Rethinking the ‘Fit’ in Fitness: Misfitting (Loudly) to Transform Physical Activity Futures
Bibliographic record
Abstract
The fitness industry has long glorified an “ideal body.” Anyone not “fitting” this ideal is cast as non-normative, and likely excluded, discriminated against, and pressured to conform to mythical standards. Using the feminist materialist concept of misfitting in our narrative thematic analysis, we thought through 22 participants’ stories of in/exclusion in the world of physical activity and fitness. Participants recognized being a misfit (noun) in juxtaposition to the white-able masculine standard. They also discussed how the norm is enforced, including stories of punitive exercise, fear of judgment, and performative worth(iness). Choreographing misfitting shares participants’ responses to being a misfit, via choreographing invisibility (by avoidance or seeking to mask/pass) and choreographing visibility (to expose unrealistic standards of normativity by misfitting (verb) loudly). We argue that misfits must always be centered and celebrated for teaching us how physical activity and fitness can and should be inclusive for all.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".