Issues in access to safe drinking water and basic hygiene for persons with physical disabilities in rural Cambodia
Bibliographic record
Abstract
An estimated 1.6 million people die from diarrheal diseases each year due to lack of access to safe water and sanitation, and persons with physical disabilities face additional barriers. In Cambodia, approximately 5% of the population is disabled, presenting substantial obstacles in accessing these basic services. The purpose of this study was twofold: first, to identify the challenges facing persons with physical disabilities in accessing safe household water and basic hygiene in rural Cambodia; and, second, to use these results to generate policy and practice recommendations for the water and sanitation hygiene sector implementing water treatment system interventions in rural settings. Fifteen field interviews were conducted with persons with physical disabilities. Thematic analysis was used to identify six main themes. The results indicated that environmental barriers to access were greater in the workplace than household settings and those persons with disabilities had greater awareness about safe drinking water compared to basic hygiene. Additionally, lack of physical strength, distance to water, and lack of financial means were noted as common access barriers. The findings support ongoing research and offer insight into the particular challenges facing persons with physical disabilities in rural areas in accessing safe drinking water and basic hygiene.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".