"It can never be worse than now" : A qualitative study of mining related conflicts in Sápmi from a Sámi perspective
Bibliographic record
Abstract
Land use conflicts are not a new phenomenon, especially when new sustainable establishments, such as mining, hydroelectric energy, and wind power, are necessary to mitigate the climate change. In Sápmi, the region of the indigenous people of Scandinavia, Sámi, there has been land use conflicts between Sámi people and mining companies since the opening of the mines and are still ongoing today. Previous research has concluded various reasons as to why this conflict has started and is still ongoing: mining legislation, indigenous peoples’ rights’ legislation, socio-environmental impacts caused by mining, lack of participation in decision-making, lack of monetary compensation, and distrust towards mining companies and the government. This thesis has investigated what Sámi people themselves perceive to be the biggest causes to the conflict. Although Sápmi is spanning over several countries, only the Swedish part of Sápmi has been investigated. Since this thesis investigates people’s perception of a conflict, this investigation used a qualitative method. A total of seven interviews was conducted with Sámi people living in Swedish Sápmi. The results show that even though there are an array of different causes to the conflict, the biggest reasons are the environmental impacts mining has on the nature, and the question of indigenous peoples’ rights and the right to involvement. Other reasons that have been brought up are the mining legislation regarding foreign companies prospecting in Sweden, and the lack of research done on the accumulated environmental and social effects various establishments have, such as mining, hydroelectric energy, and wind power. The discussion section compares this thesis’ results with previous research, as well as comparing how British Columbia, Canada, have dealt with a similar conflict.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.013 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.003 | 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".