A black dog enters the home: hunger and malnutrition in Malawi
Bibliographic record
Abstract
Hunger and inadequate nutrition are ongoing concerns in rural Malawi and are exemplified in traditional proverbs. Traditional proverbs and common expressions offer insight into commonly held truths across societies throughout sub-Saharan Africa. Strong oral traditions allow community beliefs embodied in proverbs to be passed down from generation to generation. In our qualitative study, we conducted 8 individual and 12 focus group interviews with a total of 83 participants across two districts in rural central Malawi with the aim of soliciting context-specific details on men and women's knowledge, attitudes and practices related to nutrition, gender equality and women's empowerment. Each interview began by asking participants to share common proverbs related to nutrition. Our qualitative analysis, informed by an indigenous-based theoretical framework that recognises and centres African indigenous knowledge production, yielded six themes: 'a black dog enters the home', 'don't stay with your hands hanging', 'a man is at the stomach', 'showers have fallen', 'we lack peace in our hearts' and 'the hunger season'. Traditional proverbs can provide insight into the underlying causes of hunger and malnutrition. Physicians, nurses and other allied health professionals around the world have a role to play in addressing hunger and malnutrition, which have been exacerbated by climate change. We have an ethical duty to educate ourselves and others, and change our behaviours, to mitigate the root causes of climate change, which are contributing to food insecurity and resultant poor health outcomes in countries like Malawi.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.011 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".