This article investigates whether political regime type determines the global diffusion of AI-based digital surveillance systems. Utilizing a Most-Different Systems Design (MDSD) comparing the United States and China, supplemented by a multivariate logistic regression analysis of the Carnegie AI Global Surveillance (AIGS) Index (N = 176) and several other indexes, the study develops a supply-side theory of surveillance adoption. The quantitative and qualitative analyses reveal that while the adoption of surveillance programs correlate significantly with state capacity (measured by military expenditure and digital surveillance infrastructure) and the presence of security shocks, political regime type is not a statistically significant predictor of adoption probability (p = 0.544). Instead, regime type acts as a mediating variable that shapes the intensity, integration, and legal framing of the surveillance grid. While both nations have converged on functionally equivalent architectures featuring biometric fusion and predictive policing, their institutional paths diverge: the U.S. operates via a “decentralized mesh” of public–private partnerships, whereas China employs an “integrated vertical grid” for preemptive social governance. This study challenges the “digital authoritarianism” narrative by demonstrating that pervasive surveillance is not a regime-specific pathology but a structural outcome of state capacity in high-resource modern regimes.
Official communication conveys regime priorities, but we know less about how elites use routine reporting to signal upward and how this shapes authoritarian issue politics. Using 71,460 official public-activity news releases (2016–2022) for the General Secretary, the Premier, provincial party secretaries, and governors, we build a shared issue agenda with a topic model and estimate distributed-lag panel models of responsiveness. Provincial leaders’ issue shares track shifts in the General Secretary’s attention far more than the Premier’s, even after accounting for baseline differences and common shocks. Alignment is strongest on issues closely associated with the General Secretary. Heterogeneity is mainly institutional: party secretaries respond more than governors. Observable factional proximity is linked to at most small, inconsistent differences within offices. Routine public-activity reporting thus serves as an upward-facing signaling channel and clarifies how agenda control operates in a centralized authoritarian system.
While AI-assisted decision-making is rapidly gaining global traction as a novel governance paradigm, the foundations of its legitimacy are yet to be fully revealed. To address this, we examine how AI-assisted decision-making affects public support and perceived decision quality, focusing on AI literacy. Using a survey experiment in China with a rural public goods provision scenario, we find two key effects. First, a digital legitimation effect where AI-assisted decision-making significantly increases public support compared to bureaucratic decision-making. Second, a digital compensation effect among individuals with low AI literacy, enhancing perceived scientific validity, internal political efficacy, and acceptance of AI-assisted governance at micro- and macro-levels. These findings offer a dual-pathways framework for legitimacy, showing that AI not only reinforces public support but also mitigates AI literacy disparities, fostering inclusiveness in governance decisions.
As a trade conflict between the two biggest economies in the contemporary world, the U.S.-China trade war is significantly impacting a wide range of areas involving several actors. However, few studies have paid attention to the strategic behaviors of subnational political elites during this event. To address this, we examined the emotional sentiment of 30,597 U.S.-related news items in 31 provincial party newspapers in China before and after the shock of the U.S.-China trade war (2015-2022). Employing the event study method (ESM) and Two-way Fixed Effect model, we uncovered two main findings: (1) the onset of the trade war triggered significantly more aggressive propaganda strategies against the U.S. across Chinese provincial party newspapers, and (2) contrary to the conventional wisdom of commercial peace theory, stronger trade ties with the U.S. are linked to provincial leaders adopting a more hardline anti-U.S. stance. Through additional cross-sectional heterogeneity analyses, we found that within the context of the trade war, the positive association between trade ties with a national adversary and exceeding central anti-U.S. propaganda might be driven by heightened loyalty anxieties among subnational political elites. These findings have implications for studies examining the interplay between international relations and domestic politics, research around the survival strategies of political elites in non-electoral contexts, and debates on the determinants of propaganda strategies in international news coverage.
As Sino–U.S. strategic competition intensifies, U.S. technology diffusion to China faces growing uncertainty. This paper examines how such competition affects the value of patents transferred from the United States to China. Using the entropy weighting method, we construct a patent value index and apply a Tobit model to panel data at the 4-digit IPC subclass level from 1980 to 2023. The results show that strategic competition significantly reduces the value of transferred patents, primarily through rising economic policy uncertainty, stricter CFIUS reviews, and the expansion of the Entity List. The effect varies by competition intensity, type of competition, and the patent share structure between the two countries. While high-intensity competition suppresses patent value, low-intensity competition has a positive effect. Competition events involving noneconomic issues exert a stronger negative impact than those involving economic issues do, and patents in fields where China holds a larger share are more adversely affected. Further analysis reveals that deeper value chain participation mitigates the negative impact of competition, whereas a narrowing technology gap amplifies it. These findings contribute to understanding international technology diffusion under geopolitical rivalry and offer empirical insights for policymaking in an era of global tech competition.
The Belt and Road Initiative (BRI) represent China’s flagship global infrastructure strategy; however, the influence of domestic governance variations on implementation remains underexplored. This study employs a convergent mixed-methods design, combining hierarchical linear modeling of panel data from 31 Chinese provinces (2015–2019) with qualitative process tracing and discourse analysis. The findings show that provincial bureaucratic capacity, fiscal resources, and governance quality significantly influence BRI implementation effectiveness, with bureaucratic capacity as the primary determinant. Qualitative evidence identifies three distinct provincial implementation pathways: capacity-driven proactive engagement, adaptive execution, and symbolic compliance. These findings challenge monolithic portrayals of Chinese state capacity, demonstrating substantial subnational variation in policy execution. The study highlights the importance of aligning BRI strategies with provincial capacities, as this alignment can lead to more effective implementation and better outcomes in infrastructure projects. This study offers practical insights for policymakers and international partners to enhance the effectiveness and sustainability of China’s infrastructure policy.
This article examines the role of Chinese state media in sustaining China’s external communication through softball questioning at the Ministry of Foreign Affairs press conferences. We develop a typology of four questioning strategies—charm offensive, negative othering, criticism mimicking, and preemptive counterframing—and analyze 4,988 questions posed by state media from 2020 to 2025. Our findings reveal frequent use of these strategies, varying across temporal and thematic contexts to address evolving external communication needs. Charm offensive and negative othering dominate, promoting positive images of China and criticizing rivals, while criticism mimicking and preemptive counterframing enable controlled rebuttals of international criticism. This study highlights the strategic function of softball questioning as a medium of state propaganda, advancing understanding of China’s media politics and external communication beyond traditional news framing approaches.
Artificial intelligence (AI) is rapidly transforming the scientific enterprise, yet its effects on knowledge dynamics—innovation and diffusion—remain poorly understood in the social science domain. Focusing on public administration scholarship, this study assesses whether AI integration is associated with changes in innovation and diffusion within the field. Using public administration articles indexed in Web of Science (1923–2025), we identify AI-integrated studies and construct matched comparison sets of non-AI articles with similar publication characteristics. We measure innovation using lexical and semantic novelty derived from bibliometric metadata and large language model–based semantic representations, and measure diffusion using citation-based indicators of academic influence and diffusion speed. AI-integrated articles exhibit significantly higher novelty, greater citation impact, and faster diffusion than matched non-AI studies. Decomposition analyses suggest that these gains are driven primarily by combinatorial innovation rather than the introduction of entirely new foundational ideas. Semantic trajectory analyses further show that AI-integrated work diverges more from established research pathways, consistent with reduced path dependence. This study extends technology-induced innovation debates into the social sciences, and offers scalable methodological tools for tracing AI’s imprint on scholarly communication.
Artificial intelligence (AI) has become a strategic infrastructure for contemporary science, raising pressing questions about whether it will reinforce existing hierarchies or foster more inclusive knowledge production. This study analyzed 134,719 AI-assisted articles using a large-scale large language model-based approach to examine spatial and temporal disparities between the Global North and the Global South (excluding the US and China). Results reveal several global patterns: convergence is observed in research output, while disparities persist in journal prestige. Substantial disciplinary variation also emerges, with digitally accessible fields, such as physics and technology, providing comparatively more equitable entry points for Global South researchers. Notably, collaboration networks exhibit clear North–South asymmetries. Joint publications involving major AI powers such as the US or China are consistently associated with higher journal prestige for the North and South. These findings suggest that AI-assisted research broadens participation and entrenches structural hierarchies, highlighting the need for governance and policy interventions that promote equitable access and inclusive collaboration.
This paper examines patterns in geo-strategic narratives associated with China's security signaling in the Taiwan Strait since 2020, showing that variations in China’s pressure-oriented diplomatic messaging are associated not only with reactions to U.S. or Taiwanese actions, but also with Beijing’s reassessment of global power dynamics—framed as the “great changes unseen in a century”—and growing confidence in its national capabilities. To test this argument, the paper employs a large language model (LLM) alongside advanced computational techniques to perform a longitudinal content analysis of nearly 2,000 People’s Daily articles from 2016 to 2024. The study classifies articles using Google’s Gemini 2.0 Flash model, and employs statistical modeling to examine how narrative indicators that capture geo-strategic reassessment and nationalist aspirations are associated with variations in Beijing’s security signaling toward Taiwan. Results indicate that China’s assertive messaging toward Taiwan is strongly associated with nationalist, identity-based narratives, while its coercive signaling shows a stronger correlation with China’s geo-strategic recalculation. Importantly, the findings also reveal that China's geo-strategic narratives are not monologic: different components of the “great changes unseen in a century” narrative are associated with distinct—and in some cases contradictory—patterns in Beijing’s coercive posture in the Taiwan Strait. This finding challenges the prevailing accounts of Chinese revisionism. The study contributes to a more sophisticated reading of Chinese security signaling, with broader implications for the management of regional stability in the West Pacific. Theoretically, the study advances the understanding of Chinese revisionism by disaggregating Beijing's “great changes unseen in a century” framework into distinct narrative components with divergent policy implications. Methodologically, it demonstrates the application of large language model classification combined with retrieval-augmented generation (RAG) as a validated instrument for longitudinal content analysis in social science research.
Global megacities face complex governance challenges requiring innovative digital solutions. Government hotlines have evolved into smart platforms facilitating citizen engagement and adaptive decision-making. Shanghai’s 12,345 and New York’s 311 hotlines, embedded in distinct political contexts, serve as critical interfaces between citizens and governments. Here we conduct a comparative analysis of structured data from both systems to identify request patterns, service quality, and digital transformation impacts, and apply a fine-tuned RoBERTa model on Shanghai’s unstructured data to predict citizen satisfaction. Our findings reveal how digital governance platforms encode political culture, reflecting divergent governance models and citizen-state relations. AI-empowered hotlines offer prospects for predictive analytics, integrated data ecosystems, and enhanced public services, while raising challenges related to privacy, accountability, and democratic participation. This study underscores the importance of contextualizing digital urban governance within broader institutional and cultural frameworks to harness AI’s potential effectively.
Chinese foreign direct investment (FDI) does not provoke uniform public resistance in Belt and Road Initiative (BRI) countries. Instead, security and economic threat narratives selectively reshape support, leading publics to distinguish between investors and investment modes rather than react unthinkingly to China’s presence. This study joins strategic narrative theory with the political economy literature to examine how threat narratives may alter public attitudes toward foreign investors. We develop an audience–cue–context (ACC) framework that treats narratives as cue-level inputs whose effects depend on who is listening (the audience) and what the investment signals (the context). We test these expectations through a survey experiment in Kyrgyzstan (n = 1,548), an independent, BRI investment recipient country neighbouring China, where Chinese investment is both visible and contested. Respondents were randomly exposed to security-threat, economic-threat, or neutral vignettes, and asked to evaluate Chinese FDI projects that varied by ownership (state-owned vs. private) and entry mode (greenfield vs. acquisition). Our findings show that security narratives significantly depress support for Chinese FDI, whereas economic threat narratives have weaker, more heterogeneous effects. Responses are structured rather than uniform: state-owned enterprises and greenfield investments attract heightened scrutiny under security framings, while economic frames interact more strongly with specific audience predispositions and contextual cues. Open-ended responses confirm that public reactions are structured and cue-sensitive, not uniformly sceptical. This study contributes to the literature on political communication, Chinese foreign policy, and FDI by operationalising narrative reception as a function of contextually embedded cues and audience filters in our ACC framework. Jessica E. Neafie is an assistant professor in the Department of Political Science and International Relations at Nazarbayev University (Kazakhstan). Her research focuses on China’s foreign policy in emerging economies, on multipolarity, on middle-power strategy, and on energy and environmental governance in Central Asia. She leads and co-leads several international research projects on public opinion toward China, foreign policy, and environmental policy.
This paper utilizes a strategic narrative approach to grasp China’s views of contemporary international security politics. It explores Chinese international system narratives and policy-issue narratives presented in official policy documents, with reference to the cases of Russia’s full-scale invasion of Ukraine and the ongoing Israeli–Palestinian conflict. In particular, this paper asks two questions: How and to what extent are Chinese strategic narratives pertaining to the ongoing conflicts in Ukraine and Gaza comparable, and what do these narratives reveal about the potential for China to play a stabilizing role amid these conflicts? The comparison of both cases reveals that there is some consistency in China’s narratives, as demonstrated by China’s aspiration to play a greater role in security. However, by attracting the discontent of unsatisfied countries and presenting China as the leader of the wider international community, Chinese official discourse is also hampered by several ambiguities and contradictions that complicate its ability to play a meaningful role as a global security provider amid contemporary crises.
China’s soft power faces skepticism in Western contexts despite its global achievements. In Kyrgyzstan, a country historically influenced by Russia and increasingly engaged with China, the geopolitical and normative alignment between China and Russia offers a distinct environment for Chinese soft power. Here we analyze 14 waves of the Central Asia Barometer survey using Bayesian multilevel models to examine how Kyrgyz citizens’ cultural affinity with Russia and consumption of Russian media shape their perceptions of China. Our findings reveal that Russian soft power indirectly enhances China’s image and acceptance of its economic engagement through both passive cultural-political alignment and active media exposure. These results suggest that geopolitical partnerships can serve as critical channels for soft power transmission, highlighting the relational and contextual nature of soft power beyond Western normative frameworks.
War between rivalrous great powers (GPW) often is not a deliberate choice. Historically, great powers have pursued a combination of activities to discuss differences, clarify intentions, and establish ‘guard rails’ that inhibit unintended escalation into generalized war. Confidence Building Measures (CBMs), Confidence Security Building Measures (CSBMs), and structural arms control are three classic methods to reduce the risk of a security incident triggering rapid escalation into GPW. The Sino-American great power rivalry in the western Indo-Pacific incorporates the conflicting interests, flashpoints and potential triggering events that exacerbate the risks of GPW, suggesting that risk reduction initiatives and arms control agreements may help leaders choose de-escalation over war during triggering events. An analysis of past great power arms control arrangements and verification protocols indicate that most requisite preconditions for them are not present between China and the U.S. in the Indo-Pacific today. Thus, modest Sino-U.S. CBMs focused on enhanced political dialogue, recurring political-military forums, reciprocal information exchanges, direct leadership communications, and declaratory commitments without expansive transparency or on-site verification- appear the most logical approach to reduce the risks of GPW in the western Indo- Pacific today while simultaneously building-out necessary great power trust for future arms control and risk reduction measures.
Drawing on both statistical data and qualitative analysis, this article argues that the rising risk of the East China Sea (ECS) as a Great Power War Flashpoint (GPWF) is primarily the result of interactions of system- and unit-level forces. Structural factors—namely, a shift in the distribution of material capabilities among China, Japan, and the United States following the 2008 global financial crisis—have created an intensely competitive environment in the ECS; while the domestic politics of Japan and China have shaped the intensity of regional tensions. In particular, bilateral dynamics have been largely shaped by key triggering events, notably the 2010 maritime collision between a Chinese fishing boat and two Japanese Coast Guard vessels and Japan’s 2012 “nationalization” of the Senkakus. These incidents prompted China to adopt a more explicitly assertive posture to increase its maritime presence, thereby shifting the status quo. Given that the general improvement in bilateral relations between 2017 and 2019 did not significantly alter dynamics in the ECS, tensions are likely to continue rising, structurally heightening the likelihood of conflict over this GPWF and making political leadership an even more pivotal factor in determining the risk of escalation.
Studying great power war (GPW) in the twenty-first century presents a paradox. On the one hand, GPW thus far remains a relic of the past, not a contemporary phenomenon available for empirical research because it has not yet occurred in this century. On the other hand, the risk of GPW appears to be escalating in recent years, especially in the Indo-Pacific region. Its risk is becoming so real and imminent that scholars must do more to study its potential in a theoretical, empirical way. This paradox must be confronted and addressed. This special issue advances the literature by studying “great power war flashpoints” (GPWFs) through a “Multiple War Streams Framework” (MWSF). Synergising the diversified literature on the causes of war, the MWSF seeks to guide empirical investigation of GPWFs in the Indo-Pacific region and beyond. By shifting the unit of analysis from “GPW” (which is only available for empirical analysis after the war outbreak) to “GPWF” (which is available for empirical analysis regardless of whether a war will be ultimately broken out or not), this special issue opens up a new arena for studying great power politics.
China's dominant position in the rare earth elements (REE) sector results from a strategic political approach that emphasizes technological control over simple resource scarcity. This paper uses a Stackelberg leadership model to explain how China takes advantage of first-mover benefits in upstream extraction, midstream processing, and downstream standard-setting to create unequal power within the global supply chain. Based on patent data (China holds about 50% of global REE-related filings), policy events, and stylized simulations adjusted with USGS production data, PATSTAT filings, and follower entry metrics, the analysis shows that patent activity and tacit knowledge-rather than export quotas-are key to maintaining market dominance. China's export controls, licensing policies, and opaque IP networks create barriers that sustain dependency for follower countries like the US, EU, and Japan. Simulations of historical, patent-only, and counterfactual diversification scenarios reveal nonlinear lock-in effects, where follower output drops as China's technological advantage grows. A complementary regression confirms the post-2010 increase in China's recycling patent share, rising roughly 1.6% points each year. Overall, this framework redefines REE competition as a matter of techno-industrial sovereignty, urging follower nations to focus on coordinated R&D and open platforms to lessen vulnerabilities in critical sectors such as renewables, electric vehicles, and defense.
How should “Made in China” be re-defined? This paper revisits and reconceptualizes the “Made in China”, investigating its ongoing shift from a manufacturing to an innovation orientation through the lens of the neoclassical model of investment. Specifically, our empirical analysis, using a firm value decomposition model, reveals that this transformation is more prominent in high-tech industries compared to low-tech industries, and has become increasingly evident in recent years, especially after the implementation of the “Made in China 2025” initiative in 2015. We argue this shift is not a spontaneous market occurrence but the result of a concerted state-led project, driven by the political imperative to secure economic legitimacy and technological sovereignty. This study contributes to understanding China’s unique model of governing innovation commons, embedding firm-level innovation within a broader national strategy. The findings hold implications for policymakers and investors, highlighting the primacy of innovation capital and the need for a holistic governance approach that fosters both hard and soft innovation within a balanced state-market ecosystem.
