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Record W3103214139 · doi:10.1080/13597566.2020.1843021

Unified voters in a divided society: Ideology and regionalism in Belgium

2020· article· en· W3103214139 on OpenAlex
Mike Medeiros, Jean‐Philippe Gauvin, Chris Chhim

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueRegional & Federal Studies · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicElectoral Systems and Political Participation
Canadian institutionsMcGill UniversityConcordia University
Fundersnot available
KeywordsIdeologyRegionalism (politics)PoliticsPolitical economyPolitical scienceElectoral geographySurvey data collectionFederal electionSociologyPositive economicsLawEconomics

Abstract

fetched live from OpenAlex

In societies divided along ethnocultural lines, intergroup cooperation can often be a challenging task. This process can be even more complex if political parties and voters are divided along those same social cleavages. This study focuses on the case of Belgium and explores whether divided societies with separate party systems necessarily lead to distinct partisan alignments. Using electoral survey data from the 2014 Belgian federal election, we investigate whether political ideology is stronger than ethnolinguistic group membership in shaping electoral behaviour. The results demonstrate that although Belgian voters are divided along linguistic lines when it comes to preferences about centralization, they remain aligned along party families on social and economic dimensions.

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.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.272
Threshold uncertainty score0.989

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.190
GPT teacher head0.400
Teacher spread0.210 · 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