Doing research together: wasdi ( Allium tricoccum ) plants guide dynamic research collaborations in Cherokee landscapes
Bibliographic record
Abstract
Research on harvesting culturally significant food plants can contribute to Indigenous food sovereignty. Relationships drive the process of research, which can affect research methodologies and outcomes. Promoting inclusion and equity in research relationships is necessary to reduce power hierarchies that often position conventional sciences above Indigenous knowledge systems. This paper employs a reflexive lens to consider important dynamics of an ongoing research collaboration between the Eastern Band of Cherokee Indians, federal agencies, and academic partners focused on the Cherokee food plant ᎤᏩᏍᏗᎭ [transliterated as uwasdiha or wasdi and also recognized as ramps or Allium tricoccum]. An aim of our paper is to contribute to our collective understandings of Indigenous research methodologies (IRM) and collaborative research. Through iterative, place-based conversations and thematic analysis we identify and discuss our process engaging in trust building and relationality as co-authors. Key themes emerging from our work include the importance of (1) developing relationships when conducting collaborative research across multiple knowledge systems and (2) Indigenous food narratives that center traditional foods in research and relationships.
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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 | 0.016 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.021 | 0.020 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| 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".