Analysis of sex and age differences in performance of young Canadian freestyle swimmers
Bibliographic record
Abstract
This study is intended to determine sex and age differences in young Canadian freestyle swimmers aged from ≤10 to 18, for all 6 distances from 50m to 1500m in both short and long course indoor pools. The data set used in the studies is publicly available and categorized into sex/age/course/distance groups during seasons from 2008 to 2019. The sex differences in swimming speed were determined using independent Z-tests (two-sided, unequal SD). The age differences in swimming speed over all ages were analysed using classic one-way ANOVA with subsequent pairwise Tukey-HSD post-hoc tests and Welch’s ANOVA followed by pairwise Games-Howell post-hoc tests. They were then determined using paired two-sample t-tests (two-sided). Young male swimmers outperformed young female swimmers in most groups. Groups with similar performances or no significant differences were in younger age groups (10-year and 11-year). Sex differences increased as age increased, ranging from −0.96% to 13.54%. Sex differences in shorter distances and short course were smaller than in longer distances and long course for ≤12 years and became greater than in longer distances at ≥13 years. Age speed differences decreased as age increased until 17–18-years old, ranging from 12.79% to −0.37%. The performance of female swimmers became stable earlier than that of male swimmers. The age-to-age speed differences of male swimmers were greater than those of female swimmers. These gaps increased from 10–11-year to 13–14-year groups and decreased after that. Age differences in shorter distances and short course were greater than in longer distances and long course. Further studies are required to confirm and extend this research to swimmers at other age groups, in other strokes, and from other countries.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".