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Record W4399877431 · doi:10.1080/07053436.2024.2368672

The influence of stadium renovations on the ambiance perceived by soccer audiences: the case of the Maracanã stadium in Rio de Janeiro

2024· article· en· W4399877431 on OpenAlexvenueno aff
Natália Rodrigues de Melo, José Chaboche

Bibliographic record

VenueLoisir et Société / Society and Leisure · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsStadiumAdvertisingGeographyBusinessMathematics

Abstract

fetched live from OpenAlex

Carrying a triple economic, social, and political dimension, the ambiance of a football stadium is an essential intangible asset as a cultural heritage. It is a subject of conflicts of use between organizations in the sports-spectacle sector and supporters. This article aims to analyze the impact of the renovations carried out in Maracanã Stadium, which took place from 1999 to 2014, on the ambiance experienced by cariocas clubs’ public. An ethno-topographic study was conducted, involving participant observation of 15 matches and 26 individual active non-directive interviews with spectators, to design a mnemonic archive of Maracanã. Through exploring the memories of the public, this research reveals five categories of metaphors that hold significance in describing the ambiance experienced and perceived before and after the renovations. These renovations, not only alter the ambiance of the stadium but are universally experienced as an urban trauma, compromising the re-appropriation of this public space by its users.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0080.011
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.022
GPT teacher head0.332
Teacher spread0.310 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2024
Admission routes1
Has abstractyes

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