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Record W4283588757 · doi:10.1111/jcms.13364

Narrating Europe: (Re‐)constructed and Contested Visions of the European Project in Citizens' Discourse

2022· article· en· W4283588757 on OpenAlex
Laurie Beaudonnet, Céline Belot, Hélène Caune, Anne‐Marie Houde, Damien Pennetreau

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJCMS Journal of Common Market Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversité de Montréal
FundersH2020 European Research CouncilFonds de Recherche du Québec-Société et CultureEuropean Commission
KeywordsVisionPolitical scienceAppropriationEuropean unionNarrativePublic administrationTreatyEuropean integrationCivil societyNegotiationPolitical economySociologyLawPolitics

Abstract

fetched live from OpenAlex

Changes in public opinion and civil society over the last decade have shown that citizens, particularly in old EU Member States, have developed more complex attitudes towards European integration. While the European project was previously generally described as a teleological depoliticized project, aiming at building peace and comforting growth, different competing visions of the European project are nowadays acknowledged and surface among the public on occasions, like referendums or treaty negotiations. While EU official narratives are documented by studies on the European institutions or the visions of leaders and parties, their empirical analysis at the citizens' level is still fragmented. Using focus group data in four countries (France, Portugal, Italy and Belgium) and three social groups (21 group interviews), we provide a comparative qualitative answer to how citizens envision European integration. Our results show that, first, official narratives do not fail to reach citizens, but they are also loosened, contested, and do not systematically produce a sense of common belonging. Second, they highlight the importance of socio‐economic contexts, as well as national and personal experience in the re‐appropriation of these narratives.

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)0.003
metaresearch head score (Gemma)0.002
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 score0.171
Threshold uncertainty score0.609

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.048
GPT teacher head0.365
Teacher spread0.317 · 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