‘Fog on the tyne’? The ‘common-sense’ focus on ‘sportswashing’ and the 2021 takeover of Newcastle United
Bibliographic record
Abstract
On 7 October 2021, a controversial takeover of the English Premier League team Newcastle United Football Club saw an 80% stake acquired by the Saudi Arabian Public Investment Fund (PIF), the country’s sovereign wealth fund. Public discussion and media coverage of the takeover has revolved almost entirely around the concept of ‘sportswashing’ – the practice of (usually) undemocratic regimes using sporting investments to ‘cleanse’ or enhance their reputation and deflect attention away from human rights abuses. This article examines the Newcastle takeover, interrogating the widespread portrayal of it as a clear-cut case of sportswashing, and explores alternative explanations for the purchase, and potentially other sports-related investments. Drawing broadly on scholarship by Bourdieu and scholars of the Arabian Peninsula, it argues that the concept of sportswashing as it is currently used limits discussion of wider, more complex social, political and economic entanglements.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.013 | 0.033 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".