Sustainable groundwater management in Lagos, Nigeria: the regulatory framework
Bibliographic record
Abstract
This doctoral research focuses on groundwater degradation in Lagos, Nigeria. Groundwater is a fundamental natural resource in Lagos that is presently troubled by pollution emanating from solid waste and wastewater. The city generates 10,000 metric tons of waste and 350 million gallons of wastewater daily, all of which are improperly managed and are heavily polluting its groundwater. This direct environmental pollution is aggravated by indirect problems of over-urbanization, and legal and institutional shortcomings. Over-urbanization in Lagos has resulted into a monumental population of 21 million people in the tiny city, which generates the enormous quantities of solid waste and wastewater. The population places a tremendous burden on the city’s water resources, forcing residents to revert to groundwater which is suffering the plight of pollution, and hence the concern of this research. The pollution problem is worsened by civic apathy to environmental matters, and unresolved by a nascent water sector whose evolving governance structures do not adequately address the multi-dimensional pollution problem. In the final analysis, the absence of holistic and comprehensive groundwater legislation that addresses all these problems challenges the sustainability of this vital resource. The research study contributes to knowledge by attempting to provide broad and holistic recommendations for law reform which address the pollution, management of the effects of over-urbanization and overpopulation on groundwater, and the strengthening of institutions to achieve a sustainable groundwater resource. Key words: groundwater, solid waste, wastewater, urbanization, pollution
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".