The path to investment in water infrastructure in low income and least developed countries: Obstacles and possibilities
Bibliographic record
Abstract
Rural communities in low-income countries rely on intermittent water supply, defined as access to water for less than 24 h a day. The path to continuous water supply requires electricity as well as water infrastructures, which in turn requires the necessary finance for investment. We show that a sample of 16 Least Developed Countries (as classified by the UN) do not yet meet the minimum conditions necessary to implement continuous water supply, mainly because they do not have the finance. Building up an infrastructure requires investments, using earned foreign exchange or loans, to build up electricity capacity, water treatment plants and a distribution pipe network. But once a country has the electricity infrastructure and the basic water mains, its remote areas can then be served through low-cost investment into a system called “trickle fill.” Vietnam, having developed fast through export earnings, was able to increase its electricity production and expand its drinking water infrastructure. But there are still people in rural Vietnam without access to drinking water. We show that where there are water mains, continuous supply can be extended further through “trickle fill.” We describe a freely available user-friendly decision-making tool for a feasibility study for a trickle fill solution and describe countries where this solution has been successfully implemented. For developing countries, we show that there is no shortcut to converting intermittent water supply to continuous water supply without adequate foreign exchange earnings which can then be invested in electricity and water infrastructure. Key words: Foreign exchange, intermittent water, least developed countries, trickle fill, Vietnam.
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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) | 0.000 | 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 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".