Site‐specific encounters, norms and crowding of summer visitors at alpine ski areas
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.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".