MétaCan
Menu
Back to cohort
Record W2056403601 · doi:10.3727/152599507783948675

A Comparative Approach to Analyzing Local Expenditures and Visitor Profiles of two Wildlife Festivals

2006· article· en· W2056403601 on OpenAlexaffabout
Glen T. Hvenegaard, Varghese Manaloor

Bibliographic record

VenueEvent Management · 2006
Typearticle
Languageen
FieldPsychology
TopicRecreation, Leisure, Wilderness Management
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsVisitor patternPopularityWildlifeDemographicsContext (archaeology)GeographyTourismWildlife tourismAdvertisingMarketingEcotourismBusinessSociologyPsychologyDemographyEcologySocial psychology

Abstract

fetched live from OpenAlex

Wildlife festivals are growing in popularity and warrant additional studies of festival visitors. However, comparisons of visitor demographics, motivations, activities, and local expenditure patterns between festivals are difficult because different methods of measurement are used. By using a comparative approach, this study evaluates, with the same methods, the visitor characteristics of two similar wildlife festivals in Western Canada. While providing site-specific context, this study notes variations in total local expenditure patterns, visitor motivations, and visitor activities that result from, in part, different visitor demographics, activities offered, other attractions, and rates of overnight stays. Visitors to these festivals were slightly older and had higher educational levels than the general public, which was consistent with visitors to other wildlife festivals and ecotourists in general.

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)0.003
metaresearch head score (Gemma)0.007
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 score0.042
Threshold uncertainty score0.084

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.005
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.333
Teacher spread0.310 · 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

Citations11
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueEvent ManagementSame topicRecreation, Leisure, Wilderness ManagementFrench-language works237,207