MétaCan
Menu
Back to cohort

Understanding Brand Associations of Preferred Minor Hockey Tournaments From the Parents' Perspective

2018· article· en· W2802096382 on OpenAlexaboutno aff
Daniel Wigfield, Chris Chard

Bibliographic record

VenueEvent Management · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsTournamentMarketingAdvertisingCompetition (biology)LadderingIce hockeyPerspective (graphical)BusinessPublic relationsPolitical scienceComputer scienceMathematics

Abstract

fetched live from OpenAlex

Hosting tournaments and other hockey-related activities have been hailed as important drivers of tourist dollars for many regions across Canada. The competition to attract teams to participate in tournaments, which benefit the tournament organizers and the communities in which they reside, is considerable. Consequently, the purpose of the study was to identify the characteristics of a preferred tournament experience from the perspective of representative (rep) hockey parents from Ontario's Greater Golden Horseshoe Region. Specifically, these characteristics were considered through a brand management lens by focusing on brand associations related to tournament offerings. To investigate the current study, 30 interviews were conducted using a laddering interview technique. Findings indicate that there are four attributes that influence a tournament brand including: competition, tournament operations, accommodations, and travel requirements. Further, six benefits derived from these attributes emerged: bonding, fun, parity, value, life skills, and time management.

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)0.002
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 score0.076
Threshold uncertainty score0.150

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.189
GPT teacher head0.374
Teacher spread0.185 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueEvent ManagementSame topicSport and Mega-Event ImpactsFrench-language works237,207