Big Persons, Small Voices: On Governance, Obesity, and the Narrative of the Failed Citizen
Bibliographic record
Abstract
This essay probes the connection between obesity and citizenship in Canada, outlining the ways in which the fat body or “failed body project” is equally positioned as that of the “failed citizen.” It examines how the personal body has been connected to that of the citizen, and traces the evolving narrative that explains why the ideal citizen is, literally and figuratively, a “fit” citizen. Contradictions emerge, because the figurative concept of citizen “fitness” is often mistakenly conflated with the visible look of leanness. The theoretical and practical implications of framing the larger body as a lesser citizen are then explored in light of these contradictions. Given that nearly 60% of adult Canadians—or 14 million people—are classified as overweight or obese, the framing of the fat body as the failed citizen is of considerable significance.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.048 | 0.085 |
| Scholarly communication | 0.016 | 0.006 |
| Open science | 0.002 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| 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".