‘Mind Your Business and Leave My Rolls Alone’: A Case Study of Fat Black Women Runners’ Decolonial Resistance
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Black female body has been vilified, surveilled, and viewed as ‘obese’ and irresponsible for centuries in Western societies. For just as long, some Black women have resisted their mischaracterizations. Instead they have embraced a ‘fat’ identity. But little research has demonstrated how Black fat women participate in sport. The purpose of this study is to show how Black fat women who run use social media to unapologetically celebrate Blackness and fatness. This research uses a case-study approach to illuminate a broader phenomenon of decolonial resistance through running. In addition to analysis of websites, blogs, and news articles devoted to Black women’s running, we discuss the (social) media content of two specific runners: Mirna Valerio and Latoya Shauntay Snell. We performed a critical discourse analysis on 14 media offerings from the two runners, including websites, Twitter pages, and blogs collected over a five-month period from September 2020–January 2021. The analysis examined how they represent themselves and their communities and how they comment on issues of anti-fat bias, neoliberal capitalism, ableist sexism, and white supremacy, some of the pillars of colonialism. Whereas running is often positioned as a weight-loss-focused and white-dominated colonial project, through their very presence and use of strategic communication to amplify their experiences and build community, these runners show how being a Black fat female athlete is an act of decolonial resistance. This study offers a unique sporting example of how fat women challenge obesity discourses and cultural invisibility and how Black athletes communicate anti-racist, decolonial principles.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it