KJCKorea
Journal Central

International sanctions and pandemic-era border closures rarely affect cities evenly, yet within-country distributional effects remain difficult to measure when the targeted state publishes no reliable sub-national statistics. This paper addresses the gap using a relatively underused approach in Korean studies and political economy: a high-frequency satellite nighttime-lights (NTL) panel applied to North Korea. Drawing on NASA's daily Black Marble product over 2012–2025 for sixteen cities, the analysis detects 285 power-disruption (PD) and 577 flood-inducing rainfall (FL) events, then computes eight resilience metrics per event under a fixed pre-sanctions baseline. City fixed-effects regressions compare resilience across three regimes (pre-sanctions 2012–2015, post-sanctions 2017–2019, post-COVID 2020–2025); inference is reported conservatively via exact-enumeration wild cluster bootstrap (WCB) over all 2⁴ = 16 sign patterns with G = 4 metropolitan clusters, alongside leave-one-cluster-out checks. Four findings emerge. First, a substantial capital-protection contrast in PD frequency: the Pyongyang-metropolitan cluster records 0.69 PD episodes per city-year against 2.49 in the east-inland cluster — a 3.6-fold rate gap that holds across alternative comparator schemes (illustratively, 17 events in the four most-protected core cities against 96 in the two most-exposed inland-border cities). Second, NTL responses to flood-inducing rainfall became larger during the post-sanctions period (impact +0.109, scarring +0.188), consistent with — though without direct infrastructure observation of — weakened drainage or response capacity. Third, NTL impacts of both event types contract under post-COVID conditions (PD impact −0.061; FL impact −0.318), which the analysis interprets primarily as reduced measured urban activity rather than improved resilience. Fourth, an exploratory heterogeneous-treatment pattern (HC3-based, not validated under WCB) suggests that politically protected, low-exposure cities show larger post-COVID PD impacts than high-exposure cities (interaction +0.073), consistent with prior sanctions-era adaptation among the latter; this pattern warrants further investigation. The paper also illustrates how daily satellite NTL, when combined with transparent event definitions and panel-based robustness checks, can supplement conventional sources of evidence in opaque-state political-economy research.

This study examines how the Biden administration articulated its social policy agenda within official discourse, rather than how that agenda fared as legislation. Existing scholarship reads the administration's domestic program as an ambitious welfare-state expansion later checked by retrenchment, yet leaves underexamined how social provisions were defined, framed, and linked to broader policy goals in the first place. Because a policy's meaning depends on the problem it is presented as addressing and the policy language through which it is explained, this study asks with which policy languages the administration associated its social agenda, and how those linkages structured its official discourse. Drawing on official White House texts published between January 2021 and January 2025, the analysis combines keyword frequency, N-gram, and sentence- and category-level co-occurrence analysis. Social policy vocabulary retained a visible presence throughout the term, yet ‘jobs’ and ‘investment’ operated as the central terms linking otherwise distinct agendas. At the level of four analytical categories, welfare/protection (the traditional safety-net language of income support, health, and housing) and social investment (education, training, and human-capital formation) repeatedly co-occurred with industrial policy. Fiscal responsibility, by contrast, attached chiefly to these two social categories rather than to industrial policy. These patterns indicate that social policy was not articulated primarily through the traditional welfare idiom of social rights, decommodification, and protection against social risk. Instead, it was repeatedly situated within the logics of labor-market participation, productive capacity, cost reduction, and fiscal soundness. The study conceptualizes this configuration as theeconomization of social policy.

It is the industry related to Artificial Intelligence(AI), without a doubt, that has become a dominant focus globally. With the growing recognition that AI technology could be the essence of the state’s competitiveness and power, various countries including two dominant players in this field, the US and China have pushed on towards the development of their AI industries. Despite the fact that the EU’s level in AI technology lags far behind the US and China, the EU enacted the world’s first comprehensive law related to AI regulation in 2024. There have been pros and cons of the EU AI Act; while the necessity of rules and regulations of AI under the situation of the spread of AI technology use is asserted, it is argued that the EU AI Act can be a stumbling block to the EU’s AI technological innovation. The EU has also established and implemented various policies for its purpose of becoming a global leader alongside the US and China in the AI industry. From this perspective, this research discusses whether the EU AI Act is suitable for the EU’s goal for AI technological innovation, or if the Act serves as an obstacle to AI adoption and diffusion in the EU. To this end, the research adopts two Korean programmes, <The Lost PD> and <A-IDOL> which are the world’s first programmes produced and broadcast using AI, in order to analyse how these programmes would be affected if the EU AI Act is applied. This study reveals that the possibility of production and broadcasting for each programme may differ according to the risk-based approach, which is the core of the EU AI Act. This is mainly because these two programmes adopt the different level of AI application. It means that the EU AI Act could function as a regulation for groundbreaking creation or innovation using AI. On the other hand, it is worth noting that the compliance with the EU AI Act could serve as a proof of quality and reliability in the market. Conclusively, the EU’s AI policy should maintain an appropriate balance between regulation and innovation in order to achieve the EU’s two goals of developing AI technology and protecting the EU’s values.