Industrial pollution in Ota Ogun State, Nigeria: the disconnect between citizen, industry and government perspectives
Bibliographic record
Abstract
This study examined how residents of Ota, in Ogun State Nigeria, perceive the effects of industrial pollution. It also reviewed the policies that the state government has adopted in controlling and preventing industrial pollution in the past years. Surveys and interviews were used to determine the perceptions of community members and the policy actions of government. The sampling technique used during the survey was purposeful sampling. Data were analyzed through Microsoft Excel and content analysis. Research results showed that residents perceive that industries in Ota pollute the environment a lot. The study also revealed that air pollution through smoke is the major environmental concern for residents in comparison to water and soil pollution. The study revealed that citizens believe the government has not been effective in managing industrial pollution despite its claim that various policy options are being used to address the issue. This study makes recommendations, which could further improve environmental issues in the communities. The successful implementation, monitoring, and enforcement of policies and involvement of residents has the potential to enhance environmental sustainability in Ota.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".