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Record W7083449064 · doi:10.1177/155862350800300203

“If you Can't Win, Why Should I Buy a Ticket?”: Hope, Fan Welfare, and Competitive Balance

2008· article· en· W7083449064 on OpenAlex

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.

Bibliographic record

VenueInternational Journal of Sport Finance · 2008
Typearticle
Languageen
FieldArts and Humanities
TopicTechnology, Environment, Urban Planning
Canadian institutionsNipissing UniversityToronto Metropolitan UniversityLaurentian University
Fundersnot available
KeywordsLeagueBalance (ability)Construct (python library)WelfareSports economicsCompetitive advantagePerfect competition

Abstract

fetched live from OpenAlex

Competitive balance is highly desired in professional sports leagues, yet measurement of the concept is not well established. The definition of firm/team goals in a professional sports league and its connection with competitive balance has typically been assumed rather than studied. Using fan welfare as the goal of the firm, the current research attempts to link competitive balance with fan welfare through the use of what is termed the “hope” construct. A market survey of 367 individuals in a Major League Baseball market empirically supports the use of the hope construct in competitive balance. Suggestions for future research are presented.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.836
Threshold uncertainty score0.570

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.224
Teacher spread0.203 · 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