Applying a food processing-based classification system to a food guide: a qualitative analysis of the Brazilian experience
Bibliographic record
Abstract
OBJECTIVE: The present paper aimed to identify the stakeholders, as well as their arguments and recommendations, in the debate on the application of a food processing-based classification system to the new Brazilian Food Guide. DESIGN: Qualitative approach; an analysis was made of documents resulting from the consultation conducted for the development of the new Brazilian Food Guide, which uses the NOVA classification for its dietary recommendations. A thematic matrix was constructed and the resulting themes represented the main points for discussion raised during the consultation. SETTING: Brazil. SUBJECTS: Actors from academia, government and associations/unions/professional bodies/organizations related to the area of nutrition and food security; non-profit institutions linked to consumer interests and civil society organizations; organizations, associations and food unions linked to the food industry; and individuals. RESULTS: Four themes were identified: (i) conflicting paradigms; (ii) different perceptions about the role and need of individuals; (iii) we want more from the new food guide; and (iv) a sustainable guide. CONCLUSIONS: There was extensive participation from different sectors of society. The debate generated by the consultation revealed two main conflicting opinions: a view aligned with the interests of the food industry and a view of healthy eating which serves the interests of the population. The first group was against the adoption of a food processing-based classification system in a public policy such as the new Brazilian Food Guide. The second group, although mostly agreeing with the new food guide, argued that it failed to address some important issues related to the food and nutrition agenda in Brazil.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".