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Record W3176596358 · doi:10.26522/jess.v5i1.3386

A Lot of People Did Not Want This to Happen

2021· article· en· W3176596358 on OpenAlexvenueno aff
Tunisha Singleton, Kyle Green

Bibliographic record

VenueJournal of Emerging Sport Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsMedia studiesNarrativeMainstreamCriticismIdentity (music)PoliticsSociologyAdvertisingChampionshipPolitical scienceAestheticsLaw

Abstract

fetched live from OpenAlex

Using three highly visible promotional videos from the Ultimate Fighting Championship (UFC), we perform a critical examination of the UFC’s branding during the COVID-19 pandemic. The first is a recorded endorsement from President Donald Trump, the second introduces the origin of an international pay-per-view series called “Fight Island” and the third is an end of year retrospective of the UFC’s performance in 2020. Employing content analysis grounded in brand psychology and narrative persuasion, we deconstruct the visual communication and story-based elements within this advertising to reveal how the company has adopted an identity of heroic dominance and defiance. This persona is built from a cognitively biased and framed suggestive notion which the UFC uses to market themselves as the lone organization fearless enough to “conquer” COVID-19 through the continuation of live events and overcoming obstacles posed by government regulation and media criticism. Ultimately, we find three dominant narratives actively established from this identity and heavily employed in their subsequent branded content: “Sport Must Go On,” “Unstoppable Force,” and “World Gone Crazy.” We conclude by arguing that the UFC’s branding reifies the tenuous social and political position the young sport occupies by marketing the combat sports company as different than other mainstream sport leagues, through repeated celebration of the Dana White (President of the UFC) as a heroic figure, by their disavowal of caution in the face of a pandemic, and in portrayal of the mainstream media as a jealous enemy.

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)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.004
Scholarly communication0.0040.005
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0170.006

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 head0.061
GPT teacher head0.373
Teacher spread0.311 · 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 designQualitative
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

Citations1
Published2021
Admission routes1
Has abstractyes

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