Bridging brains: exploring neurosexism and gendered stereotypes in a mindsport
Bibliographic record
Abstract
Ingrained gendered discourses about women’s abilities and skills impact on their participation in leisure and sport. This paper argues that gendered stereotyping extends to the serious leisure context of mindsport in the form of neurosexism. The card game bridge is played by a roughly equal proportion of men and women but at elite-level male players significantly outperform female players worldwide. Based on 52 semi-structured interviews, the paper explores the everyday gendered assumptions that exist and are reproduced by elite bridge players. Many of the research participants draw on ideas of male brains being more rational, logical and competitive whereas women’s brains are perceived to be more emotive, unfocused and uncompetitive. These gendered stereotypes are used to explain and defend why more women are not playing at elite level. Such neurosexist and behaviourist assumptions actively reproduce inequality within mindsport to the detriment of women bridge players. This article shows that neurosexism reinforces ongoing, systemic inequalities around gendered experiences of serious leisure, thereby reproducing gendered inequalities and hindering greater participation and inclusion in mindsport.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.014 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".