Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.026 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".