‘Clearly Blown Away by the End of the Morning’s Drama’: Spectacle, Pacification and the 2010 World Cup, South Africa
Bibliographic record
Abstract
The massive security assemblages surrounding major sporting events and political summits embody two layers of spectacle. On the one hand, security operations are central to the governance of entertainment and media imagery. Simultaneously these security measures are profoundly theatrical and calibrated for the maximum visual impact: the spectacle of security itself. Some critical thinkers have described this dual spectacle as indicative of a contemporary state-corporate obsession with image and perception management, an obsession which detracts from ‘valid’ security concerns. By contrast I argue that spectacle and theatricality are in fact highly functional components of the pacification projects of state and capital. With reference to Guy Debord’s conception of ‘spectacle’, this article highlights how mega-events reveal, in highly dramatised form, the logic of pacification. Using the 2010 FIFA (Fédération Internationale de Football Association) soccer World Cup as a case study, the article demonstrates how police and military power are mobilised to secure accumulation, to enforce social control and to extend the power and arsenal of the state security apparatus. What is truly spectacular about mega-event security is not just the incorporation of media templates into the working of state forces. Rather, the rhetoric and concept of security itself becomes a form of spectacular power as it serves to both obscure and justify how mega-events are ultimately projects of class power.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".