Mitigating the Risks of Resource Extraction for Industrial Actors and Northern Indigenous Peoples
Bibliographic record
Abstract
A collaborative relationship between native peoples and industrial corporations_two actors that value resource-rich land_is of vital importance for both the United States and the Russian Federation. A strong partnership between industrial and indigenous actors can help to ensure not only the stability of extractive projects, but also the protection of indigenous groups from the potentially existential threats associated with territorial loss. Cooperation between these two parties gains urgency as extractive corporations begin to explore the Arctic, a region of the world already home to over two dozen unique indigenous communities. In both the United States and the Russian Federation, there are legal precedents for negotiations regarding indigenous rights, natural resources, and the fuel-energy complex. Even so, parties involved in the extractive process frequently stray from these national and international legal guidelines. Our paper seeks to answer the question: why might rational actors_here, indigenous and industrial communities that are motivated by their preferences_fail to cooperate on extractive projects, even when robust collaborative agreements benefit all sides? We suggest that the explanation is twofold: first, indigenous land rights lack the consistency which may give indigenous communities control over their resources and cultural preservation; and second, a neutral and objective third-party mediator_whether in the form of a state or an international body_is often silent in, or absent from, the negotiation process, thereby undermining its authority to ensure fair and reasonable deliberations. Our findings can offer important insights for community-corporate relations, not only in the Arctic, but worldwide.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".