Women's knowledge in Madagascar: A health needs assessment study
Bibliographic record
Abstract
Nutritional and hygienic practices contribute to high morbidity and mortality rates related to malnutrition in Madagascar. This study, a research effort that brought together charitable organisations, non-governmental organisations (NGOs) and university collaborators, investigates women's health knowledge in the Anosy region of Madagascar. The needs assessment sought to characterise women's knowledge and understanding of nutrition and hygiene. Eight focus groups of 13-60 women each were conducted in the seven most impoverished communes of the Anosy region (n=373). Participants were recruited with the aid of a UK-Malagasy partnered NGO, Azafady. Study findings show that women fully understand the interplay between poor nutrition, hygiene and malnutrition but are unable to change everyday practices because the barriers to better nutrition and hygiene seem beyond their control. These findings may be used to prioritise projects and research seeking to improve nutrition and hygiene, thus reducing malnutrition in the Anosy region.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".