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Record W4210671700 · doi:10.1108/tr-04-2021-0215

Overcoming overtourism: a review of failure

2022· review· en· W4210671700 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

VenueTourism Review · 2022
Typereview
Languageen
FieldSocial Sciences
TopicDiverse Aspects of Tourism Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsTourismOriginalityControl (management)LimitingValue (mathematics)BusinessMarketingPublic relationsPolitical scienceManagement scienceEconomicsComputer scienceEngineeringManagement

Abstract

fetched live from OpenAlex

Purpose The purpose of this paper is to identify and review attempts at mitigation and prevention of overtourism and to outline reasons for the failure to date of such efforts. Design/methodology/approach This paper is a perspective paper and draws on an examination of relevant literature on the subject through the lens of a conceptual framework. It outlines the changing roles of tourism development and marketing organisations and the failure of public sector agencies to control and manage tourism. The varying methods of limiting tourist numbers are examined, and their weaknesses are presented. Findings Conclusions reveal that there are a series of global trends that are contributing to the appearance and continuation of overtourism and which, to date, are proving immune to mitigation and resolution for specific reasons. These include a lack of willingness to accept the problem of tourist numbers and to reduce or effectively manage these at all levels, from local to international. Research limitations/implications Present approaches to mitigation need to be revisited and better integrated with management and control of all aspects of development and framed to achieve and retain political support at all levels. Originality/value There has been little attempt before to analyse the reasons for the failure to effectively mitigate or prevent overtourism, and this paper makes an original contribution in this area in that it is an evaluation of what is known and a summary of shortcomings within the industry and academia.

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)0.008
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.389
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.003
Bibliometrics0.0000.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0030.001
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0580.001

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 head0.095
GPT teacher head0.423
Teacher spread0.328 · 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