Aboriginal Food Security in Northern Canada: An Assessment of the State of Knowledge
Bibliographic record
Abstract
As the world’s population increases, as global markets become more interconnected, and as the effects of climate change become clearer, the issue of food insecurity is gaining traction at local, national, and international levels. The recent global economic crisis and increased food prices have drawn attention to the urgent situation of the world’s 870 million chronically undernourished people who face the number one worldwide risk to health: hunger and malnutrition. Although about 75% of the world’s undernourished people live in low-income, rural regions of developing countries, hunger is also an issue in Canada. In 2011, 1.6 million Canadian households, or slightly more than 12%, experienced some level of food insecurity. About one in eight households are affected, including 3.9 million individuals. Of these, 1.1 million are children. Food insecurity presents a particularly serious and growing challenge in Canada’s northern and remote Aboriginal communities (see Figure 1). Evidence from a variety of sources concludes that food insecurity among northern Aboriginal peoples is a problem that requires urgent attention to address and mitigate the serious impacts it has on health and well-being. Results from the 2007–2008 International Polar Year Inuit Health Survey indicate that Nunavut has the highest documented rate of food insecurity for any Indigenous population living in a developed country. According to estimates from the 2011 Canadian Community Health Survey (CCHS), off-reserve Aboriginal households across Canada experience food insecurity at a rate that is more than double that of all Canadian households (27%). Recent data indicate that Canadian households with children have a higher prevalence of food insecurity than households without children, and preliminary evidence indicates that more women than men are affected.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.022 |
| Science and technology studies | 0.009 | 0.003 |
| Scholarly communication | 0.007 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".