Understanding exposure to avalanche terrain and avalanche information product use of snowshoers and winter hikers: Insights from Mount Seymour Provincial Park, British Columbia, Canada
Bibliographic record
Abstract
Snowshoeing and winter hiking have grown substantially in the last decade. To provide this community with better avalanche safety messages, it is critical to understand their existing avalanche awareness and safety practices. To address this knowledge gap, we conducted intercept interviews with snowshoers and winter hikers at a popular backcountry trailhead outside of Vancouver, British Columbia, Canada and surveyed students of introductory avalanche safety courses targeted at snowshoers. Study participants shared their typical trip destinations, which we used to determine their general exposure to avalanche terrain based on the Avalanche Terrain Exposure Scale (ATES). Despite the fact that all but one participant expose themselves to avalanche terrain, we found very low levels of avalanche awareness, formal training, and use of avalanche information products like the public avalanche forecast. Participants’ main reason for not using existing avalanche safety products and services was their belief that they do not expose themselves to avalanche terrain. This highlights that initiatives raising awareness of what constitutes avalanche terrain, how to recognize it and when it is safe to travel into are key starting points for improving avalanche safety practices in this community. Comparisons between study participants without formal avalanche safety training, current course students, and participants with training highlight the value of formal training and offer insights on potential pathways for raising avalanche awareness among snowshoers and winter hikers.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.012 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| 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".