Sex And Gender Bias In Movement Competence And Confidence Across The Lifespan
Bibliographic record
Abstract
PURPOSE: It has been posited that movement behaviour variances that exist between males and females may not only be a result of biological sex, but also differences in gender treatment in movement contexts arising from differential expectations (gender bias) that may exist across the lifespan. This can be demonstrated in differences in injury rates (e.g., ACL), physical activity levels, and associated movement competencies. Persistence of bias and the competency/confidence connection is currently underexplored but a necessary component of physical literacy. As such, the purpose was to explore differences in movement competence and confidence throughout the lifespan to begin to understand potential sex and gender biases and the lifelong impact. METHODS: Using a PRISMA model, a systematic review search identified studies on sex differences in movement competence and movement confidence, based on searches in Pubmed, EBSCO and ProQuest databases. A random-effects meta-analysis examined the differences in competence and confidence in males and females across the lifespan, with significance set at p<0.05. RESULTS: Fifteen studies on movement competence (4554 participants) and 7 studies on movement confidence (1646 participants) were identified with data suitable for meta-analysis, with studies ranging from an average age of 1.5 to 64 years. There was a significant effect of sex differences (male>female) for both competence (pooled effect= -0.77; Z=-7.55; p<0.01- see figure) and confidence (pooled effect= -0.49; Z=-4.88; p<0.01), consistent with persistent lifespan effects. CONCLUSIONS: The demonstrated lifespan differences in competence and confidence from pre-pubertal to geriatric populations is disconcerting, and the origins of this may be arsing from gender bias, warranting further exploration. Based on physical literacy, the linkages between competence and confidence are a vehicle for exploring gender bias in various movement contexts.
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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 | 0.027 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.012 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".