Psychosocial stressors related to extreme weather events and multiple resource insecurities: qualitative insights from refugee youth in an Ugandan humanitarian setting
Bibliographic record
Abstract
Extreme weather events (EWE) contribute to heightened psychosocial stressors through complex pathways, including by worsening resource insecurities. Refugee settlements globally are disproportionately exposed to EWE compared with host national populations, yet refugees' experiences of resource insecurity-related psychosocial stressors in low-income humanitarian settings are understudied. Our study focused on understanding the lived experiences of psychosocial stressors in the context of EWE and resource insecurity among refugee youth in Bidi Bidi Refugee Settlement, Uganda. This qualitative study involved 32 walk-along interviews with a purposive sample of refugee youth aged 16-24 (16 men, 16 women); youth led the interviewer to 1-3 places where they obtained food, water, and/or sanitation resources, discussed the place's meaning and impact on wellbeing, and took photos. We also conducted 12 in-depth interviews with key informants with expertise in refugee youth wellbeing, EWE, and/or resource security. We conducted framework thematic analysis informed by resource scarcity and water insecurity-related distress frameworks. Participant narratives reflected four key themes regarding linkages between EWE, resource insecurities, and psychosocial distress: 1) material deprivation and uncertainty (sub-themes: drought-related food and water insecurity; flooding-related infrastructure and agricultural damage); 2) shame of social failure (sub-themes: sanitation insecurity stressors; unemployment and food insecurity distress and related substance use); 3) interpersonal conflict, including multi-level violence (sub-themes: increased violence; concerns about crime and theft); and 4) coping and asset management strategies (sub-themes: social and economic infrastructure; social capital; household relations). Together findings suggest the need for integrating psychosocial support within social and economic opportunities and poverty reduction with refugee youth.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".