The Impact of Mining on the Water Resources in Ghana: Newmont Case Study at Birim North District (New Abirem)
Bibliographic record
Abstract
Mining activities accelerate the rate and degree of changes in the natural environment. These activities modify landscapes and can have long-term pollution impacts on communities and water resources due to their physical degrading nature, as well as their use of chemicals and other harmful substances. This study carried out by Department of Energy and Environmental Engineering of the University of Energy and Natural Resources therefore sought to assess the role of Newmont Akyem towards affecting the various water bodies in Akyem District. Qualitative and quantitative comparative methods were used for gathering data and performing analysis. The findings indicated that the physico-chemical parameters tested for the water bodies were all within the EPA, Ghana standards for drinking water except for the Pra River which recorded high levels of TSS indicating that there was, possibly, illegal mining activities upstream affecting the quality of the water. The study recommends that government provides both training and equipment to support small scale miners to avoid illegal mining. Also mining companies should contribute towards developing alternative livelihood for communities on whose lands they occupy. EPA should enforce environmental laws to protect the water bodies and the environment.
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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 | 0.000 | 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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".