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(Un)Mapping trajectories of fatness: a critical account of fat studies’ origin story and the reproduction of fat (white) normativity

2022· article· en· W4310992578 on OpenAlex
Samantha Zerafa

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCritical and Radical Social Work · 2022
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsScholarshipNormativeWhite (mutation)Gender studiesField (mathematics)ReproductionSociologyRace (biology)Political scienceBiologyMathematicsEcologyLawPure mathematics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.008
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.629
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0040.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.091
GPT teacher head0.442
Teacher spread0.351 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it