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La relation client-fournisseur dans le contexte des grands événements sportifs : le cas des Jeux Olympiques

2013· article· fr· W2183684179 on OpenAlexaffabout
André Tchokogué, Marie-Pier Hébert, Jean Nollet, Laurence Beaulieu

Bibliographic record

VenueLogistique & Management · 2013
Typearticle
Languagefr
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsHEC Montréal
Fundersnot available
KeywordsHumanitiesPolitical scienceArt

Abstract

fetched live from OpenAlex

En s’appuyant sur le cas des Jeux Olympiques de Vancouver en 2010, cette étude apporte un éclairage sur la nature des liens de dépendance entre un comité organisateur d’un grand événement sportif (GéS) et ses fournisseurs. Plus spécifiquement, elle montre que le comité organisateur de chaque GéS se retrouve généralement au centre d’un réseau de relations important (de par le nombre des fournisseurs-commanditaires et la nature des liens de dépendance de la relation client-fournisseur) et que pour pouvoir les gérer de manière efficace, les gestionnaires doivent mettre en œuvre les mécanismes de coordination appropriés.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.789
Threshold uncertainty score0.425

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0090.006
Scholarly communication0.0060.001
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.050
GPT teacher head0.326
Teacher spread0.276 · 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 designQualitative
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".

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Citations0
Published2013
Admission routes2
Has abstractyes

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