“ANYTHING FROM THE LAND IS GOOD”: UNDERSTANDING HOW COMMUNITY GARDENING IN KAKISA, NORTHWEST TERRITORIES, CAN CONTRIBUTE TO INDIGENOUS FOOD SOVEREIGNTY
Bibliographic record
Abstract
Rates of food insecurity in Canada’s northern Indigenous communities are at levels that should constitute an emergency. Dominant explanations for these high rates of food insecurity often ignore the ongoing impacts of colonization and over-emphasize individual choices and nutritional guidelines developed by outsiders. The importance of holistic community health is ignored, along with the cultural and social values and practices that support community health and well-being, including traditional food systems. As the acute impact of climate change in the North threatens traditional food access, a shift toward an Indigenous food sovereignty approach in health and food policy is needed. With an emphasis on decolonization and prioritizing Indigenous ways of knowing, this approach supports communities pursuing self-determined food systems.\nThe community of Kakisa in the Northwest Territories has a hybrid food system primarily comprised of traditional food and market food, with a small amount of produce from their community gardens supplementing their food needs. As their access to traditional food sources are increasingly strained due to environmental and social changes, reliance on market food is prominent in Kakisa. The community sees small-scale food production as an important step towards increasing their access to fresh produce during part of the year, and in turn, their resilience in the face of changing conditions.\nThis investigation into the goals, successes, and barriers for growing food in Kakisa was undertaken in 2018. Using a Participatory Action Research approach that was informed by Indigenous methodologies, this research evaluated the community gardening project to produce an action plan for the future of growing food in Kakisa. Data gathered through interviews and participant observation was examined using a narrative approach to inductive analysis. The themes that emerged showed that, for the residents of Kakisa, successful local food production is driven by community participation and contributes to their self-sufficiency while taking care of the land and community. The application of an Indigenous food sovereignty framework revealed how Kakisa’s pursuit of self-determination can overcome the limitations of using a southern model of community gardening in a northern, Indigenous community; however, current food system policies remain a barrier to this pursuit.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.015 | 0.012 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| 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".