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Record W3155113662 · doi:10.1080/15405702.2021.1913491

Offshoring & leaking: Cristiano Ronaldo’s tax evasion, and celebrity in neoliberal times

2021· article· en· W3155113662 on OpenAlexaff
Ana Jorge, Mercè Oliva, Luis Aguiar

Bibliographic record

VenuePopular Communication · 2021
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicTaxation and Compliance Studies
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsAusterityFootballReferendumPolitical scienceEarningsInefficiencyEconomic JusticeElitePolitical economyImmigrationEconomicsLawPoliticsMarket economy

Abstract

fetched live from OpenAlex

This article examines how the news media framed the allegations made in 2016 against Cristiano Ronaldo for evading taxes through offshores, and how audiences discussed this online, in Portugal, where he is originally from, and Spain, where he played football at the time. These countries were amidst an “austerity culture” justifying welfare cuts, promoting entrepreneurialism as “success”, and presenting neoliberal policies as “common sense”. Our analysis reveals Ronaldo portrayed as a member of the economic elite criticized for the high earnings of football players and celebrity tax privileges; as an ungrateful immigrant who does not contribute enough to society; and as “one like us” maneuvering to evade taxes. The comparative analysis shows audiences had double standards based on their feelings toward the celebrity, and they interpreted this case positively or negatively in relation to the inefficiency of the fiscal and justice systems in Southern Europe.

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 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 score0.228
Threshold uncertainty score0.456

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 head0.064
GPT teacher head0.265
Teacher spread0.201 · 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 teacher head, 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

Citations10
Published2021
Admission routes1
Has abstractyes

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