Bibliographic record
Abstract
This Major Research Paper explores the sporting environment and the impact certain sport spaces can have on lesbian, gay or bisexual athletes. Through an in-depth analysis of the literature, I explore how key scholars have critically examined themes of masculinity and femininity in sport. This was done in order to understand how coming out differs for athletes depending on their gender identity and the sport that they participate in. I engage with the theories of intersectionality, queer theory, ideology, cultural hegemony and gender performativity to enhance this analysis. I also developed original research by interviewing six male- and female-identifying athletes. Their experiences help explain why certain sporting environments are more or less accepting of sexual minorities in sports. This body of work is important because it provides readers with the opportunity to fully grasp and understand the hardships lesbian, gay and bisexual athletes endure in sports. Key Words: Team-Based Sports, Single-Person Sports, Sexuality, Gender, Intersectionality, Race, Class, Identity Politics, Queer Theory, Ideology, Hegemonic Masculinity, Orthodox Masculinity, Cultural Hegemony, and Gender Performativity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| 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".