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Record W4406467386 · doi:10.1093/isagsq/ksae091

Radical Right Dystopias in the Global Culture Wars

2024· article· en· W4406467386 on OpenAlexafffund
Rita Abrahamsen, Michael C. Williams

Bibliographic record

VenueGlobal Studies Quarterly · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsUniversity of Ottawa
FundersSocial Sciences and Humanities Research Council of CanadaUniversity of Cambridge
KeywordsDystopiaIdeologyAestheticsSociologyPoliticsLiberalismEnvironmental ethicsPolitical economyPolitical scienceLawPhilosophy

Abstract

fetched live from OpenAlex

Abstract Despite the pervasive description of our times as dystopian, the disciplines of political theory and international relations seldom consider the political power of dystopian imaginaries. This article seeks to remedy this neglect by focusing on the radical Right's invocation of dystopias. These dystopian narratives go beyond mere scaremongering and constitute instead “critical dystopias” that follow a distinct grammar rooted in the radical Right's ideological critique of managerialism and liberal globalization. They express the radical Right's fear of liberalism, exploiting the latent dystopian possibilities in the liberal present. Promoted by right-wing influencers and media pundits, critical dystopias translate theoretical and ideological interpretations of social and political life into globally mobile, everyday infotainment readily accessible to broader, global audiences. As such, radical Right dystopias are affective strategies in a global culture war that may help (re)produce and reinforce political subjectivities, identities, and geopolitical imaginaries. They provide a window on the global appeal and interconnectedness of the radical Right and serve as a reminder of the importance of emotions and affect in international politics.

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)0.004
metaresearch head score (Gemma)0.006
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 score0.010
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0080.059
Scholarly communication0.0100.007
Open science0.0010.010
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0050.000

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 head0.027
GPT teacher head0.379
Teacher spread0.352 · 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

Citations6
Published2024
Admission routes2
Has abstractyes

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