The Costs of Local Food Procurement in Two Northern Indigenous Communities in Canada
Bibliographic record
Abstract
Remote Northern Ontario First Nations communities face severe food insecurity. Prices of store foods are often unaffordable and not always in stock. Government programs have been implemented to subsidize some of the market food costs. Our objective is to illustrate the costs associated with procuring food from the land through hunting and fishing in an effort to present this as an alternate option to relying solely on store-bought foods. Northern Ontario is an area of the world undergoing a rapid nutrition transition leading to high levels of obesity and type 2 diabetes. Despite this knowledge, little has been done to reverse this trend using land based foods, widely promoted as nutritionally beneficial. We conclude that estimated cost of food from the land requires significant energy and time, but remains economically comparable to food available in-store. Further government support should be given to community hunters to make land-based food a viable option for a larger proportion of each community.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".