Capitals, climate change and food security: Building sustainable food systems in northern Canadian Indigenous communities
Bibliographic record
Abstract
For many Indigenous communities in Canada’s northern boreal forest, the impacts of climate change are directly affecting their ability to access the land they rely on for traditional foods to support their food systems and livelihoods. However, climate change is merely one stressor for communities that have undergone dramatic social, cultural and political changes during the past decades. This research examines case studies in the communities of Délı̨nę and Kakisa, Northwest Territories (NWT), and identifies community-based solutions to build more sustainable food systems with a focus on food security and climate change. Using participatory action research methods to ensure the process is community-driven and responds to stakeholder needs, each case study identifies vulnerabilities to the respective food systems due to climate change. The Community Capitals Framework – including social, cultural, natural, financial, human, built and political capital – is used to describe and assess the complex food systems in the North. The research illustrates how a community can allocate available capitals to help adapt to the impacts of climate change and identify which capitals are required to build a more sustainable food system. In both communities, addressing issues of food security involved protecting natural capital as well as social and cultural capitals, all of which are important to maintaining traditional foods as the foundation of the food system. The capacity to teach and pass on skills and knowledge to the younger generation, and work together as a community but also with researchers and broader networks, can help promote knowledge sharing. This in turn will enhance resilience in the community in the face of climate change. Building human capital through training and education, and being supported through funding and a network of organizations, was also key to providing long-term food security to the communities through the growing of food and enhanced monitoring of the land. Issues of place, space and scale drive small differences in the food systems in these communities where access to, and availability of, different capitals shape food systems in different ways. However, having access to political capital, or decision-making authority over food and land resources, emerged as a critical capital that could develop, or spiral up, other capitals and shift conversations about food security towards issues of food sovereignty in the North. This research sheds light on the complex interactions of different capitals of community food systems and highlights the importance of place-based solutions as well as the need for regional cooperation and networks to address food security issues in the North.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".