Fat bodies in space: explorations of an alternate narrative
Bibliographic record
Abstract
For far too long ‘obesity’ and healthcare have been inextricably linked, both forming and maintaining distinct narratives responsible for the “fear of fat” North American societies have embraced. Largely unrecognized, fatphobia now permeates individual and social consciousness and creates considerable harm broadly and within healthcare practice and policy. The following study seeks to unsettle the pathologization and binary views of weight and bodies to contribute to a building of a more socially just, intersectional system of care. Fat Bodies in Space is a qualitative study situated on the unceded lək̓ ʷəŋən territories and grounded in critical race, queer and decolonial perspectives. The disproportionate impacts of fatphobia in Canadian healthcare are discussed through the stories of five self-described fat individuals navigating their health in Victoria, British Columbia. Storywork, narrative and autoethnographic methods were part of the collection and analysis processes. Findings suggest a longstanding relationship between systemic inequities, social discourse and the treatment of fat individuals within health care systems.
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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 | 0.008 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.056 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".