Coping with water insecurity in urban Ghana: patterns, determinants and consequences
Bibliographic record
Abstract
Abstract In Sub-Saharan Africa (SSA), rapid urbanization poses unprecedented challenges in terms of water security and associated health risks. Like most SSA countries, many Ghanaian households lack access to safely managed drinking water sources and resort to a patchwork of alternative sources for their water needs. This paper examines determinants and implications of water insecurity coping strategies in resource-constrained neighborhoods in Ghana, using a survey (n = 1192) of adult active water collectors within households in Accra and Tamale. Findings suggest that water insecure households were more likely to adopt behavioral, physical and a mix of behavioral and physical coping strategies. Households were more likely to use behavioral (OR = 5.64, p = 0.00), physical (OR = 3.18, p = 0.00) and behavioral and physical (OR = 4.20, p = 0.00) coping strategies in the dry season. Compared with the wealthy, the less wealthy (OR = 0.27, p = 0.00) were less likely to employ a mix of physical and behavioral coping strategies. Likewise, males were less likely (OR = 0.64, p = 0.03) to employ a behavioral coping strategy. The findings can help practitioners identify vulnerable groups and provide targeted interventions that seek to build or strengthen coping strategies in the short term.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".