Solid Waste Management and Public Health Challenges: Appraisal of Local Government Capacity to Achieve Effective Environmental Governance
Bibliographic record
Abstract
Solid waste management is an essential social service of the local government system in Nigeria. The lack of adequate funding of the local governments has created a situation where most of the cities are dirty as solid waste is disposed indiscriminately resulting to various public health issues. The establishment of the ecological fund has not provided effective relief to the problems of environmental governance, including solid waste management. The study examined the relationship between solid waste management and public health challenges in Ibadan city, Nigeria. The study adopted survey design, while the population of study was Ibadan city in Oyo State, Nigeria. Quantitative data was collected using validated questionnaire with response rate of 100%. Correlation coefficient and ANOVA were employed in the testing of the hypotheses. The study found that there was significant relationship between Politicization of Waste Management and Public Health Challenges (r = .325, p<.05). In addition, there was significant relationship between Ineffective Management of Solid Waste and Public Health Challenges (r = .662, p<.05). Indiscriminate Disposal of Solid Waste, Politicization of Solid Waste and Ineffective Management of solid waste had joint significant effect on Public Health Challenges (F(3, 296) = 22.078, Adj. R2 = .696, p<0.05). The study concluded that the politicization of solid waste management in the selected local governments had resulted in ineffective management of solid wastes, with the residents being exposed to several public health challenges. It was recommended that there should be improved funding of the waste management agencies to enable them adopt modern waste disposal techniques.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| 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".