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Record W3009892581 · doi:10.1177/1527002520906529

Impacts of Performance-Enhancing Drug Suspensions on the Demand for Major League Baseball

2020· article· en· W3009892581 on OpenAlex
Jeffrey Cisyk

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

VenueJournal of Sports Economics · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsLeagueAdvertisingQuality (philosophy)MarketingBusinessNatural experimentMedicine

Abstract

fetched live from OpenAlex

In 2005, Major League Baseball (MLB) introduced a new policy regarding the use of performance-enhancing drugs (PEDs) wherein the league would not only suspend but also publicly name any player who tested positive for banned PEDs. Using the estimated television audience size of MLB games from 2006 to 2012, these PED suspension announcements provide a unique natural experiment to test how consumers react to news of PED use. This study finds that PED announcements have two major impacts on the demand for baseball. First, there is on average an immediate 9.3% reduction in the television audience of the PED player’s team. Second, the magnitude of the effect gradually decreases over time yet remains negative and significant for a period of 37 days or approximately 33 game-broadcasts. This is the first study to link PED use to an adverse reaction by consumers in a systematic way using television audience while controlling for the change in team quality caused by removing the suspended player from the team.

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)0.001
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 score0.319
Threshold uncertainty score0.614

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.030
GPT teacher head0.210
Teacher spread0.180 · 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