The structure of informal water markets: Insights from spatial monitoring in Lodwar, Kenya
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Public water utilities have struggled to keep pace with rapid urbanization, particularly in towns and small to medium-sized cities of low-income regions. Informal water markets have proliferated to fill gaps in piped water coverage and service delivery through a wide range of water vending activities (from private water sources to tanker trucks and handcart operators that distribute water). Despite the prevalence and persistence of water vending, the structure, impacts, and evolution of informal water markets in these settings remain poorly understood, especially the interaction between private vendors and public utilities. We seek to improve our understanding of mobile, distributing vendors (tankers, motorcycles) by advancing high-frequency, spatially explicit monitoring of water vendor transactions in Lodwar, Kenya. We examine both the market and spatial structure of the informal water supply system and then draw inferences about their impacts and evolution. We find that vendors that use motorcycles are not making profits from transporting water. We also identify many linkages between the formal and informal systems. For example, purchases of bulk water by water vendors account for 28% of the public water utility’s revenue. We also find that while most consumers of vended water are located outside of the piped water service area, many households and institutions inside the service area still purchase from private water vendors due to concerns about reliability and quality. These results highlight the complementarities between public utilities and private water vending and the corresponding importance of mapping water vending networks to support planning, policy, and investment and to protect consumers.
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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) | 0.000 | 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 it