MétaCan
Menu
Back to cohort
Record W2093123255 · doi:10.1080/02589340801962536

The Symbolic Politics of Sport Mega-Events: 2010 in Comparative Perspective

2007· article· en· W2093123255 on OpenAlexaboutno aff
David Black

Bibliographic record

VenuePolitikon · 2007
Typearticle
Languageen
FieldSocial Sciences
TopicSport and Mega-Event Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsNarrativePoliticsRealmCognitive reframingSociologyPolitical economyAestheticsPolitical scienceLawSocial psychology

Abstract

fetched live from OpenAlex

For ambitious civic and national boosts sport mega-events provide unique opportunities for the pursuit of symbolic politics—a chance to signal important changes of direction, reframe dominant narratives about the host, and/or reinforce key messages of change. These signals or narratives are critical vehicles of legitimation, with both narrowly instrumental objectives and more expansive purposes related to the mobilisation of societal support for certain dominant ‘ideas of the state’. This paper explores the realm of symbolic politics through a comparative analysis of three disparate mega-event hosts which will take the world stage in 2010: South Africa (the FIFA World Cup), Delhi/India (the Commonwealth Games), and Vancouver/Canada (the Winter Olympics). The paper argues that despite important differences in the circumstances of these hosts and the events they are to mount, there are some key commonalities in the narratives they seek to deploy and the subtexts they embody. These commonalities revolve around a paradoxical blending of inclusive, transcendent, or cosmopolitan narratives on the one hand, and competitive, differentiating narratives of ‘world class’ aspirations and achievements, on the other. Strikingly then, these widely dispersed events have become vehicles for similar messages with potentially contradictory implications.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.053

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0050.009
Scholarly communication0.0070.004
Open science0.0010.004
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0160.000

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 head0.052
GPT teacher head0.390
Teacher spread0.338 · 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

Citations177
Published2007
Admission routes1
Has abstractyes

Explore more

Same venuePolitikonSame topicSport and Mega-Event ImpactsFrench-language works237,207