Resilience in the Time of a Pandemic: Developing Public Policies for Ollas Comunes in Peru
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The coronavirus (Covid-19) pandemic has created economic, social, and food security crises in many countries throughout the world. Faced with growing hunger in Peru, and the government’s delayed and inadequate reaction, the most important response came from the citizens themselves, particularly the women, in the form of thousands of social care initiatives known as ollas comunes (literally ‘communal pots’, similar to soup kitchens, whereby local communities pool their resources to supply food for everyone in the neighbourhood). This article tells the parallel stories of the resurgence of these ollas comunes and the state-funded support initiatives, alongside the process followed by GRADE (Group for the Analysis of Development – Grupo de Análisis para el Desarrollo; a non-profit research centre founded in Peru) that enabled it to contribute to those institutions looking to improve access to food for the most vulnerable people. Both stories are underpinned by a common ability to adapt quickly, which is crucial for achieving objectives in uncertain and ever‑changing situations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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 it