Managing delivery of sanitation infrastructures for poor communities
Bibliographic record
Abstract
Purpose The purpose of this paper is to investigate how lessons learnt from a case study of a sanitation project undertaken in periurban Vietnam can indicate a more sustainable scale of operations by decentralization. In context of high urbanization in South‐East Asia, periurban areas suffer increasing environmental pressure and lack access to environmental infrastructures. As the government of Vietnam has not yet defined its supply programme for sanitation, central governmental supply and operation is questioned by various small non‐governmental organizations (NGO) that could successfully provide community‐managed projects. Design/methodology/approach A pilot wastewater management community project by an international NGO serves as a case study for capacity‐analysis at the local level. Using interviews with experts and user‐oriented focus groups, both the village and household capacities to participate in the project are analyzed. Findings The research identifies the skills and expertise necessary for the management of a sustainable sanitation service. Observing local skills and resulting outputs of the community‐managed system provides comprehensive insight about the highest needs of local support and clarifies coordination priorities between stakeholders. Research limitations/implications This paper is limited to one country and context, while findings can be useful in similar contexts it cannot be generally applied. Practical implications The Lai Xa project demonstrates that operation decentralization could be highly profitable for the authorities compared to the traditional approach of government supply and maintenance. Local communities could, with proper training, manage and maintain a simple sanitation system. The sustainability of these community services finally depends on proper coordination by water and sanitation authorities providing specialized technical and managerial support. Originality/value There is a dearth of literature on project case studies in the NGO world and this paper helps to broaden the understanding of the interface between project management and aid project delivery by providing useful insights on how the project uses a complex system of capacities at various levels.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".