Apportionment of Funds to Mining-Impacted Communities within Forest Reserve Environments in Ghana
Bibliographic record
Abstract
This paper uses risk assessment of socio-economic and environmental indicators to develop criteria for apportionment (AP) of funds to communities impacted by mining activities within a Forest Reserve environment in Ghana. A t-test statistic of assessment data shows that factors such as; cost of living, health conditions, air pollution, water contamination, land degradation and distance (D km) are significant. Ratings of the factors using a 1-5 intensity scale to determine risk values (RV) for communities indicate that RV of 25 requires no remediation, while (25-RV) is remediation factor. A long-term AP criterion using the ranked risk (RR) values is defined by the equation APRR%=7.45-0.233(RR) with R2 of 0.961. Based on this criterion, communities D and S which are located at 1.5 and 16.1km from the mining focus have APRR values of 7.23% and 2.26%, respectively. APRR% in relation to distance is defined by the equation APRR%=7.22-0.281(D) with R2 of 0.647. RR-dependent distance equation (APD %) is used to deduce a short-term criterion defined by K*APD%=4.13-0.097(RR), where K is a constant. The expression of (APRR-K*APD) represents the residual apportionment required after a long-term assessment. The findings in this research demonstrate well-defined patterns that can be replicated for similar future projects.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".