Water Transfer from Peri-urban to Urban Areas
Bibliographic record
Abstract
This article documents the conflict between peri-urban and urban water users in Mallampet, a peri-urban village adjacent to Hyderabad City. In Mallampet and adjoining villages, 15–20 tanker companies are operating, most of which are owned by the local residents of the area. The number of tanker companies fluctuates depending on the business conditions. Most of them operate without legal permission from authorities. Pumping groundwater and selling it to urban consumers requires minimal hard work and yields maximum returns. Some villagers have been able to seize this opportunity, more so because agriculture is no longer profitable. Based on the data collected from individual pumps and selected tanker companies operating in the village, estimates were made for the amount of water extracted and the revenue earned by a few wealthy and powerful people in the village who are ignorant of the dire consequences of rapid aquifer discharge. The conflict is latent at the moment because the water sellers and buyers are more powerful socially and economically, while the people who are at the receiving end do not have a voice. They are unable to prevent the extraction and sale of groundwater in order to help reduce their insecurity. Even though there are strong laws like the 2002 Andhra Pradesh Water, Land and Trees Act (APWALTA) which prevents the mining of aquifers, the strong nexus between local authorities, politicians and water sellers helps bypass the law.
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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 | 0.000 | 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 | 0.000 | 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) | 0.002 | 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 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".