Mining, Pollution and Agricultural Productivity: Evidence from Ghana
Why this work is in the frame
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Bibliographic record
Abstract
Most modern mines in the developing world are located in rural areas, where agriculture is the main source of livelihood. This creates the potential of negative spillovers to farmers through competition for key inputs (such as land) and environmental pollution. To explore this issue, we examine the case of gold mining in Ghana. Through the estimation of an agricultural production function using household level data, we find that mining has reduced agricultural productivity by almost 40%. This result is driven by polluting mines, not by input availability. Because of its crowding out effects on agriculture, we find that the mining activity is associated with an increase in poverty, child malnutrition and respiratory diseases. A simple cost-benefit analysis shows that the fiscal contribution of mining would not have been enough to compensate affected populations.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it