Availability, Accessibility, and Diversity of The Highly Consumed Foods in A Rural Setting in Western Kenya
Bibliographic record
Abstract
Drift in the consumption of particular foods in a setting affects the pillars of food security. To avert the drift that results in adverse nutritional outcomes, there is a need to assess the consumption of highly consumed foods in a particular area for an evidence-based approach to policy formulation. This study was undertaken to determine access to food, own food production, market access, and consumption patterns of foods, as well as the diversity of highly consumed foods in rural areas of Western Kenya. The study employed a cross-sectional design incorporating purposive and multi-stage simple random sampling and was analyzed using Python software. The data was presented in tables and charts. From the results, 53.6% often have no food, 44.8% sometimes consume smaller meals, 43.8% sometimes were worried about food, 40% complained about the limited variety of food, and 39.3% sometimes consume fewer meals. Further, 81.2% of the respondents rely on farming for food, and 59.4% of the respondents access the market on foot, 26.6% by motorcycle, and 14.1% by bicycle. In addition, vegetables and grains were consumed an average of more than five times a week. The study shows the drift of food pillars with the diversity of vegetables, but not on grains. To address the drift, there is a need to improve the access and diversity of foods. The improved diversity of grains will compliment already existing diversified vegetables resulting into a good health outcome.
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.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".