Prevalence of affirmative responses to questions of food insecurity: International Polar Year Inuit Health Survey, 2007–2008
Bibliographic record
Abstract
OBJECTIVES: Assess the prevalence of food insecurity by region among Inuit households in the Canadian Arctic. STUDY DESIGN: A community-participatory, cross-sectional Inuit health survey conducted through face-to-face interviews. METHODS: A quantitative household food security questionnaire was conducted with a random sample of 2,595 self-identified Inuit adults aged 18 years and older, from 36 communities located in 3 jurisdictions (Inuvialuit Settlement Region; Nunavut; Nunatsiavut Region) during the period from 2007 to 2008. Weighted prevalence of levels of adult and household food insecurity was calculated. RESULTS: Differences in the prevalence of household food insecurity were noted by region, with Nunavut having the highest prevalence of food insecurity (68.8%), significantly higher than that observed in Inuvialuit Settlement Region (43.3%) and Nunatsiavut Region (45.7%) (p≤0.01). Adults living in households rated as severely food insecure reported times in the past year when they or other adults in the household had skipped meals (88.6%), gone hungry (76.9%) or not eaten for a whole day (58.2%). Adults living in households rated as moderately food insecure reported times in the past year when they worried that food would run out (86.5%) and when the food did not last and there was no money to buy more (87.8%). CONCLUSIONS: A high level of food insecurity was reported among Inuit adults residing in the Canadian Arctic, particularly for Nunavut. Immediate action and meaningful interventions are needed to mitigate the negative health impacts of food insecurity and ensure a healthy Inuit population.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".