“If the reindeer die, everything dies”: The mental health of a Sámi community exposed to a mining project in Swedish Sápmi
Bibliographic record
Abstract
In 2006, a British mining company started the process of extracting ore from Gállok/Kallak, in Swedish Sápmi. These grounds are used all year round for reindeer herding by the Sámi community Jåhkågasska tjiellde. While environmental impact assessments should be conducted by law in any development project in Sweden, the health component included is usually vague. The aim of this study was to understand the experiences and perceptions of the Sámi community regarding the current and potential health effects of the proposed mine.A qualitative study, including six in-depth interviews with members of the community, was conducted in 2020. Interviews were analysed using thematic analysis. Five themes were identified and organised in current and future impacts. Current impacts included "It's like David's battle against Goliath", "It's a slow process that takes a lot of power and energy", "It's a defense … like, to protect oneself"; with future impacts including: "If the reindeer die, everything dies", "You would feel that you do not possess any power, [you would feel] overridden, pushed away, not liked".The fear of losing current and future generations' livelihoods appeared to be the main mediators of the current and potential worsened mental health experienced by the community.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.009 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".