The Inuit Health Survey: Health in Transition and Resiliency
Bibliographic record
Abstract
The Inuit Health Survey represents a cross-sectional study design. Data collection was performed with the assistance of an ice-breaker that is part of the Canadian Coast Guard Ship fleet. The ship visited 18 communities in the Eastern Arctic in 2007, and 4 communities in Inuvialuit, 6 in Nunavut, and 5 in Nunatsiavut in 2008. The research used 4 separate crews: 3 land-based teams and 1 ship-based team. The land teams visited the hamlets prior to the ship's arrival. Households were randomly selected from municipal household lists where there was at least one Inuk adult residing. The land-based teams recruited the adults and conducted face-to-face interviews prior to their ship appointment. On the ship nurses took fasting blood samples, administered a glucose tolerance test, took blood pressure and pulse, measured height, sitting height, waist circumference and % body fat, and toenail clippings. Men and women over 40 years wore a holter monitor for 2 hours to assess heart rate and had the carotid intima-media thickness assessed using a portable non invasive ultrasound technique. Women also had their bone mineral density measured using a low dose x-ray of the forearm and heel. Participants also answered questionnaires about general health, dental health, tobacco use, nutritional habits and physical activity and a questionnaire about social support, wellness and coping mechanisms, alcohol and drug use, and life experiences such as violence, abuse and suicide. The survey was designed to be compatible with a similar survey in Nunavik of Northern Québec in 2004 and with an ongoing health survey in Greenland. A total of 2,595 adults participated in the survey.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".