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Record W2068939128 · doi:10.1080/01490400701881465

Trend Analysis of Motivation-Based Clusters at the Chilkoot Trail National Historic Site of Canada

2008· article· en· W2068939128 on OpenAlex
Anne-Marie Legaré, Wolfgang Haider

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueLeisure Sciences · 2008
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsVisitor patternCluster (spacecraft)Principal component analysisGeographyPsychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

This study combines data from three cross-sectional surveys (1993, 1998, and 2004) to explore how hikers at the Chilkoot Trail National Historic Site of Canada were affected by the introduction of several restrictive management policies. The analysis revolves around motivation-based segments defined via one single principal component and cluster analysis over all three years of data. The results document similarities and differences between the three motivation-based segments over time and as a reaction to the restrictions. Clusters also differed in the reaction to indicator variables such as advance booking time, perceived management problems, encounters, and satisfaction. Future longitudinal data collections and investigations as part of visitor monitoring protocols are suggested.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.350
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.038
GPT teacher head0.277
Teacher spread0.239 · 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