Indigenous food sovereignty: Pathways for Native scholars: Revitalizing Indigenous food systems through research and knowledge-sharing
Bibliographic record
Abstract
Introduction This inaugural column by the Indigenous Food Sovereignty Editorial Circle (IFSEC) in the Journal of Agriculture, Food Systems, and Community Development (JAFSCD) introduces a dedicated section of articles on Indigenous food sovereignty in partnership with First Nations Development Institute (First Nations). The column and the IFSEC reflect both our mission to work toward a more equitable and just food sys¬tem, and JAFSCD’s long-standing commitment to Indigenous food sovereignty, illustrated by the 2019 special issue on “Indigenous Food Sovereignty of North America.” An Indigenous-led editorial circle as part of JAFSCD, IFSEC uplifts Indigenous values and community food system aspirations in academic publishing. As an introduction to the IFSEC, this column will briefly outline the centrality of food, place, and learning in Indigenous lifeways, the main differences between Indigenous and Western approaches to the food system, and some thoughts on the role of Indigenous ways of knowing and being for the collective flourishing of humanity and all our relations, human and otherwise. The cycle of themes, along with other emergent topics related to Indigenous food systems, will thread throughout future columns. The current geographic focus includes the continental United States, Hawai’i, and Canada. The geographic scope is determined by the territorial affiliations of IFSEC members and may broaden to include other nations and regions over time.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.014 | 0.002 |
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".