MétaCan
Menu
Back to cohort
Record W4321215175 · doi:10.1177/15270025231156058

The Emergence of Mixed Martial-Arts and the Future of Boxing: An Analysis of Consumer Interest and Compensation

2023· article· en· W4321215175 on OpenAlex
Nicholas M. Watanabe, Brian P. Soebbing, Tarlan Chahardovali, Yinle Huang

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 · 2023
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicSports Analytics and Performance
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMartial artsChampionshipLiberian dollarCompetition (biology)SuperstarMainstreamAdvertisingAthletesCompensation (psychology)MarketingEconomicsPolitical scienceBusinessArtPsychologyVisual artsLawSocial psychologyFinance

Abstract

fetched live from OpenAlex

Despite its long-standing history as the most popular and mainstream combat sport, boxing has been confronted with increased competition from mixed martial arts (MMA) in recent decades. The dominant organization in the MMA market, the Ultimate Fighting Championship (UFC), has grown to become a multibillion dollar organization. In this article, we directly compare consumer interest and fighter compensation between boxing and the UFC to consider the economic potential for these combat sports into the future. Overall, our conclusions indicate that boxing has continued to be more lucrative as a whole, with the key factor being the presence of superstar athletes.

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)0.002
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 score0.113
Threshold uncertainty score0.251

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.031
GPT teacher head0.235
Teacher spread0.203 · 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