Integrating Healthcare and e-Health in the Territories: The Tasks Ahead for Yukon, the Northwest Territories and Nunavut
Bibliographic record
Abstract
Introduction In the government’s Speech from the Throne opening the Third Session of Canada’s 40th Parliament, delivered on March 3, 2010, the Right Honourable Michaelle Jean, Governor General of Canada, asserted that the current government “established the Northern Strategy to realize the potential of Canada’s North for northerners and all Canadians.” Specifically, the government “will continue to give northerners a greater say over their own future and take further steps toward territorial devolution” (Government of Canada 2010). In the last decade, the federal government’s policy of promoting Canada’s North for northerners has been echoed in the strategic initiatives, budgets and specific policies of the country’s northern jurisdictions. Specifically in healthcare and social services, Yukon, the Northwest Territories and Nunavut have undertaken initiatives in the last year that reflect the distinctive healthcare needs and priorities of their northern jurisdictions. Examples of initiatives undertaken since 2004 follow:
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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 | 0.001 | 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 | 0.013 | 0.004 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".