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Record W4366517561 · doi:10.1080/23750472.2023.2200491

Innovations in global sports brand management: the case of FC Barcelona’s Barça Museum

2023· article· en· W4366517561 on OpenAlexaff
Andrew Webb, Amélie Cloutier, François Brouard

Bibliographic record

VenueManaging Sport and Leisure · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversité du Québec à MontréalCarleton University
Fundersnot available
KeywordsCorporate social responsibilityClubFoundation (evidence)Value (mathematics)Asset (computer security)Scale (ratio)BusinessPublic relationsMarketingManagementPolitical scienceGeographyComputer scienceCartographyEconomics

Abstract

fetched live from OpenAlex

Purpose Ongoing improvements in sports management, marketing, fan experience, as well as corporate social responsibility (CSR) must be implemented by professional team sport organisations (PTSO). Yet, little is known about how and why PTSOs account for the impacts of their CSR initiatives.Design This case study analyses a one-of-a-kind sport for development museum. Curated by FC Barcelona’s Barça foundation, this innovative museum was designed to showcase, and account for, Barça’s social impacts.Findings Four main sections of the Museum are leveraged to translate the claim that Barça programs provide positive social impact.Research Contribution This paper illustrates how a museum becomes a significant asset for convincing and activating both fans of a PTSO as well as sponsors of a sport-related foundation.Practical Implications This study invites CSR practitioners to reflect about innovations in how they account for the impact of their programs.Value How this unique SfD museum contributes to FC Barcelona’s efforts of becoming més que un club, or more than a club – and therefore allowing FC Barcelona to escape market logic on a planetary scale – is also discussed.

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)0.001
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 score0.234
Threshold uncertainty score0.715

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
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 head0.019
GPT teacher head0.305
Teacher spread0.286 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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