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Record W1553280998 · doi:10.18061/dsq.v28i4.150

Resistance Training: Re-reading Fat Embodiment at a Women's Gym

2008· article· en· W1553280998 on OpenAlexaff
Margaret Shalma, Professor Rod Michalko

Bibliographic record

VenueDisability Studies Quarterly · 2008
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEmbodied cognitionNormativeOppressionReading (process)NormalityResistance (ecology)PsychologyAestheticsSociologyRepresentation (politics)Gender studiesSocial psychologyEpistemologyPoliticsLinguisticsArt

Abstract

fetched live from OpenAlex

This paper uses feminist disability studies to explore the discursive production of fat embodiment within contemporary Western society. I examine beauty and medicine as fields of knowledge which create and sustain bodily norms, representations and practices. Specifically, I examine the representation of women's (fat) embodiment through an analysis of the promotional material at a well-known women's gym. I show that this gym implicitly references wider health discourses to characterize fatness as pathology, thereby requiring intervention through physical fitness to return the body to normality. Through this analysis, I demonstrate that fatness is not a value neutral embodiment but is socially produced. By bringing together disability studies and fat studies, I highlight the importance of interdisciplinary dialogue, and reveal how different forms of oppression and discourse interlock to create normative understandings of embodiment. I argue that by re-reading fatness we can resist these normative demands and begin to imagine ways of desiring embodied difference.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.153
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.188
GPT teacher head0.461
Teacher spread0.273 · 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

Classification

machine, unvalidated

Machine predicted; both teacher heads agree on what is shown here.

Study designQualitative
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2008
Admission routes1
Has abstractyes

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