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Record W3094111186 · doi:10.1515/fjsb-2020-0051

<b>Zwischen Putin und Trump:</b>Orbáns illiberale Demokratie und das Spektakel des Sports in Ostmitteleuropa

2020· article· de· W3094111186 on OpenAlexaff
Ivan Kalmár

Bibliographic record

VenueForschungsjournal Soziale Bewegungen · 2020
Typearticle
Languagede
FieldSocial Sciences
TopicGerman legal, social, and political studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsHumanitiesPolitical sciencePhilosophyArt

Abstract

fetched live from OpenAlex

Zusammenfassung Wie schaffen es illiberale Politiker, mit einer Politik gewählt zu werden, die gegen die Interessen ihrer Wähler verstößt? Eine mögliche Antwort ist, dass sie Spektakel als Ersatz für Debatten und politische Auseinandersetzung bieten. Mit den Arbeiten von Roland Barthes zu Mythologie und von Guy Debords zu Spektakeln argumentiere ich, dass für illiberale Führungsspitzen wie Putin, Trump und Orbán das Spektakel des Sports dazu dient, die Debattenkultur in der praktischen Politik zu übertünchen. Orbáns Variante dieser Spektakel ist von besonderem Interesse für den europäischen Kontext, da sie aufzeigt, wie die illiberale Beseitigung einer Debattenkultur innerhalb der Regelwerke und Vorgaben der Europäischen Union möglich wird.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.040
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0060.009
Scholarly communication0.0070.007
Open science0.0010.004
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0190.002

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 head0.045
GPT teacher head0.328
Teacher spread0.282 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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