Public health in the Canadian Arctic: contributions from International Polar Year research
Bibliographic record
Abstract
The contributions of several IPY health projects are highlighted in the context of population health indicators for Inuit Nunangat. Food and housing are two critical social determinants of health contributing to health issues on many levels. The nutritional deficit associated with food insecurity and the transition away from traditional and towards market foods represents a dual risk with profound consequences. Knowledge of the physiological benefits associated with traditional food consumption is increasing, including for mental health and chronic disease. Ensuring the safety of traditional foods in terms of zoonotic diseases is thus highly valuable and efforts to institute adequate monitoring and address knowledge gaps are underway. Acute respiratory disease among the young remains a significant public health issue with potential long term effects. The human papilloma virus is manifesting itself among women across northern Canada with high risk types that are more similar to profiles observed in Europe than in North America with possible implications for immunization programs. Despite a high prevalence of Hepatitis B virus infections among residents of Inuit Nunangat, the outcomes appear to be relatively benign. Communication of new knowledge on the manifestation of this virus among northern populations is provided to health care providers in the North through modern technology.
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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 | 0.009 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.011 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.006 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".