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Record W4403824243 · doi:10.1080/23745118.2024.2421889

Identarian Atlanticism and foreign policy implications: a study of European public attitudes

2024· article· en· W4403824243 on OpenAlexaff
Benjamin Toettoe, Florent Guntz, Richard Turcsányi

Bibliographic record

VenueEuropean Politics and Society · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsUniversité de Montréal
FundersNextGenerationEU
KeywordsForeign policyPolitical sciencePublic policyPublic opinionPublic administrationPolitics

Abstract

fetched live from OpenAlex

An increasing number of scholars have studied the role of identity in shaping states’ foreign policy. In Europe, the existence of diverse national identities renders shared senses of European identity an important foundation for any foreign policy requiring supra-national coordination. Most studies support the view that strengthening senses of European identity promote ‘Europeanist’ foreign policy paradigms that emphasize the importance for Europe to act as an autonomous and independent global player. However, we suggest that the effects of European identification on citizens’ foreign policy preferences remain poorly understood. In this paper, using novel survey data, we statistically assess the linkages between citizens’ sense of European identity and their preferences to align with the United States. We find European identity to be strongly tied to ‘Atlanticist’ foreign policy attitudes and attribute much of this effect to feelings of ideational proximity. Our results provide insights into the future of Europe’s international positioning and showcase the importance of considering the relative proximity in actors’ identities when studying the impact of such identities on foreign policy attitudes.

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)0.006
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.011
Threshold uncertainty score0.032

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0030.004
Scholarly communication0.0050.003
Open science0.0000.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.330
Teacher spread0.287 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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