Mining and Sustainability in the Circumpolar North: The Role of Government in Advancing Corporate Social Responsibility
Bibliographic record
Abstract
Corporate Social Responsibility (CSR) is recognized as important to fostering sustainable natural resource development in the Circumpolar North. Governments are playing an increasingly active role in promoting and shaping CSR initiatives, often in collaboration with Indigenous communities and industry. This paper explores the role of CSR in mining for improving socio-economic and environmental management practice. The article argues that government instituted regulations can lead to the development and implementation of CSR practices by mining companies. To examine the relationship between government requirements and CSR, we use two Northern case studies: Cameco Corporation's uranium mining operations located in Saskatchewan, Canada and Northern Iron's iron mining operation located in Troms and Finnmark county, Norway. Through an in-depth review of scholarly literature, document analysis, and semi-structured interviews, our findings suggest that the role of the state in the initiation and implementation of CSR is of much greater importance than is currently acknowledged in the literature. In the case of Cameco, the Mine Surface Lease Agreements agreed to by the corporation and the provincial government provided motivation for the development and implementation of their world-renowned CSR practices, resulting in a community-based environmental monitoring program and benefits for both the company and surrounding communities. With Northern Iron's operations in Kirkenes, working hour requirements instituted by the Norwegian Government allowed for significantly higher levels of local employment. Our findings suggest a greater role exists for government to facilitate the adoption of CSR policies, contributing in turn to improved socio-economic and environmental outcomes for Northern communities.
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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 | 0.001 | 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".