How Mountain Snowmobilers Adjust Their Riding Preferences in Response to Avalanche Hazard Information Available at Different Stages of Backcountry Trips
Bibliographic record
Abstract
ABSTRACT: Over the last five winters, mountain snowmobilers accounted for 53 % (41 of 77) of all rec-reational avalanche fatalities in Canada, which is a significant increase from the 28 % (18 of 64) during the previous five winters. This trend clearly highlights the need for the Canadian avalanche community to im-prove avalanche awareness among this user group. Creating an in-depth understanding of the perspec-tives, needs and challenges of mountain snowmobilers is an important first step in the development of more appropriate risk communication and prevention strategies. This paper presents preliminary results from an extensive online survey on mountain snowmobiling and avalanche awareness that was conduct-ed in British Columbia during the 2011/2012 winter season. The survey included a series of discrete choice experiments, a stated preference technique, to examine how snowmobilers adjust their riding preferences as new avalanche hazard information becomes available during different stages of typical backcountry trips. The analysis revealed that participating snowmobilers interpret danger ratings on a lin-ear scale and that the presence of a persistent avalanche problem does not affect their riding choices. Furthermore, under increasing avalanche danger, snowmobilers first gravitate towards areas with higher snowmobile traffic before they avoid complex and challenging avalanche terrain. The analysis also showed that instability observations (i.e..whumpfs) affect riding choices more than other relevant observa-tions. The results of this study can help to develop evidence-based avalanche safety initiatives that effec-tively target existing weaknesses in the avalanche safety behavior of mountain snowmobilers.
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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 | 0.000 | 0.000 |
| 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".