.000) and the Sport Orientation Questionnaire (SOQcomp ( r = 0.513475, p = 0.000), SOQgoal ( r = 0.253, p = 0.015), SOQwin ( r = 0.366, p = 0.000)). Conclusion: Although strength and competitiveness are strongly correlated with female sport participation, the impact of prenatal androgen exposure (i.e., 2D:4D) remains to be determined given its weak and negative association with female sport participation. Given that females participate in sport at lower rates than males, continuing to determine what factors influence sport participation is an important goal.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".