Certificación de productores ecológicos en SGP Lima: Reporte basado en la estrategia de la intervención piloto
Bibliographic record
Abstract
In 2022, Peru led the food insecurity table in South America, registering 16.6 million Peruvians in this situation, the most vulnerable families had to reduce their food intake to once a day. The Institute of Development and Environment – IDMA, in alliance with the International Potato Center – CIP, within the framework of the CGIAR research on "Resilient cities through sustainable urban and peri-urban agri-food systems", has been organizing the development of an awareness campaign for World Food Day, concerning the contribution provided by agroecological family farming located in the Valleys of Metropolitan Lima. The central part of this strategy was the forum: ”DIALOGUES ABOUT HEALTHY DIETS FOR EVERYONE, 3X7”; this space was creates with the purpose of dialogue and reflection in relation to healthy diets, where the roles that small farmers have been fulfilling for the generation of food were identified and highlighted. Likewise, the importance of common soup kitchens was highlighted to provide food in low-resource areas and how vegetable producers have been articulated, mainly at the level of urban agriculture to provide inputs for common soup kitchens.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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; both teacher heads agree on what is shown here.
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".