How and Why Indigenous Peoples are Engaged in Wildland Fire Management
Bibliographic record
Abstract
Little is known about how and why Indigenous peoples are engaged in wildland fire management particularly in the areas of wildfire prevention, mitigation, preparedness, response, and recovery abilities in the event of a threatening wildfire. This qualitative study explored how and why Indigenous peoples in six case study jurisdictions in Canada and New Zealand are engaged with government fire management agencies in wildfire management, barriers to engagement, and identifies opportunities to increase engagement between governments and Indigenous peoples. This research used a qualitative research approach with a case study design. Twenty-nine participants were interviewed from Canada and New Zealand, including in the provinces of British Columbia, Saskatchewan, Ontario, and Nova Scotia, as well as the Northwest Territories. Findings indicate that engagement between government fire management agencies and Indigenous peoples predominantly occurs when agencies respond to a wildland fire affecting Indigenous land and in the employment of Indigenous peoples. The key barriers identified by Indigenous leaders were a lack of trust towards the government, and limited financial support by the federal government that would allow Indigenous communities the ability to hire staff to support emergency management including engagement, as well as the fire suppression equipment needed to respond to wildfires in or near their community. Government participants indicated that a lack of funding to hire the appropriate amount of staff to support engagement with Indigenous communities as a barrier, as was a lack of Indigenous cultural awareness and history in government staff, and the lack of clarity around the roles and responsibilities of the multiple agencies involved during emergency response. Recommendations for increasing engagement are provided. This research concludes with a way forward for both Indigenous and government leaders that can enhance their relationship.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.009 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".