Gathering, Governing, and Gifting Food: Community Economy and Food Distribution in the First Nation of Na-Cho Nyäk Dun
Bibliographic record
Abstract
This research with the First Nation of Na-Cho Nyäk Dun (NND) explores how customary food practices and potlatch traditions might inform community-oriented food distribution and food governance. Food and potlatch practices contribute to NND’s community economy – the everyday relationships, activities, and decisions that sustain people and land. Grounded in feminist and decolonial community-engaged methodologies, this thesis integrates diverse community economies, Indigenous food sovereignty, and gift economy concepts. Community interviews emphasize the multidimensional values of food. Food and potlatch traditions generate insights into healing multiple relations by focusing on community strengths and the power of food as a convener of people and place, of human and more-than-human, of knowledge and skills, and of past, present, and future generations. Strategic, community-informed recommendations are grouped into themes of gathering (with the land and together), governing (for well-being, rematriation, and a circular food economy), and gifting (to honour food and knowledge as sacred).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".