FIND YOUR FIT: RACIALIZED QUEER VOICES BUILDING STRENGTH ONE STORY AT A TIME
Bibliographic record
Abstract
Using qualitative narrative research, this study highlights the complex stories of queer and racialized individuals and their experiences in strength and conditioning spaces. Interviews informed by Intersectional Queer Black Feminist Thought uncovered how racialized queer participants, including business owners, face and resist systemic barriers while accessing colonial Western sporting and fitness spaces. Key findings show a toxic mindset continues to permeate fitness through heteronormative, racist, classist, ableist and sexist expectations placed on bodies to be a certain way. Participants’ narratives about their lived fitness experiences demonstrate that racial awareness, anti-colonial struggle, gender variance, and ways to ‘queer’ fitness must become priorities of the fitness industry. With the help of virtual tools, both fitness participants and fitness business owners continue to build their capacity and create their own spaces for racialized queer folks, and for those who are also interested in queering fitness by challenging heteronormative, racist, and neoliberal ways of being. Findings also uncovered what it means to be physically and mentally strong, as well as fit, from the participants' own queer racialized terms rather than from what the dominant culture considers acceptable. The insights gained from this research can contribute to a more comprehensive understanding of the complexities of diversity in sport and fitness at the scholarly level. Furthermore, by addressing the gap between theory and praxis, the findings can support policy decisions that impact trainer and professional development, business structures, and ultimately the current and future experiences of queer racialized individuals in health and fitness spaces.
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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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.041 | 0.040 |
| Scholarly communication | 0.016 | 0.017 |
| Open science | 0.003 | 0.016 |
| Research integrity | 0.005 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".