MétaCan
Menu
Back to cohort
Record W4417434512 · doi:10.32920/eb.v2i2.2324

Encounters of Care In and Outside of the Bodies-without-Organs

2025· article· W4417434512 on OpenAlexaff
Ramanpreet Annie Bahra

Bibliographic record

VenueExcessive Bodies A Journal of Artistic and Critical Fat Praxis and World Making · 2025
Typearticle
Language
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsYork University
Fundersnot available
KeywordsMateriality (auditing)IntersectionalityFraming (construction)BiopowerPhenomenology (philosophy)Politics

Abstract

fetched live from OpenAlex

This article develops a critical fat phenomenology rooted in the lived, fleshy, and affective experiences of being fat, racialized, and femme within uncaring structures of worldmaking. Drawing from fat studies, critical disability studies, and intersectionality theory as praxis, it interrogates how fatness is socially, politically, and medically constructed alongside race, gender, and coloniality. Fat racialized bodies are positioned within a continuum of “life-in-death,” subjected to biopolitical regulation through the medical-industrial complex, aesthetic norms, and the personal registry’s spatial-temporal logics. These interlocking systems uphold the thin, white, nondisabled, cisgender body as the artifact of full personhood, while framing fatness as pathology, spectacle, and failure. In response, this paper turns to Deleuze and Guattari’s concept of the “Body-without-Organs” (BwO) to reconceptualize fat materiality as non-prescriptive, relational, and generative. Through this lens, fat embodiment becomes a site of resistance and worldmaking, leaking beyond the confines of sizeism, shapeism, and whiteness, and affirming the potentialities of fat life beyond the coercive demands of thinness, health, and normativity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0140.053
Scholarly communication0.0090.011
Open science0.0010.015
Research integrity0.0030.009
Insufficient payload (model declined to judge)0.0040.000

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 head0.026
GPT teacher head0.407
Teacher spread0.381 · 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; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueExcessive Bodies A Journal of Artistic and Critical Fat Praxis and World MakingSame topicObesity and Health PracticesFrench-language works237,207