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Record W3036452420 · doi:10.1108/ijtc-02-2020-0025

Formula 1, city and tourism: a research theme analyzed on the basis of a systematic literature review

2020· article· en· W3036452420 on OpenAlexaff
Romain Roult, Denis Auger, Marie-Pierre Lafond

Bibliographic record

VenueInternational Journal of Tourism Cities · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversité du Québec à Trois-Rivières
Fundersnot available
KeywordsOriginalityTourismTheme (computing)Value (mathematics)Field (mathematics)Scientific literatureSociologyRelation (database)Perspective (graphical)EpistemologyManagement scienceSocial scienceComputer sciencePolitical scienceQualitative researchEngineeringMathematicsLaw

Abstract

fetched live from OpenAlex

Purpose This paper aims to draw up the state of scientific knowledge in the field of Formula 1 with relation to tourism and urban studies. Design/methodology/approach This study is based on a systematic review of the scientific literature regarding this issue. Using targeted keywords and the analysis of various documentary databases, 8,075 references were identified and 40 documents were analyzed in an exhaustive manner. Findings This study presents a very nuanced portrait of the urban and tourism impacts of Formula 1 on the host territories. In many of the studies analyzed, a gap may be noted, sometimes flagrant, between the development goals of the promoters of these mega-events and local realities. This study also highlights the fact that Formula 1 has established itself as a sports events industry that can renew and enhance the brand image of certain cities. Originality/value Very few recent studies have exhaustively reviewed the scientific literature published in English and French with regard to the field of Formula 1 from a tourism and urban perspective. This study makes it possible to identify the main analytical findings and research perspectives resulting from this scientific work while discussing them using a theoretical framework related to the hypermodern character of different societies.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.590
Threshold uncertainty score0.368

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.124
GPT teacher head0.397
Teacher spread0.273 · 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 designNot applicable
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

Citations14
Published2020
Admission routes1
Has abstractyes

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