Integrating indigenous knowledge and skills in mining operations: A systematic literature review
Bibliographic record
Abstract
This review explores the integration of Indigenous Knowledge and Skills (IKS) in mining operations, aimed at developing a comprehensive understanding of how these knowledge systems are embedded throughout the mining life cycle. The study systematically reviewed relevant literature from three electronic databases using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eighteen articles that met the inclusion criteria were included in the final analysis. Key findings reveal that qualitative methods, particularly interviews, are predominantly used to capture Indigenous perspectives. The research is regionally concentrated in Australia, with significant contributions from Canada, Papua New Guinea, and the USA. The studies encompass various Indigenous groups, highlighting varied cultural contexts and knowledge systems. Traditional ecological knowledge, a subset of IKS, is frequently integrated into mine planning and rehabilitation, demonstrating its practical value in sustainable mining practices. Factors facilitating the integration of IKS include supportive policies and laws, community leader involvement, and alignment with community expectations. Our findings contribute to the understanding of IKS in mining operations by providing a detailed overview of IKS integration in the mining life cycle, emphasising the importance of qualitative research, regional and cultural diversity, and their practical benefits.
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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 | 0.000 | 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 | 0.000 |
| 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".