MétaCan
Menu
Back to cohort
Record W4411617910 · doi:10.1177/19408447251334614

Body-Mapping the Affective Politics of Bariatric Surgery

2025· article· en· W4411617910 on OpenAlex

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.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Review of Qualitative Research · 2025
Typearticle
Languageen
FieldHealth Professions
TopicObesity and Health Practices
Canadian institutionsUniversity of Guelph
FundersCanadian Institutes of Health ResearchCanada Research Chairs
KeywordsPoliticsMedicinePsychologyGeneral surgerySurgeryPolitical science

Abstract

fetched live from OpenAlex

Bariatric surgery (or weight loss surgery, WLS), an increasingly common intervention into "obesity," remains a contentious topic amongst obesity experts, critics, and fat activists. As part of a larger study employing a neomaterialist framework, we worked with four women who resided in Canada and had WLS a minimum of one year prior to create life-size body-maps representing their pre- and post-surgical experiences. As a method, body-mapping can bring attention to somatic, embodied, and affective elements, uncovering structures of feeling informing/shaping WLS experiences. We used an affective analytic approach to make sense of the body-maps, which we present according to three affective strands: shades of gray, sensorial-cognitive relationalities with food and body, and entanglements of anticipated and unruly sensations and affects. Body-maps highlight the affective politics that are set into motion by, and set into motion, WLS and the hegemonic discourses and unruly affects that emerged.

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)0.038
metaresearch head score (Gemma)0.045
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Insufficient payload (model declined to judge)
Consensus categoriesMetaresearch
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.714
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0380.045
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.580
GPT teacher head0.710
Teacher spread0.130 · 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