Change in cost and affordability of a typical and nutritionally adequate diet among socio-economic groups in rural Nepal after the 2008 food price crisis
Bibliographic record
Abstract
Diet quality is an important determinant of nutrition and food security and access can be constrained by changes in food prices and affordability. Poverty, malnutrition, and food insecurity are high in Nepal and may have been aggravated by the 2008 food price crisis. To assess the potential impact of the food price crisis on the affordability of a nutritionally adequate diet in the rural plains of Nepal, data on consumption patterns and local food prices were used to construct typical food baskets, consumed by four different wealth groups in Dhanusha district in 2005 and 2008. A modelled diet designed to meet household requirements for energy and essential nutrients at minimum cost, was also constructed using the 'Cost of Diet' linear programming tool, developed by Save the Children. Between 2005 and 2008, the cost of the four typical food baskets increased by 19% - 26% and the cost of the nutritionally adequate modelled diet increased by 28%. Typical food baskets of all wealth groups were low in macro and micronutrients. Income data for the four wealth groups in 2005 and 2008 were used to assess diet affordability. The nutritionally adequate diet was not affordable for poorer households in both 2005 and 2008. Due to an increase in household income levels, the affordability scenario did not deteriorate further in 2008. Poverty constrained access to nutritionally adequate diets for rural households in Dhanusha, even before the 2008 food price crisis. Despite increased income in 2008, households remain financially unable to meet their nutritional requirements.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".