Bibliographic record
Abstract
Wildfire and flood events of recent years, including this year, have stretched and tested British Columbia’s Emergency Support Services (ESS) system, a provincial program designed by Emergency Management BC (EMBC) to support evacuees. After action reviews from the 2017 and 2018 wildfire and flood seasons, demonstrate ESS approaches fell short of providing fully adequate support to Indigenous communities. Building upon a Master’s thesis which was designed using Indigenous research methodologies and action research engagement principles, I asked the question: “How might emergency management practitioners braid cultural safety and a respect, honouring and celebration of Indigenous traditional knowledge, and community-based practices into ESS training and practices?” This article offers a summary of findings and recommendations for practical application for communities and emergency management organizations across the country. The findings include:
 Finding 1 was a theme related to the context and the current state of emergency services evacuations in 2020. This included the social and historical contexts, jurisdiction, and roles and responsibilities.
 Finding 2 focused on the participants’ perspectives of a definition of ‘Cultural Safety,’ which included the identification of specific competencies, a focus on trust-based relationships, and a connection to land.
 Finding 3 focused on the evacuation and registration process, including keeping families together, the use of community ‘navigators,’ (key individuals with knowledge of community protocol trusted by the community), and suggestions for reception centres in the process of registering evacuees.
 Finding 4 was about providing appropriate supports and services to evacuate communities, including providing traditional food, appropriate accommodation, transportation, language, culture and cultural protocols, and including pets.
 Finding 5 encompassed knowledge and training required for ESS professionals engaged in evacuation of communities. This included content for culturally relevant ESS training, which need to be codesigned and led by indigenous cultural navigators, as well as incorporating evaluation and public education.
 Finding 6 is on the theme of Planning and Preparedness, and includes subtopics of relationships, professional capacity, emergency and evacuation plans, personal preparedness and responder self-care and wellness.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.014 | 0.007 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.004 | 0.007 |
| Insufficient payload (model declined to judge) | 0.024 | 0.002 |
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".