Bobbing and Weaving: A Nonbinary Boxer's Experiences of Sport, Gender and Resistance
Bibliographic record
Abstract
Abstract Even though trans and nonbinary athletes regularly experience oppression and exclusion in sport, many encounter sport as a site of gendered liberation. Most literature on trans and nonbinary athletes focuses on experiences of oppression; much less examines trans and nonbinary athlete resistance. Centring the voices of trans and nonbinary athletes in sport is essential for attending to the complexity of their experiences in sport. I draw on my own experiences as a nonbinary elite boxer to explore what is at stake in sport and demonstrate how sport can function as a site of joy and resistance for trans and nonbinary athletes. Amid ongoing debates about whether or not it is fair for trans women athletes to compete in sport, Gleaves and Lehrbach (2016) argued that sport does not solely concern who wins but also encompasses the ‘the stories we tell ourselves about ourselves’ in competitive sport. I argue that the stories we tell ourselves about ourselves in competitive sport stay with us for a lifetime. These stories shape how we make sense of ourselves and others. I explore how women, trans, and nonbinary boxers issue a threat to patriarchal cisheteronormative customs in boxing, precisely because we disrupt the assumption that aggression is the male domain and that masculinity equals cisgender maleness. I contribute to the growing body of literature centring trans and nonbinary voices by drawing attention to how trans and nonbinary athletes' experiences of sport are characterized not only by exclusion and oppression but also by joy and resistance.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.020 | 0.023 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".