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Record W3096099042 · doi:10.1080/10357718.2020.1831435

The structure of foreign policy attitudes among middle power publics: a transpacific replication

2020· article· en· W3096099042 on OpenAlexaboutno aff
Timothy B. Gravelle, Jason Reifler, Thomas J. Scotto

Bibliographic record

VenueAustralian Journal Of International Affairs · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicPolicy Transfer and Learning
Canadian institutionsnot available
FundersEconomic and Social Research CouncilUniversity of Melbourne
KeywordsInternationalism (politics)Middle powerForeign policyMilitantIsolationismPolitical scienceInternational relationsExplanatory powerPolitical economyMiddle EastSociologyPoliticsLawEpistemology

Abstract

fetched live from OpenAlex

Empirical models illustrating how mass publics organise their views on foreign policy issues abound. Models that posit militant internationalism and cooperative internationalism as the two factors structuring mass foreign policy attitudes and that typically rely on American survey data have given way to models positing a larger number of underlying factors supported by cross-national survey data. Still, there are few studies assessing the cross-national validity of multi-factor models. Further, middle power states that must navigate between international leadership and followership remain understudied. This article draws on new survey data from Canada and Australia—two archetypal middle power states—to replicate a recent and influential model of foreign policy attitudes comprised of four factors: cooperative internationalism, militant internationalism, isolationism, and support for global justice. Using an exploratory structural equation modelling (ESEM) framework, it finds that the four-factor structure of foreign policy attitudes observed in the United States, United Kingdom, France and Germany obtains among the Canadian and Australian publics, yet there are country-specific nuances that suggest differences in the ways Canadians and Australians perceive foreign policy options.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.305

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
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 head0.044
GPT teacher head0.327
Teacher spread0.283 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2020
Admission routes1
Has abstractyes

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