Using Metaphors of Contagion: How Framing Obesity as ‘Epidemic’ Shapes Cultural and Medical Understandings of Noncommunicability and ‘Fatness’
Bibliographic record
Abstract
This paper explores the contestations regarding the use of the term ‘epidemic’ in obesity discourses. On one side, obesity studies are increasingly demonstrating links which suggest the condition is communicable, thus possibly warranting an ‘epidemic’ framework. On the other side–to which I position this paper–obesity remains understood as noncommunicable; therefore when the notion of ‘epidemic’ is employed, it is recognized to be metaphorical. Drawing on the works of critical scholars, this paper argues that the framing of obesity as ‘epidemic’ has more harmful consequences on prevailing cultural and medical understandings of fatness.
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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 | 0.021 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.010 | 0.091 |
| Scholarly communication | 0.014 | 0.022 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.006 | 0.008 |
| 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".