Cooperative community wildfire response: Pathways to First Nations’ leadership and partnership in British Columbia, Canada
Bibliographic record
Abstract
With the growing scale of wildfires, many First Nations are demanding a stronger role in wildfire response. Disproportionate impacts on Indigenous communities (including First Nations, Métis, and Inuit) in Canada are motivating these demands: although approximately 5 % of the population identifies as Indigenous, about 42 % of wildfire evacuation events occur communities that are more than half Indigenous. In what is now known as British Columbia, Canada, new pathways for cooperative wildfire response between First Nations and provincial agencies are emerging. Drawing from semi-structured interviews with 15 experts from First Nations communities and agencies, and a review of 42 documents on wildfire response, our research highlights the diverse existing capacities, priority opportunities, and processes required to enhance cooperative pathways. Within First Nations communities, existing capacities include local knowledge, firefighting experience, equipment, funding, relationships, and leadership – an overlooked but fundamental capacity. Priority opportunities include ways to build capacity within and beyond wildfire response, such as fully equipped response crews, full-time year-round wildfire management crews, Emergency Management Coordinators, First Nations Liaisons, and cross-trained wildland and structural crews. Translating existing capacities into priority opportunities requires an ongoing focus on cooperative processes, including relationship-building, respecting Rights and Title, streamlining funding, and enabling “cultural safety” to overcome racism. These cooperative pathways can help transform wildfire governance toward First Nations-led partnerships.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".