Shifting narratives, recognizing resilience: new anti-oppressive and decolonial approaches to ethnobotanical research with Indigenous communities in Canada
Bibliographic record
Abstract
Revitalizing Indigenous land-based practices is an act of resurgence and resistance. The presence of Indigenous bodies occupying land to nourish and strengthen themselves through ancestral practices is a political act. These cultural systems of knowledge and practice are in opposition to historical and ongoing colonial attempts to dispossess Indigenous Peoples of their connections to land. Indigenous People have undergone changes in diet and land access, including cultivating and harvesting plants for health and wellbeing. Recognizing and understanding the impacts and implications of colonization on land-based knowledge is fundamental in carrying out meaningful work within Indigenous communities in the field of ethnobotany. Much of the literature and media on Indigenous issues continue to uphold trauma narratives. When working with Indigenous communities on projects, it is essential to understand the history, impacts, and ongoing struggles related to colonization and genocide in America to not cause harm and to contribute positively to these communities. Furthermore, by taking our responsibilities one step further, we can carry out research in trauma-informed ways while prioritizing anti-oppressive, decolonial, and strength-based approaches to our research and collaborations with Indigenous communities. We illustrate these points through a community-based case study from the Squamish Nation in British Columbia, Canada.
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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 | 0.012 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.061 | 0.047 |
| Scholarly communication | 0.014 | 0.005 |
| Open science | 0.004 | 0.016 |
| Research integrity | 0.002 | 0.005 |
| 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".