Putting small-scale mining in perspective: an analysis of risk perception of a southwestern Nigerian community
Bibliographic record
Abstract
Across the developing world, informal small-scale mining is still growing in popularity, so are its significant socio-environmental burdens to the host communities. The assumption that understanding risk tolerance at small scale of mining is important to recommending effective planning approach, in mitigating its environmental impacts, and in promoting environmentally responsible oversight gave rise to this survey. Quantitative responses from a systematic random sampling of 506 residents of Ijero-Ekiti mining community (southwestern Nigeria) are presented with an emphasis on risk perception and management measures. By ranking 21 variables identified through an extensive literature review, residents’ tolerance index (RTI) and resident agreement index (RAI) are computed. The results suggest that while residents’ risk perception is largely motivated by socio-economic considerations brought about by a major surge in population growth in recent years, there is greater desire for an active public engagement and improved regulatory oversight. The conclusion highlights the value of local capacity building and increased awareness of less risky economic alternatives in successfully implementing long-terms solutions to risks associated with unsustainable mining practice at any scale.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".