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Record W1969581508 · doi:10.1177/1012690211433452

Shadowed by the corpse of war: Sport spectacles and the spirit of terrorism

2012· article· en· W1969581508 on OpenAlexaff
Michael Atkinson, Kevin Young

Bibliographic record

VenueInternational Review for the Sociology of Sport · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsUniversity of CalgaryUniversity of Toronto
Fundersnot available
KeywordsTerrorismFraming (construction)SociologyMedia studiesPolitical scienceHistoryLaw

Abstract

fetched live from OpenAlex

Since the early 2000s, there has been a groundswell of research on terrorism and sports mega-events, including investigations into the impact of ‘9/11’ on fear and risk management strategies at high profile sports events. In this article, we re-examine the case of the Salt Lake City Winter Games of 2002 around Baudrillard’s (1995) concept of the ‘non-event’. We compare the (largely British and North American) mass mediation and discursive framing of terrorism at the 2002 Games with subsequent discourses interwoven into accounts of terrorism, fear and security at the 2004 Summer Olympic Games in Athens and the 2006 Winter Olympic Games in Turin. Of principal interest is the global framing of sports mega-events as targets of terrorism and the ways in which such events become fabricated zones of risk. To understand why there is a lingering media construction of the sports mega-event as an imagined target (and, in many ways, pre-constructed victim) of terrorism, we draw centrally on Baudrillard’s work (1995, 2001, 2002a, 2002b). Specifically, we employ Baudrillard’s concepts of the hyperreal and the non-event as a means of exploring terrorism’s relationship with sport, and the potential usage of such theoretical ideas in the sociology of sport and physical culture more broadly.

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)0.003
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.857
Threshold uncertainty score0.933

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.362
Teacher spread0.328 · 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 designNot applicable
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

Citations42
Published2012
Admission routes1
Has abstractyes

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