Demonstration gardens improve agricultural production, food security and preschool child diets in subsistence farming communities in Panama
Bibliographic record
Abstract
OBJECTIVES: To explore impacts of a demonstration garden-based agricultural intervention on agricultural knowledge, practices and production, food security and preschool child diet diversity of subsistence farming households. DESIGN: Observational study of households new to the intervention or participating for 1 or 5 years. Variables measured were agricultural techniques learned from the intervention and used, agricultural production, household food insecurity (FIS) and child diet diversity (DDS), over one agricultural cycle (during land preparation, growing and harvest months). SETTING: Fifteen rural subsistence farming communities in Panama. PARTICIPANTS: Households participating in intervention (n 237) with minimum one preschool child. RESULTS: After 1 year, participants had more learned and applied techniques, more staple crops produced and lower FIS and higher DDS during land preparation and growing months compared with those new to the intervention. After 5 years, participants grew more maize, chickens and types of crops and had higher DDS during growing months and, where demonstration gardens persisted, used more learned techniques and children ate more vitamin A-rich foods. Variables associated with DDS varied seasonally: during land preparation, higher DDS was associated with higher household durable asset-based wealth; during growing months, with greater diversity of vegetables planted and lower FIS; during harvest, with older caregivers, caregivers working less in agriculture, more diverse crops and receiving food from demonstration gardens. CONCLUSIONS: The intervention improved food production, food security and diets. Sustained demonstration gardens were important for continued use of new agricultural techniques and improved diets.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".