Food insecurity in Nunavut following the introduction of Nutrition North Canada
Bibliographic record
Abstract
BACKGROUND: Household food insecurity, a measure of income-related problems of food access, is a pressing public health problem in Canada's North, especially in Nunavut. We aimed to assess the impact of Nutrition North Canada, a food retail subsidy intended to improve food access and affordability in isolated communities, on household food insecurity in Nunavut. METHODS: Using data from 3250 Nunavut households sampled in the annual components of the Canadian Community Health Survey (2007 to 2016), we conducted interrupted time series regression analyses to determine whether the introduction of Nutrition North Canada was associated with changes in the rates of self-reported food insecurity, according to a validated instrument. We used propensity score weighting to control for several sociodemographic characteristics associated with food insecurity. RESULTS: Food insecurity affected 33.1% of households in 2010 (the year before the launch of Nutrition North Canada), 39.4% of households in 2011 (the year of the launch) and 46.6% of households in 2014 (the year after full implementation). After controlling for several covariates, we found the rate of food insecurity increased by 13.2 percentage points (95% confidence interval [CI] 1.7 to 24.7) after the full implementation of the subsidy program, and the increase in food insecurity first occurred in 2011 (9.6 percentage points, 95% CI 2.7 to 16.4), the year Nutrition North Canada was launched. INTERPRETATION: Food insecurity was a pervasive problem in Nunavut before Nutrition North Canada, but it has become even more prevalent since the program was implemented. Given the important health consequences of food insecurity, more effective initiatives to address food insecurity in Canada's North are urgently needed.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 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".