Generations of gardeners regenerating the soil of sovereignty in Moose Cree First Nation: An account of community and research collaboration
Bibliographic record
Abstract
The challenges northern remote communities in Canada face acquiring regular access to affordable and healthy food have been well documented. Our Indigenous Health Research Group, made up of an informal network of researchers from universities across Canada, has partnered with northern communities, Tribal Councils, and Political organizations (Assembly of First Nations, Nishnawbe Aski Nation) in Yukon, Northwest Territories, British Columbia, and Ontario since 2004 to document and support local land-based food strategies to increase local food capacity. While much of this work has focused on supporting traditional food harvesting efforts, many community partners are seeking to develop small-scale gardening to increase access to fresh fruit and vegetables. As part of a five-year project supporting local food initiatives in four communities in northern Canada (Northwest Territories and northern Ontario), we worked with the Moose Cree First Nation in Moose Factory, Ontario and their local Food Developer to support food sustainability planning. The research presented in this article describes collaborative efforts between Moose Cree First Nation Band Council leadership, community members, and our research group in support of local garden development as part of their local food sustainability strategy. With the guidance and engagement of community, we worked with families in Moose Factory to build and plant family-centered gardens. The article focuses on start-up engagement strategies, garden uptake, garden construction and planting activities, garden yields, and individual feedback from gardeners describing their experiences with the project.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.042 | 0.014 |
| Scholarly communication | 0.009 | 0.006 |
| Open science | 0.002 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| 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".