Suicidal behavior among indigenous Sami in Arctic Norway : a special focus on adolescents and young adults
Bibliographic record
Abstract
Since the 1950’s the global suicide rates have continued to increase, and today suicide has\nbecome an important public-health problem worldwide (World Health Organization (WHO),\n2002). According to WHO there are approximately one million deaths from suicide each year\nworldwide, and about 20 times this number of people attempt suicide (2002). There are\nsubstantial variations in the national suicide rates (Lester, 1997), and in addition great\nvariation in rates within the same country and between different ethnic groups (Roberts, Chen\n& Roberts, 1997). During the last decades suicide rates have increased alarmingly among\nindigenous people, and especially among indigenous residing in the Arctic, such as the lnuit\nin Greenland (Leineweber et al., 2001) and in Canada (Sigurdson et al., 1994), and among\nAlaskan Natives in the US (Borowsky et al., 1999). The increase in suicide rates among\nindigenous people in the Arctic have been so alarmingly high that it has been described as an\nepidemic level (Bjerregaard & Lynge, 2006; Leenaars, 2006) and it has been declared that\ncertain indigenous people have the highest suicide risk of any identifiable cultural (or ethnic)\ngroup (Leenaars, 2006; Kirmayer, 1994). Unfortunately, suicide has become the leading cause\nof death for young indigenous people, especially among males, and is a significant contributor\nto potential years of life lost. Although there is carried out research on the prevalence of\nsuicidal behavior among several indigenous people, e.g. in Canada, Alaska, Greenland,\nSweden, Australia, New Zealand, our understanding of suicidal behavior among indigenous\npeople is still limited (Cutcliffe, 2005; Leenaars, 2006; Stewart, 2005).<br>\nThere is no registration of ethnicity in the national population register in Norway, for\nthat reason there are neither official statistics of health and living conditions nor suicide rates\nfor indigenous Sami (hereafter called Sami). There have so far been conducted limited\nresearch on health and living conditions among Sami in Norway, and suicidal behavior has\nnot previously been studied in a systematically way. Although some Sami communities have\nexperienced high rates of suicides, there is in general lack of specific prevention strategies.\nEpidemiological knowledge about suicidal behavior among Sami is important for\nimplementation of appropriate prevention strategies in Sami communities, and in addition\nuseful to public health practitioners and policy makers in addressing this problem.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".