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Record W424902448

The Social Cost of Baseball: Addressing the Effects 0f Major League Baseball Recruitment in Latin America and the Caribbean

2014· article· en· W424902448 on OpenAlexaboutno aff
Emily B. Ottenson

Bibliographic record

VenueOpen Scholarship Institutional Repository (Washington University in St. Louis) · 2014
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsLeagueLatin AmericansPolitical scienceDevelopment economicsEconomicsLaw
DOInot available

Abstract

fetched live from OpenAlex

Latin American and Caribbean countries should be financially compensated for the loss of native baseball players to MLB teams. Players recruited from Latin America and the Caribbean should be afforded the same rights and privileges as U.S., Puerto Rican, and Canadian players, and MLB should not be permitted to recruit them without some acceptable level of restraint or oversight. This Note offers one possible solution to MLB’s recruitment problems while taking into account both the interests of the recruited players, as well as the effect MLB’s talent recruitment efforts have on Latin American and Caribbean countries. The solution this Note proposes is a Coase Theorem—based compensation system, in which MLB teams cooperate with Latin American and Caribbean countries to support the fair and responsible development of baseball players. Under this system, MLB teams will financially compensate these countries for the right to negotiate contracts with players and bring them into the Major League system. This system will in effect allow MLB teams to purchase a country’s interest in its player’s talent, so that a team can sign and develop the player as a major league prospect. Implementing and enforcing this compensation system will require the involvement of the governments of all participating countries or an international organization designed to oversee the process. It will encourage positive political relationships between the United States and Latin American and Caribbean countries by incentivizing governments to work with MLB teams in the development of young players. Because the supply and demand for talented baseball players is virtually unlimited, countries that are regularly financially compensated for the recruitment of their ballplayers will have a strong incentive to maintain positive relations with the United States. Part I of this Note will discuss how MLB teams currently recruit talent in Latin America and the Caribbean. It will also introduce the recruitment systems in other countries for comparison purposes. Part II will discuss current issues surrounding MLB teams’ recruitment in Latin America and the Caribbean. This includes discussion of the possibility of an international draft, difficulties with expanding the jurisdiction of the Major League Baseball Players Association (“MLBPA”) internationally, and the lack of a regulatory body to govern how MLB teams recruit in Latin America and the Caribbean. It will also discuss Japan’s system for regulating MLB teams’ recruitment of Japanese players for comparative purposes. Part III will propose a Coase Theorem-based approach to international player recruitment. This approach suggests the implementation of a compensation system, wherein countries are paid by MLB teams for the right to recruit talent as a remedy for the social cost of baseball. It will also propose a “public-private” partnership to regulate this system. Under a public-private system, MLB teams will negotiate directly with both Latin American and Caribbean countries and the players themselves in a process that will allow MLB teams to purchase the right to recruit the players they hope to bring to the United States. Part IV will discuss some of the problems, benefits, and complications that may result from a player-rental system. For example: general resistance to a change in the recruitment model, concerns with incentivizing countries to embrace the new system, concerns with enforcement of the system, MLB’s possible responses to the concept of player value, and the system’s possible effect on international political relations.

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)0.003
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.704

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0050.003
Scholarly communication0.0080.003
Open science0.0020.006
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0140.000

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 head0.068
GPT teacher head0.272
Teacher spread0.204 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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