Extreme weather events and refugee youths’ experiences of physical health in a Ugandan humanitarian setting: qualitative insights
Bibliographic record
Abstract
PURPOSE: Refugee settlements globally experience increased exposure to extreme weather events (EWE) compared with host national settings; however, refugee youth climate-related health experiences in humanitarian settings are understudied. We explored the lived experiences of climate change and EWE related to physical health among refugee youth aged 16-24 in a Ugandan refugee settlement. METHODS: We conducted a community-based, multi-method study. We purposively sampled refugee youth living in a Northern Ugandan refugee settlement reporting recent (past 14-day) EWE and/or resource insecurity. We conducted 32 refugee youth walk-along interviews to elicit a rich understanding of lived experiences in a target environment. During each interview, the youth brought the research assistant to places where they obtained resources (i.e. food, water, sanitation), took photos of their chosen places on a tablet, and described the photo and the place. We also conducted 12 in-depth interviews with key informants, comprising adults with experience working in this refugee settlement on refugee well-being, food security, water and sanitation hygiene (WASH), and/or climate change. We analysed the findings using template thematic analysis informed by the resource scarcity framework, which examines ecologic, social, and socioeconomic factors associated with resource insecurities. FINDINGS: = 12; mean age: 37.0, SD: 5.8; 75% men, 25% women). Participant narratives identified how flooding, heavy rain, and drought contributed to youth experiencing resource insecurities (food, water, sanitation), in turn increasing malnutrition risks, water-borne diseases, and risks of bodily harm. Flooding and heavy rains also contributed to vector-borne diseases, and drought to dehydration and hygiene-related infections. CONCLUSIONS: The findings highlight the need for better WASH infrastructure and increased food aid in Ugandan humanitarian settings, along with refugee youth-led initiatives to address the impacts of climate change on refugee well-being.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.007 |
| 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".