Nutrition Promotion and Collective Vegetable Gardening by Adolescent Girls: Feasibility Assessment from a Pilot in Afghanistan
Bibliographic record
Abstract
This study aimed to assess the feasibility of collective vegetable gardening into an existing development programme for adolescent girls as a means of improving awareness about health and nutrition and increasing vegetable consumption in Afghanistan. A one and half year pilot study tested the feasibility of layering an intervention that combined agricultural training and input support in Kabul, Parwan and Kapisa regions on an adolescent programme implemented by a non-government organisation. The study included 400 adolescent girls for survey and qualitative tools to understand the local context of adolescent girls' participation in vegetable cultivation. The assessment demonstrates the evidence that despite of the challenging situation and traditional culture in Afghanistan the pilot had successfully engaged almost all of the adolescent girls in collective vegetables cultivation by making them aware about health, nutrition and the usefulness of vegetables consumption while the bad effects of not intake those. And the cultivation proved itself financially viable and very much effective for the community though there were little challenges. The pilot would be feasible and scalable to address the malnutrition and girls' marginalization if those challenges were taken into consideration carefully.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".