Impact of an enhanced homestead food production program on household food production and dietary intake of women aged 15-49 years and children aged 6-59 months: a pragmatic delayed cluster randomized control trial protocol
Bibliographic record
Abstract
Background: Undernutrition remains a public health problem in Cambodia. To address this, Helen Keller International has implemented an enhanced homestead food production (EHFP) program that provides agricultural inputs and, nutrition, hygiene, and gender empowerment training. This research evaluates the impact of EHFP on dietary intake of women and children and, household food production. Methods: This two-year pragmatic delayed cluster randomized controlled trial will be conducted in 600 households in Kampot, Cambodia. Half the households will be randomly assigned to the intervention group and administered the EHFP program immediately. The remaining households (control) will be delayed for one year after which they will receive EHFP. In year one in the control group and year two in the intervention group, household data on food production and income generation will be collected using monthly surveys and, dietary data will be collected using 24-hour recalls from women 15-49 years and children 6-59 months twice during the year. Primary outcomes are differences between the treatment groups in mean intake of zinc and vitamin A among women and children. Secondary outcomes are differences between the treatment groups for other key nutrients and the incremental net monetary benefit of EHFP. Additional outcomes including household food security, women’s empowerment, and hygiene practices from larger project data will also be assessed. Conclusions: The results of this trial will assess the impact of EHFP on household food production and the dietary intake of women and children.
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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 | 0.010 | 0.010 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.043 | 0.004 |
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".