Study on current community access to and practices on water, sanitation and hygiene in selected villages of Chargawa block, Gorakhpur, Uttar Pradesh, India
Bibliographic record
Abstract
Background: More than 90% of deaths from diarrhoea in under five children is caused by unsafe WASH practices. Adequate hygiene practices have been recognised to decrease the diarrhoeal incidence by 30–40 percent. 748 million people still depend on unimproved sources of drinking water almost a quarter of which depend on untreated surface water, and 2.5 billion people need to improve sanitation, including one billion who practice open defecation. Yet to date, the water, sanitation and hygiene (WASH) element has received minute attention and the potential to link efforts on WASH and NTDs has been mostly untouched. This study was planned to identify current levels of community access to and practices related to water, sanitation and hygiene facilities.Methods: Cross sectional survey of 200 households conducted in selected villages of chargawa block through multistage sampling. Data were collected using pre-designed questionnaire.Results: 66% of our responder’s were female, 86% of household are male-headed. The burden of collecting water is mostly with women & girls (89%). 51% of people still rely on the unprotected hand pump as a source of water for drinking. Majority of the population defecates in the bush/backyard/field (79%). Hand washing with soap and water during key times is practiced by 21% of the respondents, and hand washing with water only is practiced by 67%.Conclusions: The study shows that access to safe drinking water & WASH practices in the rural villages is still a big everyday challenge. This study provides baseline information’s for future interventions in this community.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".