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Record W2034332461 · doi:10.1080/16184742.2014.997772

Extending the benefits of leveraging cycling events: evidence from the Tour of Flanders

2015· article· en· W2034332461 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

VenueEuropean Sport Management Quarterly · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCyclingBusinessMarketingGeography

Abstract

fetched live from OpenAlex

Research question: This paper examines event leveraging for public health benefits with the outcome of increasing physical activity participation. While event leveraging provides the foundation for this research, social ecological theory is additionally applied to further examine how leveraging efforts can increase physical activity participation through an understanding of systems and targets. Research methods: An in-depth case study of the Tour of Flanders (Dutch: Ronde van Vlaanderen), Belgium's most popular annual cycling event, is conducted by using qualitative data from interviews and documents. Results and findings: Results reveal that community and sport event-related leverageable resources have been leveraged simultaneously through the strategic use of Flanders' cycling heritage to increase bicycle tourism and active participation in cycling in the region. The Village of the Tour and the Centennial Tour are discussed as two leveraging processes that occur at distinct social ecological systems, using different targets to promote cycling. Implications: The paper argues for greater cooperation between different levels of government operating in the advent of leveraging cycling events to extend the benefits of leveraging.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.496
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
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 head0.092
GPT teacher head0.307
Teacher spread0.215 · 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