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Record W2586447965 · doi:10.1177/1354816616656273

How to quantify and characterize day trippers at the local level

2017· article· en· W2586447965 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.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueTourism Economics · 2017
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
FundersUniversity of Waterloo
KeywordsTourismTRIPS architecturePhenomenonRelevance (law)Work (physics)Order (exchange)Regional scienceGeographyComputer scienceOperations researchBusinessTransport engineeringPolitical scienceEngineering

Abstract

fetched live from OpenAlex

This article presents a methodology for the operational definition, quantification and characterization of day trippers, for use at the local or regional levels. The methodology stresses the importance of such concepts as ‘daily urban systems’, ‘functional areas’, ‘travel-to-work areas’ and other similar aggregations to define what is one of the main features of tourism: ‘usual environment’. Different systems are developed for the quantification of day trippers, based on both primary (fieldwork) and secondary data, and we apply both to the case of a comarca in the Province of Barcelona (Catalonia). The results show the relevance of the phenomenon of ‘same-day trips’ (for tourism) and the interest for defining and characterizing this phenomenon correctly in order to implement tourism policies that address the different profiles presented by day trippers.

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 categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.060
GPT teacher head0.223
Teacher spread0.164 · 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