The north is not all the same: comparing health system performance in 18 northern regions of Canada
Bibliographic record
Abstract
We investigated the availability of health system performance indicator data in Canada's 18 northern regions and the feasibility of using the performance framework developed by the Canadian Institute for Health Information [CIHI]. We examined the variation in 24 indicators across regions and factors that might explain such variation. The 18 regions vary in population size and various measures of socioeconomic status, health-care delivery, and health status. The worst performing health systems generally include Nunavut and the northern regions of Québec, Manitoba and Saskatchewan where indigenous people constitute the overwhelming majority of the population, ranging from 70% to 90%, and where they also fare worst in terms of adverse social determinants. All northern regions perform worse than Canada nationally in hospitalisations for ambulatory care sensitive conditions and potentially avoidable mortality. Population size, socioeconomic status, degree of urbanisation and proportion of Aboriginal people in the population are all associated with performance. The North is far from homogenous. Inter-regional variation demands further investigation. The more intermediate pathways, especially between health system inputs, outputs and outcomes, are largely unexplored. Improvement of health system performance for northern and remote regions will require the engagement of indigenous leadership, communities and patient representatives.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".