Sustainable Water Service Delivery: An Assessment of a Water Agency in a Rapidly Urbanizing City in Nigeria
Bibliographic record
Abstract
In the Nigerian Federation, water supply is a state responsibility. State governments have therefore created State Water Agencies to manage and operate systems for water service delivery in all urban and semi-urban areas. Generally, these State Water Agencies have failed to effectively deliver water services to the people. In Ado-Ekiti, the Ekiti State Water Corporation is saddled with the task of meeting the water needs of the city dwellers. This paper examines some factors that explain the poor service delivery level of the Corporation. Adopting a sample size of 1,200 (4% of the total number of households in Ado-Ekiti) through random sampling technique, empirical estimates show that factors that significantly affect the performance level of this Corporation include: payment for water supply, billing system, adequacy of supply, frequency of pumping of water, notices from the Corporation in cases of system breakdown, response to leakages, adequacy of public standing pipes and appropriate location or distribution of standing pipes. The paper clamored for an evolvement of water policy for the state that would adequately address the issues emanating from the significant factors affecting the Corporation performance.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".