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Record W2062507696 · doi:10.5367/0000000041895030

Tourist Typology: An Ex Ante Approach

2004· article· en· W2062507696 on OpenAlex
Antoine Zalatan

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

VenueTourism Economics · 2004
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTourismTypologyEx-anteMarketingSet (abstract data type)Factory (object-oriented programming)BusinessAdvertisingEconomicsComputer scienceGeography

Abstract

fetched live from OpenAlex

A tourist typology based on an ex ante rather than an ex post approach is proposed and examined. An ‘ex ante’ tourist classification can facilitate the planning process and provide a basis for tourism marketing. Five conceptual tourist classifications were formulated. Two samples (N = 615, 1997) and (N = 528, 2002) were used to test the proposed classification. The ‘social tourist’ classification (goes where friends, family and neighbours go) captured over 45% of the tourist classifications, followed by the ‘conventional tourist’ (19.8%, relies largely on the services of a travel agent), the ‘marketing tourist’ (17.5%, goes to places that are widely advertised), the ‘planning tourist’ (10.7%, plans all aspects of the vacation trip in detail), and finally the ‘impulsive tourist’ (6.1%, decides on the spur of the moment). The respondents' classifications were also confirmed by a separate set of data (20 questions) which describe each tourist category. The validity of the theoretical tourist typology was tested by a ‘confirmatory factory analysis’ to ensure that the conceptual model and the 20 questions were compatible.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.451
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.319
Teacher spread0.281 · 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