Mining and Indigenous Livelihoods
Bibliographic record
Abstract
<p>This book maps the encounters between Indigenous Peoples and local communities with mining companies in various postcolonial contexts.</p><p>Combining comparative and multidisciplinary analysis, the contributors to this volume shine a light on how the mining industry might adapt its practices to the political and legal contexts where they operate. Understanding these processes and how communities respond to these encounters is critical to documenting where and how encounters with mining may benefit or negatively impact Indigenous Peoples. The experiences and reflections shared by Indigenous and non-Indigenous contributors will enhance our understanding of evolving practices and of the different strategies and discourses developed by Indigenous Peoples to deal with mining projects. By mobilizing in-depth fieldwork in five regions—Australia, Canada, Sweden, New Caledonia, and Brazil—this body of work highlights voices often marginalized in mining development studies, including those of Indigenous Peoples and women.</p><p>This book will be of great interest to students and scholars of mining and the extractive industries, sustainable development, natural resource management, and Indigenous Peoples.</p><p>The Open Access version of this book, available at http://www.taylorfrancis.com, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives (CC-BY-NC-ND) 4.0 license.</p>
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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".