Principles of care: Indigenous land stewards’ motivations in protecting land and food systems in British Columbia
Bibliographic record
Abstract
Indigenous land stewards hold unique roles and responsibilities in relation to the land and employ traditional ecological knowledges to protect the land’s health and longevity, supporting Indigenous self-determination and food sovereignty. This research explored Indigenous land stewards’ motivations in caring for the land and how their work is an expression of love and care. Conversational interviews were held with twelve Indigenous land stewards residing in British Columbia, who discussed their roles and responsibilities through oral storytelling. The findings revealed six key themes: land, good relations, and reciprocity; learning, sharing, and healing; spirituality and ceremony; love and care; Indigenous food sovereignty; and resistance against colonial structures. Participants articulated a profound interconnectedness with the land, emphasizing reciprocal relationships, spiritual practices, and a commitment to food sovereignty as being central to their roles. Participants also highlighted the importance of advocating for the well-being of the land and Indigenous communities in the ongoing struggle against harmful colonial practices including resource extraction and industrial developments. These themes collectively highlight the collaborative and committed nature of their work, with a goal of protecting and nurturing the land for future generations.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.020 | 0.011 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".