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Record W4412580565 · doi:10.5509/2025983-art2

Perceived Protest Efficacy: How Economic and Diplomatic Ties with China Influence Support for Anti-China Protests Over South China Sea Disputes

2025· article· en· W4412580565 on OpenAlexvenueno aff
Mai Truong

Bibliographic record

VenuePacific Affairs · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHong Kong and Taiwan Politics
Canadian institutionsnot available
Fundersnot available
KeywordsChinaPolitical sciencePolitical economyLawSociology

Abstract

fetched live from OpenAlex

How do citizens in Southeast Asia view and support protests against China's aggression in the South China Sea (SCS)? Despite the critical role of public opinion in shaping Southeast Asian states' bargaining power with China and preferences for resolving SCS disputes, little research has addressed this question. This article examines how the multifaceted economic and diplomatic relations between China and SCS claimant states influence public attitudes toward anti-China protests, focusing on the mediating role of perceived protest efficacy—the belief that protesting can effectively address SCS disputes. Using survey experiments in Vietnam, Malaysia, and Indonesia, I find that information about diplomatic relations with China exerts a stronger influence on public attitudes than economic factors. Emphasizing broader political tensions increases support for anti-China protests in Vietnam and Indonesia, while highlighting improved diplomatic ties reduces it. In Malaysia, exposure to economic dependence on China diminishes support for protests. Crucially, the findings reveal that perceptions of protest efficacy mediate these effects, demonstrating how the salience of certain narratives affects collective action. By highlighting the balance between confrontation and diplomacy, this study provides fresh insights into regional dynamics, public mobilization in authoritarian regimes, and the challenges of building anti-China coalitions in Southeast Asia.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score1.000

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 studies0.0010.001
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 head0.007
GPT teacher head0.255
Teacher spread0.247 · 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.

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
Published2025
Admission routes1
Has abstractyes

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