MétaCan
Menu
Back to cohort
Record W2171786117 · doi:10.1177/0047287510379161

An Integrative Model of Place Image

2010· article· en· W2171786117 on OpenAlex

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.

Bibliographic record

VenueJournal of Travel Research · 2010
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsCarleton UniversityUniversity of Guelph
Fundersnot available
KeywordsTourismStructural equation modelingImage (mathematics)Product (mathematics)MarketingDestination imageAdvertisingKey (lock)PsychologyBusinessDestinationsComputer scienceGeographyComputer visionMathematics

Abstract

fetched live from OpenAlex

To advance place image theory, this study combines elements from two areas that have explored place image more than any others: tourism destination image (TDI) and product-country image (PCI). Key constructs from each are measured simultaneously in an Integrative Model of Place Image. The model test uses consumer survey data from South Korea to compare image measures of the United States and Japan using structural equation modeling. The results reveal that cognitive country image has greater influence on product factors than on destination factors, while affective country image has greater influence directly on receptivity than indirectly on beliefs. In addition, consumer beliefs exhibit a strong crossover effect between product beliefs and destination receptivity. Newly tested relationships point to a number of directions for future research in place image and branding, and provide empirical evidence of the need for place marketers to move toward greater integration between product- and tourism-oriented place image campaigns.

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)0.012
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.495
Threshold uncertainty score0.921

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0020.000
Research integrity0.0000.002
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 head0.096
GPT teacher head0.476
Teacher spread0.380 · 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