Feminist and Gender Research in Sport and Leisure Management: Understanding the Social–Cultural Nexus of Gender–Power Relations
Bibliographic record
Abstract
This article aims toward developing a critical theory that can further advance feminist research in sport management. I seek to offer a critical analysis of gender relations in sport and leisure management by developing a theoretical critique of gender (in)equity that integrates both social theory and cultural analyses. The original empirical data was gathered in a national study of Gender Equity in Leisure Management conducted by the author in 1998/99 and secondary data was drawn from comparative studies undertaken in Australia, New Zealand, Canada, and the U.S. (Aitchison, Brackenridge, & Jordan, 1999; Henderson & Bialeschki, 1993, 1995; Mckay, 1996; Shinew & Arnold, 1998). The research cited demonstrates that women’s experience of sport and leisure management is shaped by both structural and cultural factors. My findings highlight the need for new epistemological perspectives as much as new methodological approaches and techniques. This new perspective acknowledges the complexities of gender–power relations in the workplace and recognizes the interconnectedness and mutually informing nature of structural and cultural power, thus opening the way for more sophisticated analyses and understandings of gender equity in sport and leisure management.
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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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.007 | 0.039 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".