Ghanaian caregivers’ opinions on feeding 2‐ to 5‐year old children varies by agro‐ecological zone
Bibliographic record
Abstract
Childhood malnutrition is high in Sub‐Saharan Africa. Knowing caregivers’ opinions about feeding children may aid in designing effective nutrition interventions. Data on caregiver feeding opinions, and diets of 2‐ to 5‐y‐old children were collected from 608 caregivers living in three ecological zones (EZ) of Ghana. This analysis compared caregivers’ feeding opinions across three ecological zones. About 27.8% of caregivers believed that their children needed to be fed only 2 to 3 times/d. Reasons for adult supervision during child meal times, feeding diverse foods, and prioritizing a child to receive animal source foods (ASF), and the perceived child benefits of ASF differed across EZ (P<0.001). Caregivers’ opinions in agreement with recommended child feeding practices were scored as good opinion otherwise their opinion scored as poor. Children of caregivers with good feeding opinion scores consumed more diverse ASF compared to those of caregivers with poor opinions (5.0 ± 2.1 vs. 4.6 ± 2.1; P=0.026). Age and education of caregivers positively predicted better feeding opinions (P<0.01); living in the Guinea Savannah ecological zone was associated with poor feeding opinions. A key component to improving child nutrition is to understand the opinions held by caregivers in order to address them adequately within the specific locale of the caregiver and child. Support: GL‐CRSP, funded in part by US‐AID, PCE‐G‐00–98
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".