On judgement day: Anorexic and obese women’s phenomenological experience of the body, food and eating
Bibliographic record
Abstract
In contemporary Western society, both anorexic and obese 1 bodies are regarded to be “out of bounds.” Although scholars have enhanced our understanding of anorexia and obesity, these “disorders” have most often been studied in isolation from one another. In this article, we examine the similarities and differences in the embodied experiences of anorexic and obese women. Informed by the phenomenological research tradition, we follow in the footsteps of other scholars who have already begun to depart from binarized, polarized views by describing how women living with anorexia and obesity in two Canadian provinces experience the body, food and eating. Anorexic and obese women described a vast range of intense emotional experiences to characterize their relationship to food, the body and eating. Shame marked the bodies of these women. Family relationships also changed how the women experienced the body and food over time. The women ascribed a diverse array of complex meanings to the body and food. We hope that our study opens new phenomenological terrain to dialogue with and for anorexic and obese bodies in a relational way, recognizing that both of these bodies hurt in a remarkably similar manner. In a judgement day of sorts, both anorexic and obese bodies carry the heavy burden of culture’s expectations to fit within a narrow range of normative slenderness.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.020 | 0.026 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".