<b> <i>Nutrition Links</i> </b> – Building Capacity for Sustainable Lives in Ghana
Bibliographic record
Abstract
The Upper Manya Krobo District is an impoverished, underserved rural area in the Eastern region of Ghana. To improve the quality of services offered by district institutions and ameliorate the health and economic well‐being of vulnerable populations, we initiated a multi‐sector, 5‐y, district‐wide project “Nutrition Links”. An annual survey of all 1081 households with young infants provides information on health, nutrition, agriculture, and economic activities; this information is being used to develop project interventions and to support evidence‐based decisions of local institutions. At baseline, food insecurity affected more than half the population and was dispersed throughout the district. Over half of infants were anemic and about 11% were stunted and/or underweight. Diet diversity among infants > 6 mo was low. The project provides training on health, nutrition, agriculture, and finance to diverse stakeholders (from caregivers to program managers). Two interventions have been started: (1) intensive nutrition, health, and agricultural training with support for home gardens and poultry rearing among households with an infant; and (2) training on financial literacy and savings along with nutrition and health education for female school‐aged children (9 ‐ 13 y). This project is a working model for strengthening households, local institutions, and services for underserved rural communities in sub‐Saharan Africa. Funding: Government of Canada, through DFATD
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.017 | 0.001 |
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".