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Record W4413877775 · doi:10.1177/10806032251368754

Acceptance of Risk and Confidence Assessing Avalanche Terrain and Conditions: A Large Cross-Sectional Study

2025· article· en· W4413877775 on OpenAlexaboutno aff
Cameron C. Shonnard, Lingchen Wang, David C. Fiore

Bibliographic record

VenueWilderness and Environmental Medicine · 2025
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsCross-sectional studyConfidence intervalTerrainMedicineEnvironmental healthGeographyCartographyInternal medicinePathology

Abstract

fetched live from OpenAlex

IntroductionThe COVID-19 pandemic affected the ski industry globally, including limiting access to ski resorts and prompting more skiers and snowboarders to explore the backcountry. In this study, we quantified the willingness to take risks (risk propensity) and self-perceived ability to assess hazards in the backcountry and to explore correlations between these factors.MethodsWe based our study on a previously reported data set gathered under the supervision of our senior author, who collected anonymous responses to a 29-question online survey completed by 4792 self-identified backcountry skiers and snowboarders (aged ≥18 yr) in the United States and Canada. The survey was distributed primarily through regional avalanche centers, education providers, and skiing organizations. Pearson correlation coefficients and multivariable linear regression models were used to analyze associations among variables. More specifically, we examined the relationships among confidence in assessing avalanche terrain and willingness to take risks, level of avalanche training, years of experience, and days per season of backcountry skiing.ResultsWe identified a positive correlation between confidence in assessing avalanche terrain and willingness to take risks, level of avalanche training, years of experience, and days per season of backcountry skiing. Female respondents demonstrated lower risk willingness and self-reported ability to assess avalanche risk compared to males. Over 30% of individuals lacking level 1 avalanche training expressed confidence in appraising complex terrain. Our findings demonstrated a positive correlation between greater risk propensity, formal avalanche education, and increasing confidence in assessing avalanche terrain. However, we also observed concerningly high confidence levels among skiers with minimal or no training.ConclusionsAvalanche education should focus on aligning skiers' confidence with their actual abilities to reduce overconfidence and enhance safety. We recommend that future research aim to include a more diverse sample, especially those less engaged in formal avalanche education.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.022
GPT teacher head0.390
Teacher spread0.368 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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