Fatphobia as a form of gender-based violence: Fat women, public space and body belonging work
Bibliographic record
Abstract
In this article, we propose bringing together theoretical frameworks from fat studies and research into street harassment, as a form of gendered violence, to provide a novel lens for thinking about fat women’s experiences of public space. By focusing on the gendered politics of public space itself, we show how fears of fat-based and gender-based street harassment and abuse work together to create a complex sense of “non-belonging” for fat women. Coupled with primary interview data gathered from twenty-one self-defined fat women, our approach brings together theoretical frameworks from fat studies and research into street harassment to provide a novel lens for thinking about fat women’s experiences of public space. Specifically, we identify and explore points of confluence where experiences of fatphobia and street harassment mirror each other – exclusion from public space, intrusion as a means of policing non-belonging bodies, and what we call body belonging work as an active process of accomplishing belonging. We suggest that current policy attention to gender-based violence represents a timely moment to address the intersectional nature of women’s experiences.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.029 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.010 |
| Research integrity | 0.002 | 0.003 |
| 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".