Seasonal variation of food security among the Batwa of Kanungu, Uganda
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Climate change is projected to increase the burden of food insecurity (FI) globally, particularly among populations that depend on subsistence agriculture. The impacts of climate change will have disproportionate effects on populations with higher existing vulnerability. Indigenous people consistently experience higher levels of FI than their non-Indigenous counterparts and are more likely to be dependent upon land-based resources. The present study aimed to understand the sensitivity of the food system of an Indigenous African population, the Batwa of Kanungu District, Uganda, to seasonal variation. DESIGN: A concurrent, mixed methods (quantitative and qualitative) design was used. Six cross-sectional retrospective surveys, conducted between January 2013 and April 2014, provided quantitative data to examine the seasonal variation of self-reported household FI. This was complemented by qualitative data from focus group discussions and semi-structured interviews collected between June and August 2014. SETTING: Ten rural Indigenous communities in Kanungu District, Uganda. SUBJECTS: FI data were collected from 130 Indigenous Batwa Pygmy households. Qualitative methods involved Batwa community members, local key informants, health workers and governmental representatives. RESULTS: The dry season was associated with increased FI among the Batwa in the quantitative surveys and in the qualitative interviews. During the dry season, the majority of Batwa households reported greater difficulty in acquiring sufficient quantities and quality of food. However, the qualitative data indicated that the effect of seasonal variation on FI was modified by employment, wealth and community location. CONCLUSIONS: These findings highlight the role social factors play in mediating seasonal impacts on FI and support calls to treat climate associations with health outcomes as non-stationary and mediated by social sensitivity.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it