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Record W2116317216 · doi:10.1504/ijsmm.2008.015965

Dangerous liaisons: how can sports brands capitalise on the Hip Hop movement

2007· article· en· W2116317216 on OpenAlexaff
Barbara Manivet, André Richelieu

Bibliographic record

VenueInternational Journal of Sport Management and Marketing · 2007
Typearticle
Languageen
FieldArts and Humanities
TopicMusic History and Culture
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHop (telecommunications)Hip painBusinessAdvertisingMarketingPublic relationsOperations managementEngineeringTelecommunicationsPhysical therapyPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Hip Hop represents an important development potential for professional sports teams and equipment makers. This article examines the literature on diffusion and adoption processes, which stresses the ongoing adjustment of Hip Hop culture, the challenges, opportunities and constraint factors a professional sports team or an equipment maker should consider when approaching Hip Hop. Hip Hop requires authenticity and preaches different values from those of the sports fans. Therefore, we recommend a bipolar strategy with a set of operational actions directed at Hip Hop, on one hand, and team core fans on the other, together with a 'buffer' zone for the mass market.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.715
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.204
Teacher spread0.190 · 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.

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

Citations4
Published2007
Admission routes1
Has abstractyes

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