Bibliographic record
Abstract
Although dominant western narratives often imply otherwise, mining is not just a colonial idea or activity. First Nations have been mining and quarrying rocks and minerals for thousands of years, using the extracted materials for cultural, spiritual, medicinal, and practical purposes. The literature documenting the use of rocks and minerals by First Nations peoples has been produced by archaeologists, and very little is known about these activities within the context of mining engineering and geoscience. By documenting the knowledge, resource management and science behind First Nations use of rocks, minerals and mining, we can contribute to the decolonization of the mining sector, while also helping to drive much needed innovation. The mining industry is now evolving to focus more attention on smaller and lower grade deposits, reprocessing of waste, sourcing independent supplies of critical minerals, and Indigenous reconciliation. Continued advances in these areas, inspired from the lessons of First Nations mining, are needed to transition the industry on a path to social and environmental sustainability. Working with Indigenous peoples to incorporate Indigenous ways of knowing into mine design and reclamation could be the key to overcoming the challenges ahead.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.044 | 0.010 |
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".