Disparities amidst plenty: a health portrait of Indigenous peoples in circumpolar regions
Bibliographic record
Abstract
This paper describes the extent and variation in health disparities between Indigenous and non-Indigenous people within Alaska, Greenland and the northern regions of Canada, Russia and the Nordic countries. We accessed official health statistics and reviewed research studies. We selected a few indicators of health status, health determinants and health care to demonstrate the health disparities that exist. For a large number of health indicators Indigenous people fare worse than non-Indigenous people in the same region or nationally, with the exception of the Sami in the Nordic countries whose health profiles are similar to their non-Sami neighbours. That we were unable to produce a uniform set of indicators applicable to all regions is indicative of the large knowledge gaps that exist. The need for ongoing health monitoring for Indigenous people is most acute for the Sami and Russia, less so for Canada, and least for Alaska, where health data specific to Alaska Natives are generally available. It is difficult to produce an overarching explanatory model for health disparities that is applicable to all regions. We need to seek explanation in the broader political, cultural and societal contexts within which Indigenous people live in their respective regions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".