COVID-19 and British Columbia’s volunteer search and rescue workers: risk recognition and risk mitigation
Bibliographic record
Abstract
Background: Early during COVID-19, British Columbia coordinated collaboration between academic researchers, public healthcare systems, and private sector partners to focus research resources on knowledge gaps in a timely manner, avoid duplication, and identify overlooked aspects. At a collaboration symposium, it became evident that BC's volunteer search & rescue (SAR) cadre was overlooked. Objective: Our exploratory project studied volunteer SAR's operational readiness; use and perceived value of information sources; consistency in infection prevention measures among volunteer stations, and with their professional counterparts for comparable first aid medical interventions throughout the pandemic. Methods: We partnered with the 2 organizations that govern BC's volunteer SAR stations. Local station leaders completed a short confidential survey. Guidance documents issued by associations governing voluntary and professional first responders were compared. Results: Survey responses were received from 33 of 109 local stations, spanning all regions of BC. Most remained operationally ready throughout the entire pandemic (12.1% had to stand down at times). Except for 21% lacking eye protection, all had personal protective equipment commensurate with that of healthcare professionals; however, few used this PPE in a manner consistent with professional counterparts. Usage and perceived usefulness of various information sources differed. There was no communication link between the province's infection control experts and 2 volunteer SAR organizations. Conclusions: Search & rescue capability was maintained despite pandemic impacts. Results reveal strengths and opportunities for improvement in the ways volunteers are informed and protected. Infection control experts providing advice for emergency health services professional responders should remember to include their volunteer counterparts.
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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 | 0.012 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".