Small-scale Mining and Sustainable Rurality in the Atiwa District of Ghana
Bibliographic record
Abstract
This paper examines the effects of artisanal and small-scale mining (ASM) activities on sustainable development in the Atiwa District of Ghana. It relies on data from 75 respondents from five communities in the District. Twenty-eight of them responded through face-to-face in-depth interviews while 47 responded through a survey questionnaire. This data is complemented by secondary sources, including literature on mining and sustainable development. Using this data, the paper deploys the three canons of sustainable development—economic, social and environmental—to investigate, the impact of ASM on rural communities. The result furthers the arguments of previous research that the ASM sector has both positive and negative impacts on the sustainability of local or rural economies. However, this paper adds that whether present rural communities will reap the full benefit of the sector, while not undermining the social, economic, and environmental livelihoods of future generations, would depend on government regulation and policy. Since most ASM activities occur in rural communities, which are primarily agrarian and subsistent in character, a lack of regulation of the sector not only contributes to the destruction of rural economies and environments, but it also unsettles current and future human ecology. In a country like Ghana—where many, if not most, citizens live in rural areas—making ASM sustainable to benefit present and future rural dwellers should be a legitimate national development concern. Thus, we use the concept of sustainable rurality to mean a case of governing the ASM to ensure that current rural and agrarian livelihoods are improved without jeopardizing the societies, economies and environment of future generations. We conclude that mandated institutions, regulatory agencies, and development stakeholders should work to tilt the balance of the sector in favor of sustainable rurality. Keywords: small-scale mining, Atiwa District, Ghana, rural livelihoods, sustainable development
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".