The Influence of Household Procurement Strategies on Food Intake and Nutritional Status of Pre-school Children in Rural Western Kenya
Bibliographic record
Abstract
<p>A cross sectional survey design was set up to assess the influence of household procurement strategies on food intake and nutritional status of preschool children in from 196 households in Vihiga County, Kenya. Dietary diversity was positively correlated with food availability (p&lt;0.05). Increased consumption of bread and cereals, and, fruits and vegetables was influenced by food availability and food consumption (dietary diversity) (&lt;0.05). Roots and tubers, legumes and pulses, and carbonated drinks were the main contributors to food procurement strategies and availability (F= 3.419, F sig=0.02). Nutrition outcome was influenced by household socioeconomic status (R= 0.189, p value = 0.012) and income levels of households (R= 0.246, p value= 0.002), while procurement strategies had no effect on the nutritional status of the pre-school child. Household income levels determined food availability, diversity and intake.</p>
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".