Study on Access to Improved Source of Drinking Water in Rural Households of a Block in District Rohtak, Haryana
Bibliographic record
Abstract
Background: Access to improved source of drinking water in adequate quantity is one of the major challenges in India. Factors such as poor availability and distance between water source and home may lead households to depend on less safe sources leading to water related infections. Objective: To study access to improved source of drinking water in rural households in the study area Material and methods: This cross sectional study was undertaken among 250 randomly selected households in a rural block, for a period of two months. The response from a single person preferably head of the family regarding access to improved source of drinking water, washing hands before water collection and drawing, water purification practices and other details were collected. Results: The major source of water for the households was groundwater through hand pumps. Out of 250 households, 40 % did not have access to water within the household premises. Sixty two percent of households had water scarcity problem especially in summer months. Only 46 percent of the respondents reported washing hands before drawing water. Nearly 30 % of the respondents knew that boiling water helps to purify water. Conclusion: For most of the households, groundwater is the major source of water. In the present study, practices by villagers were favourable for contamination.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".