Bibliographic record
Abstract
In the health-risk society, food choice is framed through public health nutrition and dietary risks which are produced through nutritionism and econutrition. Dietary guidelines recommend the consumption of functional foods to target bodily health (Scrinis 2013; Mudry 2010), whereas ecological nutrition pushes sustainable diets for planetary health (Mason & Lang 2017; Friedberg, 2016). These healthy eating discourses construct dietary food risks and reorient ideas about what constitutes good food and eating right. This paper explores how food risk discourses extend the moralizing of healthism through emerging public health nutrition discourses and the ‘new public health.’ I suggest that in considering what constitutes eating right, dietary health risks extend individual responsibility for bodily health to increasing responsibility for the health of our environment or ecosystems, exercised as choice over the foods one chooses to eat. The feminine-citizen-subject is particularly targeted because as Moore (2010) contends, hegemonic femininity is constructed through beliefs about health and the healthy body. Thinking through feminist intersectionality (Crenshaw, 1991) however, I draw attention to the limits of choice and individualized approaches to managing food risk given the structural constraints of food and health.
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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 | 0.013 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.095 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.006 | 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".