Research on the Evolution of the Spatiotemporal Patterns and Influencing Factors of China's Agricultural Green Resilience

This paper created an evaluation index system for agricultural green resilience, consisting of five dimensions: resistibility, recoverability, adaptability, innovatability, and reconstructability. We used the entropy method to measure the agricultural green resilience levels of 30 provinces(municipalities/autonomous regions) in China from 2007 to 2021 and employed spatial Markov chains and geographic detectors to reveal the dynamics and evolution of the patterns and influencing factors of the agricultural green resilience. The study shows that the level of agricultural green resilience in China displayed a slight upward trend from 2007 to 2021, but the overall level remained low. Spatially, a distribution pattern of “eastern China > central China > northeastern China > western China” was observed. The transfer process for agricultural green resilience exhibited a “path dependence” characteristic that maintained its initial state, while it also showed a “trickle-down effect.” This means that the regions adjacent to provinces(municipalities/autonomous regions) with higher levels of agricultural green resilience tend to have an increased probability of an upward movement in their ranking. However, such movements are not leapfrogging and only occur at the adjacent levels. The spatial differentiations in the agricultural green resilience levels are primarily driven by the technological innovation capacity and market maturity, with interactions between these factors exhibiting both dual-factor enhancements and nonlinear enhancements. Accordingly, efforts should be made to strengthen support for the less-developed regions, increase research and development investment in the agricultural sector, and improve the market systems for agricultural products to enhance agricultural green resilience.

An Evaluation and Similarity Analysis of Provincial Green Development Levels in China Using Grey Relational Analysis

Green development is vital for bringing about high-quality development, which makes measuring and comparing provincial green development levels essential. This study calculates the comprehensive green development scores using panel data from 30 Chinese provinces and autonomous regions(2013–2022) and a combined subjective-objective weighting method. It also innovatively establishes a grey relational degree matrix and a grey improvement sequence to analyze provincial similarities and identify benchmarks for improvement. The results indicate that ecological and environmental protection holds the highest weight among the primary indicators. Beijing, Shanghai, Tianjin, Zhejiang, and Jiangsu lead in green development, with Shanghai, Beijing, and Tianjin exhibiting distinct development trajectories, while Guizhou and Yunnan share a similar trend. Zhejiang and Shaanxi have prominent benchmarks for improvement, while some provinces dynamically adjust their targets. The results suggest that advanced regions should further refine their green development pathways to align with their specific contexts, while less-developed regions should adaptively learn from the appropriate benchmarks and periodically reassess their strategies. This study provides scientific guidance for regional green development planning, policymaking, and benchmarking, thus contributing to sustainable regional development. Furthermore, it lays a foundation for future research to expand into broader datasets, scales, influencing factors, and policy evaluations.

The Impact of English Language Anxiety on the Cross-Cultural Adaptability of Chinese Overseas Students in Malaysia

With the deepening of cross-cultural educational cooperation between China and Malaysia, the crosscultural challenges that Chinese overseas students face in Malaysia due to language and cultural differences have become increasingly prominent. Focusing on Chinese graduate students at a public university in Malaysia where English is the medium of instruction, this study employs a scale survey method in conjunction with IBM SPSS 26.0 and Smart PLS 4.0 for data analysis to quantitatively explore the level of language anxiety and its relationship with cross-cultural adaptability and learning motivation. The results indicate that most Chinese graduate students experience notable language anxiety, which is significantly negatively correlated with cross-cultural adaptability, especially academic adaptability, but is not related to learning motivation. Furthermore, the study reveals the complex influencing mechanism of language anxiety within multicultural educational environments and offers suggestions for improvement tailored to Malaysia's unique educational context. These include utilizing technological tools for language interventions, optimizing classroom teaching strategies, enhancing language learning motivation through external incentives, strengthening training for cross-cultural adaptation skills, and promoting deeper cross-cultural communication. This study provides theoretical support and practical references for alleviating language anxiety and enhancing the cross-cultural adaptability of Chinese overseas students.

Adopting Inclusive Legal Regulation for Digital Finance in the Context of Generative AI

Driven by the dual forces of China's financial powerhouse strategy and advancements in artificial intelligence, digital finance has experienced rapid growth, rendering traditional financial legal regulations inadequate to meet its regulatory demands. Key challenges include lagging legislative regulation, limited applicability of the standard regulations, and diminished effectiveness of the supervisory regulations. These challenges stem from the “single-entity” regulatory approach which is inadequate to meet its regulatory needs of mixed operations of digital finance, the misalignment between “static” administrative regulations and the dynamic evolution of financial technology(fintech), and the uneven allocation of regulatory resources, which constrain regulatory precision. To achieve a dynamic balance between the development of digital finance and its regulation, the adoption of inclusive legal regulation is imperative. The technological empowerment theory integrates the principles of finance with the “people-centered” concept and the social good, which thereby safeguards the rights and interests of digital finance consumers. As a pivotal standard for shaping inclusive legal regulation, digital justice should not only uphold fairness in the regulation of processes but also advance the organic integration of scenario-based justice and the principles of Law 3.0. In the future, China should foster multi-stakeholder collaborative governance to ensure the orderly allocation of the regulators' power. This effort should be supported by a comprehensive toolkit of technological regulations, which can dynamically balance incentive regulation with binding regulation while simultaneously enabling the efficient flow of regulatory resources within specific application scenarios. Such strategies would provide a viable pathway toward the goal of achieving inclusive legal regulation in digital finance.

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