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Record W2148341324 · doi:10.1123/jsm.2013-0133

Determinants of Regional Sport Network Television Ratings in MLB, NBA, and NHL

2014· article· en· W2148341324 on OpenAlexaff
George Foster, Norm O’Reilly, Carlos Shimizu, Neal Khosla, Ryan Murray

Bibliographic record

VenueJournal of Sport Management · 2014
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsLeagueClubBasketballProxy (statistics)UnivariateAdvertisingPsychologyMultivariate analysisMultivariate statisticsProduct (mathematics)Sample (material)VariablesMarketingBusinessGeographyStatisticsMathematicsMedicine

Abstract

fetched live from OpenAlex

This paper examines the determinants of live game Regional Sport Network (RSN) average annual ratings in three major North American professional sport leagues: Major League Baseball (MLB), the National Basketball Association (NBA), and the National Hockey League (NHL). A conceptual model of the determinants of club RSN ratings is constructed based on a marketing management framework. Five categories of determinants are identified: Product-Club, Product-Player, Brand-Club, Brand-Player, and Place. Data were collected over a 12-year period (1999–2011) for a total of 46 independent variables. The list of independent variables was reduced to 16 factors and a proxy variable for each of the factors identified. Univariate and multivariate analyses were undertaken. Strong support for the each of the five categories in the conceptual model was found for the pooled sample of all three leagues. Results at the individual league level revealed league differences in the relative importance of individual variables. Implications for future research and practice 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.

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)0.003
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.157
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 head0.020
GPT teacher head0.288
Teacher spread0.269 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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