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Record W2783372898 · doi:10.1080/01490400.2017.1408511

The Influence of Corporate Social Responsibility and Team Identification on Spectator Behavior in Major Junior Hockey

2018· article· en· W2783372898 on OpenAlexaff
Kristen A. Morrison, Katie Misener, Steven E. Mock

Bibliographic record

VenueLeisure Sciences · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsIdentification (biology)Corporate social responsibilityPerceptionPsychologyPublic relationsSpectator sportOrder (exchange)Social psychologyAdvertisingBusinessPolitical science

Abstract

fetched live from OpenAlex

Sport spectatorship is a predominant leisure activity for many individuals who invest considerable time, discretionary income, and emotional energy in their teams. As a result, spectators are becoming more discerning about different aspects of their fan experience and extending their awareness and evaluation of a team's efforts beyond the main sport spectacle. This study builds on previous research on corporate social responsibility (CSR) in sport, which has found that spectators express their opinion of an organization's ethics and practices, such as their CSR programs, through their actions and spending. In order to understand the mechanism behind this, the current study examines the role of team identification as a potential mediator between spectators' perceptions of a Major Junior Hockey team's CSR initiatives and their patronage behaviors. The results show that team identification acts as a partial mediator between awareness and affective evaluation, and different types of patronage behavior.

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)0.002
metaresearch head score (Gemma)0.008
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
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 head0.045
GPT teacher head0.344
Teacher spread0.299 · 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

Citations27
Published2018
Admission routes1
Has abstractyes

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