(Un)Mapping trajectories of fatness: a critical account of fat studies’ origin story and the reproduction of fat (white) normativity
Bibliographic record
Abstract
Origin stories set the stage for the development of a field of study and are integral to the ways they grow and shift. Similar to other reclamation projects, fat studies aims to rewrite the history of ‘fat’ by subverting its violent use for surveillance and control, and positioning it as a natural human characteristic. Its origin story is inextricably linked to the activism and scholarship of white and white-passing women, and is often located in gendered expectations of the ‘appropriate’ feminine body. As a result, the racial origins and functionings of fatphobia become erased and create a normative fat subject that is typically cisgender, female and white, which is reproduced in much of the research emerging from the field. I, along with other fat activists and scholars, propose a fundamental shift towards an intersectional fat studies, with race as an entry point to analysis towards rewriting the field’s history and presence.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.015 | 0.064 |
| Scholarly communication | 0.013 | 0.013 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.004 | 0.008 |
| 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".