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Record W4399210958 · doi:10.1177/23780231241251714

Politics of Boundary Consolidation: Income Inequality, Ethnonationalism, and Radical-Right Voting

2024· article· en· W4399210958 on OpenAlexaff
Martin Lukk

Bibliographic record

VenueSocius Sociological Research for a Dynamic World · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicPopulism, Right-Wing Movements
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsRadical rightOpposition (politics)VotingInequalityPoliticsPolitical radicalismConsolidation (business)Redistribution (election)Ethnic groupPolitical economyPolitical scienceEconomicsSociologyDemographic economicsLaw

Abstract

fetched live from OpenAlex

Scholars have linked income inequality to the recent success of radical-right parties and movements. Yet research shows that inequality reduces participation among groups likely to support the radical right and promotes support for redistribution, an issue championed by the radical left. This raises questions about why, if at all, inequality matters for radical-right politics. The author reconciles previous arguments by developing a theory that connects these phenomena through the process of boundary consolidation. He argues that inequality generates status threats that prompt exclusionary shifts in national group boundaries. This promotes ethnonationalism, a restrictive conception of national membership and, ultimately, support for the radical right, whose mobilization relies on ethnonationalist appeals. Analyses of time-series cross-sectional data from 38 countries support this theory, revealing that inequality is associated with greater ethnonationalism, with distinct associations by income and ethnicity, and that ethnonationalism strongly predicts radical-right voting. The author thus demonstrates how long-term structural changes are linked to contemporary radical politics and how arguments setting economic and cultural causes of the radical right in opposition are inadequate.

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)0.008
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.106
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.005
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.144
GPT teacher head0.490
Teacher spread0.346 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
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

Citations1
Published2024
Admission routes1
Has abstractyes

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Same venueSocius Sociological Research for a Dynamic WorldSame topicPopulism, Right-Wing MovementsFrench-language works237,207