Why and How to Document the Traditional Food System in your Community: Report from Breakout Discussions at the 2017 Native American Nutrition Conference
Why this work is in the frame
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Bibliographic record
Abstract
Two conference breakout sessions at the 2017 Second Annual Conference on Native American Nutrition focused on the reasons and methods to document traditional food systems. The sessions included examples from 4 communities of Indigenous Peoples. A total of 60 participants discussed their thoughts and experiences within their communities on documenting traditional food systems. Some of the reasons, or “whys” for the documentation, included reinvigorating the culture to benefit the youth and those who had moved away from the community, preserving Elder knowledge, and increasing the ability to use the local plants. The methods, or “hows” of the documentation discussed included making sure the communities lead projects, protections are in place for the knowledge holders, and creating a contemporary feel for youth. Meeting transportation needs was paramount, as was creating a network of people and communities involved in documenting and reintroducing traditional food systems. This was exemplified by the diverse and experienced participants of these sessions and the associated conference.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 it