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Record W2163658412 · doi:10.1177/0047287510382298

Motivations and Normative Evaluations of Summer Visitors at an Alpine Ski Area

2010· article· en· W2163658412 on OpenAlexafffundabout
Mark D. Needham, Rick Rollins, Robyn L. Ceurvorst, Colin Wood, Kerry E. Grimm, Philip Dearden

Bibliographic record

VenueJournal of Travel Research · 2010
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of VictoriaVancouver Island University
FundersMinistry of EnvironmentVancouver Island UniversityOregon State University
KeywordsNormativeGeographyNorm (philosophy)Cluster (spacecraft)Social psychologyPsychologyPolitical scienceComputer scienceLaw

Abstract

fetched live from OpenAlex

This article examines motivations of people visiting an alpine ski area in the summer season and their norms regarding acceptable and unacceptable trail conditions and densities of use at this area. Data were obtained from on-site surveys of summer visitors ( n = 422) at the Whistler Mountain ski area in British Columbia, Canada. Cluster analysis of several reasons for visiting revealed three groups ranging from a group who rated all motivation factors as most important to a group who only considered the alpine scenery as important. Norms were measured using evaluations of photographs depicting increasing trail widths and densities of sightseers/hikers and mountain bikers. Compared to the other two groups, the group who only considered the scenery important had lower normative acceptance of increasing densities of use and wider trails and had more norm crystallization or consensus about acceptable and unacceptable conditions. Research and management implications are discussed.

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)0.001
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.163
GPT teacher head0.487
Teacher spread0.324 · 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

Citations42
Published2010
Admission routes3
Has abstractyes

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