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Record W2889576113 · doi:10.1177/106169341202100106

The Role of Mega-Sports Event Interest in Sponsorship and Ambush Marketing Attitudes

2012· article· en· W2889576113 on OpenAlex
Eric MacIntosh, John Nadeau, Benoît Séguin, Norm O’Reilly, Cheri L. Bradish, David Legg

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSport Marketing Quarterly · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsMount Royal UniversityBrock UniversityNipissing University
Fundersnot available
KeywordsMega-Sports marketingAmbush marketingAdvertisingEvent (particle physics)MarketingBusinessPolitical scienceMarketing managementRelationship marketing

Abstract

fetched live from OpenAlex

Sponsorship of mega-sports events continues to be one of the most popular forms of marketing. The international appeal and reach of the Olympic Games, in particular, is amongst the top advertising and sponsorship opportunities in the world for international branding. In turn, the marketing value provided by the Olympic Games has attracted the interest of multiple sponsors in various categories, leading to competitive hosting bids and ambush marketing. This study examined mega-sports event interest as a determinant of sponsorship and ambush marketing attitudes, as well as the purchase intention of affiliated properties during the 2010 Vancouver Olympic Winter Games. In total, 619 consumer surveys were collected from four different Canadian cities. Results showed that overall consumer interest was high, and that their purchase intention was strongly influenced by level of interest.

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)0.026
metaresearch head score (Gemma)0.001
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 score0.080
Threshold uncertainty score0.915

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0260.001
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)0.0000.000

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 head0.022
GPT teacher head0.294
Teacher spread0.272 · 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