Shifting Transitions: Health Inequalities of Inuit Nunangat in Perspective
Bibliographic record
Abstract
The health of the Canadian Inuit population has been the topic of numerous studies and reviews. Many of these studies have focussed on specific geographic areas, on specific diseases, or on broad reviews of the literature. However, few publications have sought to quantitatively overview the health of the circumpolar Inuit within a population health framework that uses comparable data over time for comparable populations. It has been noted that research on the Inuit should address the broader relationships of health beyond health indicators and status, to include community well-being and socio-economic characteristics. This paper examines the health of the Inuit population in Canada from a broad population perspective, focussing on demographic changes and core health indicators, as well as health status and socio-economic backgrounds. While the inequalities in health indicators between the Inuit and the general population are evident, the story is not as clear when population dynamics and community characteristics are taken into consideration. The results suggest that the inequalities in health between Inuit Nunangat and the general Canadian population are most strongly related to access to health and social services, a lack of education and employment opportunities, and the loss of traditional culture. keywords: Inuit; health; demography; life expectancy; mortality
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".