The effect of stereotype threat on men and women's athletic performance
Bibliographic record
Abstract
Stereotype threat occurs when performance suffers after an individual is reminded of negative stereotypes surrounding his or her in-group. In physical activity, women tend to be stereotyped as having poor musculoskeletal ability, but better cardiovascular endurance compared to men. The effect of stereotype threat on exercise performance has not been tested. The purpose of this study was to test the effects of stereotype threat on men and women's performance on an exercise task (jump squats) and to test theoretical moderators of performance (self-handicapping and athletic disengagement). Healthy young adults (N=142) completed a jump squat task in pairs after being exposed to one of three scenarios: (1) men are stronger and should outperform women (2) women have better aerobic capacity and should outperform men or (3) the task was related to recovery time and was not gendered in any way. There was no significant effect of condition on women's performance, and athletic disengagement was lower in the threat condition for women. Performance on the jump squat task was better in the threat condition for men. Men in the threat condition also displayed more self-handicapping and athletic disengagement. Self-handicapping and athletic disengagement were not significant moderators of the effects of condition on performance for either sex. These findings were not consistent with the hypotheses. These results suggest that gender stereotyping may be less relevant to women's athletic performance than literature suggests, and that gender stereotyping may motivate men towards improved performance.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".