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Record W1903556031 · doi:10.1108/ijsms-13-02-2012-b003

A demand analysis for the Chinese Professional Baseball League 1990-2008

2012· article· en· W1903556031 on OpenAlexaff
Chen-Yueh Chen, Yi-Hsiu Lin, Yen‐Kuang Lin

Bibliographic record

VenueInternational Journal of Sports Marketing and Sponsorship · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsArtificial Intelligence in Medicine (Canada)
Fundersnot available
KeywordsLeagueAttendanceOrdinary least squaresAdvertisingDemographic economicsEconomicsProduct (mathematics)Professional sportEconometricsMarketingBusinessEconomic growthMathematics

Abstract

fetched live from OpenAlex

The Chinese Professional Baseball League (CPBL) experienced a rapid decline in attendance after the mid 1990s. In this study, market demand analysis is used to discover the causes of variation in CPBL attendance from 1990 to 2008. The ordinary least squares (OLS) is employed for model estimation. From this model, empirical evidence reveals that a homogenous sport substitute, Taiwan Major League (TML), the Major League Baseball (MLB) effect and game-fixing scandals in CPBL negatively influence CPBL attendance. Additionally, real income is found to negatively affect CPBL attendance, making CPBL games an inferior product. The proposed model accounts for approximately 91% of variation in CPBL attendance between 1990 and 2008.

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)0.009
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 score0.035
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.001
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)0.0010.000

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 head0.022
GPT teacher head0.263
Teacher spread0.240 · 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.

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

Citations6
Published2012
Admission routes1
Has abstractyes

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