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Record W4409409460 · doi:10.1007/s11366-025-09913-w

The Five Eyes Allies and China: Assessing Threat Perceptions and Power Dynamics

2025· article· en· W4409409460 on OpenAlexaboutno aff
Maria Papageorgiou, Zeno Leoni

Bibliographic record

VenueJournal of Chinese Political Science · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsnot available
FundersLeverhulme Trust
KeywordsChinaPerceptionPolitical sciencePower (physics)Dynamics (music)PsychologyLaw

Abstract

fetched live from OpenAlex

Abstract China's expanding role in global affairs, along with its economic, military, and technological capabilities, have increased concerns about it being a potential threat to U.S. hegemony. Consequently, since 2017, threat perceptions have heightened, with China increasingly viewed as a strategic competitor and rival. While the"China threat theory"is widely analyzed, it is often approached from a U.S.-centric perspective, neglecting the viewpoints of other key actors. This study aims to address that gap by examining also the threat perceptions of four US allies—New Zealand, Australia, Canada, and the United Kingdom—under the Five Eyes intelligence partnership. By analyzing their national security documents from 2008 to 2024, the study seeks to identify the presence, frequency, and sources of perceived threats. The findings indicate that although China as a threat is a multifaceted concern in issues such as identity, intentions, and geography, these countries primarily perceive China’s capabilities as the main source of threat. Finally, all states have elevated their threat perceptions of China, justifying decisions to counter its power in the Indo-Pacific as the main theatre of competition and to reinforce multilateral and bilateral alliances against Beijing.

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)0.002
metaresearch head score (Gemma)0.003
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.704
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.005
Scholarly communication0.0010.001
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 head0.007
GPT teacher head0.357
Teacher spread0.350 · 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

Citations16
Published2025
Admission routes1
Has abstractyes

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