Site‐specific encounters, norms and crowding of summer visitors at alpine ski areas
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
Abstract Operating chairlifts at alpine ski areas during the summer to accommodate tourism and recreation activities (e.g. hiking and mountain biking) is increasing in popularity. Increasing summer use, however, may affect the ability of ski areas to sustain acceptable social conditions (e.g. crowding). In addition, little is known about encounters, crowding or acceptable use levels at ski areas during the summer. This article addresses these issues using data from surveys of summer visitors ( n = 548) conducted at five separate sites in the Whistler Mountain ski area in British Columbia, Canada. Photographs and Likert‐type scales measured visitors' encounters with others, perceived crowding and acceptance of use levels. Results showed that: (i) crowding and encounters differed among the sites; (ii) visitors at the backcountry sites rated encounters as less acceptable and possessed greater agreement regarding acceptable encounter levels compared with visitors at the more accessible sites; (iii) crowding and encounters were important indicators of summer use at each site; and (iv) visitors who felt more crowded encountered more people than their normative tolerances. Explanations for these findings and implications for managers and researchers are discussed. Copyright © 2004 John Wiley & Sons, Ltd.
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.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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