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Record W3082291758 · doi:10.3390/economies8030071

Revenue Sharing and Collusive Behavior in the Major League Baseball Posting System

2020· article· en· W3082291758 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

VenueEconomies · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Lethbridge
Fundersnot available
KeywordsLeagueBiddingRevenue sharingRevenueCompromiseBusinessClubFootballAdvertisingPaymentProfit (economics)Profit sharingCollusionEconomicsMicroeconomicsMarketingFinanceIndustrial organizationPolitical science

Abstract

fetched live from OpenAlex

This paper uses auction theory to explain the unique design of the 1998–2013 posting system agreed to between Major League Baseball and the Japanese Nippon Professional Baseball League that allowed for the transfer of baseball players from Japan to the United States. It has some similarities and many differences from the transfer system used to obtain players in European football. The unique features of the posting system were a compromise between Major League Baseball clubs and Nippon Professional Baseball clubs with the understanding that the former was a collusive group of club owners. Revenue sharing is a method to enforce a system of side payments to collusive bidders. It is then profit-maximizing to have the bidder with the highest net surplus from the player win the auction. Changes to the revenue sharing system used in Major League Baseball reduced the ability of club owners to bid for Japanese players, hence changes to the bidding rules of the posting system coincided at the same time.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.097
Threshold uncertainty score0.406

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 studies0.0000.000
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 head0.040
GPT teacher head0.210
Teacher spread0.170 · 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