From “Healthy Eating” to a Holistic Approach to Current Food Environments
Bibliographic record
Abstract
The consumption of the industrial diet—characterized by highly processed, low-nutrient foods and the reduced intake of produce in its natural state, such as fruits and vegetables—is generating a large number of health and environmental concerns in the developed world. In the meantime, the public health response to food-related health issues typically focuses on healthy eating, despite the growing amount of research showing the complexity of food environments. In this article, we discuss the limitations and fragmented perspective of current “healthy eating” strategies and the obvious disconnect between public health interventions and broader food environments. We outline the transformation of food environments in recent decades and how this is shaped by shifting ways of life and forms of governance built on neoliberal principles, which in turn influence individuals’ food practices. By availing of critical social theory, we suggest that the potential for change should involve a systemic, ecological understanding of the complexities involved, exposing the interdependencies within broader socioeconomic, cultural, and political contexts and current food systems processes and environments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.068 |
| Scholarly communication | 0.009 | 0.010 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".