Demographic differences in hiker cellular technology use in backcountry areas in Montana’s Custer Gallatin National Forest
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Technology remains an important part of outdoor recreation, ranging from the introduction of lighter materials in gear to new gadgets that improve the outdoor experience. Recently, advances in cellular technology and mobile devices have presented new opportunities for using mobile technology in backcountry areas. Applications ranging from public lands apps to GPS apps are a now a common find in outdoor recreation areas. Use of mobile technologies, such as cellular phones, can differ by demographic variables such as sex, age, and income. This presents a valuable opportunity to explore how and why demographics may shape the use of cellular devices while in the backcountry. This study examines technology use among hikers in Montana’s Custer Gallatin National Forest. Using data from an online survey, the researchers explored the importance of eight different uses of cellular technology while in the backcountry and analyzed how these responses vary by sex, age, income, and education categories. The results indicate cellular technology plays a varied, albeit often neutral or even unimportant, role in backcountry outdoor recreation situations. Notably, these experiences do vary by age, education, and income categories but, surprisingly, not sex. Important outcomes include new understanding of hiker use of cellular devices as cameras, wayfinding devices, and for information gathering while in the backcountry.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it