Water Governance: Challenges and Prospects for the Implementation of Sustainable Development Goal Six in Nigeria
Bibliographic record
Abstract
The primary objective of this study is to review all Nigerian National Water and Sanitation Policies implemented since 1993. The aim is to assess their performance, efficiency, and alignment with the targets set forth in UN Sustainable Development Goal 6 (SDG 6). This review provides a contextual understanding of the challenges and opportunities for implementing SDG 6 in Nigeria. We conducted a critical appraisal and qualitative analysis of the 2016 Nigerian National Water Resources Policy, the most recently published policy, in relation to the targets of SDG 6. Our findings indicate that seven out of the eight SDG 6 targets are addressed in the policy. These include safe drinking water, sanitation and hygiene, pollution reduction, water-use efficiency, trans-boundary cooperation, and protection of water-related ecosystems. However, the policy falls short in involving local communities in water and sanitation management, which is the eighth requirement of SDG 6. Specifically, only 28 states have a dedicated Rural Water Supply and Sanitation Agency (RUWASSA), and few local government areas have Water Supply and Sanitation Hygiene Departments (WASH) as required by SDG 6. Our assessment of the policy's implementation and practices is based on secondary data sources, notably from the United Nations, the World Health Organization, and the National Bureau of Statistics. We argue that by developing effective implementation strategies that involve local communities, the 2016 National Water Resources Policy can significantly contribute to achieving sustainable water and sanitation management for all Nigerians by 2030.
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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 | 0.009 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".