The tip of the iceberg: A literature review on suicide among Indigenous peoples of the Arctic region
Bibliographic record
Abstract
Background: The Arctic region has been experiencing profound changes in the last decades that have been affecting health and disease patterns.Increased vulnerability towards many diseases and mental health-related conditions including suicide has been pointed out in research, especially for Indigenous populations both globally and in the Arctic region.The aim of this thesis is to conduct a systematised review of the available literature on suicide and suicidal behaviours in the Indigenous populations of the Arctic region to identify patterns and possible contributing factors. Methods:Following a systematised search of the literature published between 2003 and 2023, a narrative synthesis of the included studies was conducted.Contributing factors identified by the authors of these studies were reviewed.Results: Twelve relevant studies from five Arctic states (Norway, Sweden, the US, Canada, and Russia) were identified.The majority of studies found increased risks of suicide and suicidal attempts for Indigenous populations of the Arctic region when compared to non-Indigenous populations.While findings on the Sami people in Norway and Sweden were somewhat mixed, findings from the US, Canada and Russia all established that Alaska Native, Inuit and Nenet populations experience disproportionately higher suicide rates compared to national majority populations. Conclusions:The Indigenous populations of the Arctic region experience higher rates of suicide relative to the majority national populations yet with relevant geographical variations.These rates are especially high for Indigenous youth aged below 25 years.
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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 | 0.007 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.016 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".