Sex Difference in Female and Male Ice Swimmers for Different Strokes and Water Categories Over Short and Middle Distances: A Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Winter swimming developed from a national tradition into a health-improving sport with international competitions. The difference in performance between women and men was thoroughly examined in various sporting disciplines; however, there is little data on winter swimming events. Therefore, this study aims to compare the sex differences in female and male winter swimmers for a distinct stroke over distances of 25 m and 200 m in ice water, freezing water and cold water in the multiple stages of the Winter Swimming World Cup, hosted by the International Winter Swimming Association (IWSA) since 2016. METHODS: All data included in this study were obtained from the official results of the Winter Swimming World Cup, published on the "International Winter Swimming Association" (IWSA) website. The Mann-Whitney U test was used to compare race time between sexes in different swimming strokes and categories of water. In contrast, the Kruskal-Wallis H test was used to compare differences between swimming strokes or water categories for the same sex. RESULTS: For 25 m and 200 m events of the "IWSA World Cup," male athletes were faster than female athletes, regardless of stroke and water temperature category. However, the effect size of the difference between the sexes was greater in 25 m than in 200 m for all strokes and water temperatures. Swimming speed for the same-sex differed between the swimming stroke in relation to the water temperature category. Head-up breaststroke was found to be the slowest stroke (p < 0.05). CONCLUSION: In water temperatures between - 2° and + 9 °C, men were faster than women in all stages of the "IWSA World Cup," regardless of the swimming stroke, but the effect size of the difference between the sexes was greater in shorter than in longer events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".