In the wake of canada’s violent eugenic legacies: An urgency to ReVision Fitness
Bibliographic record
Abstract
Eugenics is often misunderstood as a historical set of practices that mobilized outside of Canada and ended after World War II. Less is known about canada’s influence on and participation in the practices/ideologies/movement, and even less about how contemporary fitness practices continue to be tethered to eugenics. ReVisioning Fitness aims to counter/refuse eugenic-infused fitness regimes designed to eliminate ‘unfit’ people, by centring the lived experiences of trans, non-binary, queer, Black, racialized, disabled, and fat/thick/thicc/curvy people. We created three-to-five-minute multimedia videos that express our fitness-related experiences and inventiveness. We explore the concept of ‘inclusionism’ and critiques of current anti-racism rhetoric and reflect on our videos across three themes: complexities of racism and other markers of difference; politics of rest in leisure; and unsettling white supremacy in fitness. We call on fitness stakeholders to examine our/their implicatedness in upholding eugenic underpinnings of fitness as a call to action to refuse anti-life agendas.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.044 | 0.036 |
| Scholarly communication | 0.012 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.008 | 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".