Know before you go! A field survey of the preparedness of wilderness day hikers and trail runners in Rocky Mountain National Park
Bibliographic record
Abstract
Abstract Introduction Actively recreating in natural environments enhances physical and mental health, but also carries risk. We aimed to characterize wilderness day hikers and trail runners, and examine factors that predict preparedness. Methods We conducted a cross-sectional survey in 4 distinct areas of Rocky Mountain National Park (RMNP) in Colorado during June-August of 2024. English-speaking adults returning from a day hike or trail run were invited to participate. We classified visitors as ‘prepared’ based on the gear they reported carrying. Results Of 801 potential participants approached, 586 (82.3%) day hikers and 68 (76.4%) trail runners agreed to participate. The overall average age was 40.7 years (range 18-82); 50.1% were female; and most common state of residence was Colorado (47.3%). Day hikers tended to be older, travel in larger groups, and spend fewer days in the wilderness per year while trail runners reported higher levels of experience and wilderness preparedness, and were more likely to experience ‘close calls’. A minority of participants met our definition of wilderness prepared, about half were altitude prepared, and approximately a quarter did not tell anyone where they were going and when they expected to return. Several measures of experience were associated with preparedness. Conclusions Both equipment and knowledge are important for safely enjoying and leaving wilderness settings. Yet many wilderness users in RMNP did not meet our definition of adequate preparation, especially those with less experience. Additional efforts to increase the proportion of wilderness day-users who are prepared may help further improve visitor safety.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".