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Record W7128525406 · doi:10.64903/1480-6800.20.2.170

Football in the Hands of the Other: Qatar's World Cup in the British Broadsheet Press

2017· article· W7128525406 on OpenAlexvenueno aff

Bibliographic record

VenueArab world geographer · 2017
Typearticle
Language
FieldSocial Sciences
TopicSports, Gender, and Society
Canadian institutionsnot available
Fundersnot available
KeywordsColonialismOrientalismIdeologyNarrativeDominance (genetics)RacismHegemonyFootballCultural hegemony

Abstract

fetched live from OpenAlex

Using reportage of the 2022 World Cup taken from The Telegraph and The Guardian , this paper demonstrates how Bhaba's ‘dynamics of writing and textuality’ are implemented to represent an Orientalist discourse that describes Qatar in colonial terms. Citing work by cultural critics such as Edward Said and Stuart Hall, it is argued that the British media constructs such a discourse to re-assert a form of colonial dominance which has historically greatly benefitted the former. Adapting theoretical frameworks on ‘grammars of exchange’ by Said and on mimicry by Homi Bhaba, it is contended that the British media's dominance allows it to replicate the process of knowledge formation that enabled colonial discourse to thrive throughout the 19 th century, and that Qatar's success in mimicking many of the cultural attributes of the West has transformed it into a viable threat which must be controlled. The paper concludes by arguing that the cultural narrative of Qatar conveyed to global audiences by the British media is a Western invention. It insists that such homogenising, Eurocentric narratives represent an ideological agenda with little relevance to the actual culture of Qatar and their exposure challenges the reductive hierarchies of neo-colonial racism that they promote.

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)0.002
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.220
Threshold uncertainty score0.437

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0080.004
Scholarly communication0.0100.002
Open science0.0000.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0170.002

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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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