Stakeholder participation and sustainability challenges confronting a small urban community-managed water supply project: case study of Buea, Cameroon
Bibliographic record
Abstract
Community-managed initiatives play an important role in global efforts to meet the Millennium Development Goal for water supply provision of halving the population without access to improved water sources, especially in developing countries. However, in the context of growing urbanisation, these community-managed projects are increasingly intersecting urban areas that by their very nature are at odds with traditional rural community-based management practices. This research examines the case of a small community-managed water supply scheme in Buea, a rapidly growing urban area in Cameroon. The study adopted qualitative research methods (household questionnaires and interviews of community water management and users) and applied choice experiments to better understand the sustainability challenges facing community-managed water supply projects in an urbanizing setting, a phenomenon of growing importance in many developing areas. This thesis presents and discusses the findings that in urban areas, community-managed schemes face added management and planning pressures because of larger, more diverse, populations and rapid population growth. Therefore they require greater support from government, non-governmental organisations, and development agencies to provide them with improved technical planning capacity and post-construction operation and maintenance support. Furthermore, urban community-managed schemes require strong political and institutional support to uphold their participatory mechanisms that due to the urban context are at risk of failure. Lack of participation has the added consequences of reducing accountability, reducing cost recovery, and impairing financial sustainability. Based on the results of this research in Buea, failing the provision of support, the future of community-managed schemes in urban areas is an unsustainable one, reneging on the Millennium Development Goals and forcing a return to "unimproved" sources of water.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".