Sex segregation in strength sports: Do equal‐sized muscles express the same levels of strength between sexes?
Bibliographic record
Abstract
OBJECTIVES: Concerns have been raised against the current two-sex binary category in sports competitions. The thesis states that if males and females were separated based on muscle size, it would negate the strength advantage between the sexes. We tested the possible sex differences in various strength outcomes when pair-matched for muscle thickness. METHODS: A total of 16 different data sets (n = 963) were assessed to pair-match females with males who had a muscle thickness value within 2%. We further compared the competition performances of the smallest male weight class within the International Powerlifting Federation (IPF) to different weight classes in females. RESULTS: Overall, 76%-88% of the strength assessments were greater in males than females with pair-matched muscle thickness, regardless of contraction types (i.e., isotonic, isometric, isokinetic). Additionally, males in the lightest weight division in the IPF largely outperformed females in heavier weight divisions. CONCLUSIONS: Our results would suggest that segregation based on muscle mass or surrogates of muscle mass (e.g., lean body mass) might not be an appropriate classification to create fair competition within strength sports. This is not to refute the concept of the desegregation of the two-sex binary category but to present data that raises important concerns about the potential sex-based differences in strength 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 | 0.001 | 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".