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Record W4403947632 · doi:10.1080/08865655.2024.2415026

Multilayered Borders as a Method for Studying Tourism Destinations: A Case of Northern European Border Regions

2024· article· en· W4403947632 on OpenAlexvenueno aff
Eeva‐Kaisa Prokkola, Dorte Jagetić Andersen, Fredriika Jakola, Tomas Nilson, Sara Svensson

Bibliographic record

VenueJournal of Borderlands Studies · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicCross-Border Cooperation and Integration
Canadian institutionsnot available
Fundersnot available
KeywordsTourismDestinationsEconomic geographyRegional scienceTourist destinationsGeographyPolitical scienceBusinessInternational tradeEconomyEconomicsArchaeology

Abstract

fetched live from OpenAlex

The article problematizes tourism destination development in the European borderlands of Denmark–Germany, Sweden–Denmark and Sweden–Finland, where border crossing has been relatively free for decades, except for the time of Covid-19 pandemic border restrictions in 2020–2021. The research contributes to border studies and tourism studies by developing a framework for analyzing tourism destinations through the prism of the multilayered border, with a focus on destination images, attractions, and hosts. The reseach complements previous studies on tourism development and cross-border partnership in the European Union territory by investigating multiple tourism destinations in the border regions and by contemplating to what extent borders form a resource for destination promotion in the aftermath of the pandemic. The examination of regional tourism development through the prism of borders informs us about the compatibility of the idea of a “borderless” Europe with border region “realities.”

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 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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.440
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.073
GPT teacher head0.470
Teacher spread0.398 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations2
Published2024
Admission routes1
Has abstractyes

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