英文目次丨华南农业大学学报(社科版)2026年第一期文章摘要

College of Economics and Management, China Agricultural University

Abstract：The high-quality development of agriculture is an imperative pathway in the new era for building a strong agricultural nation and advancing agricultural modernization with Chinese characteristics. Deeply implementing the ″Artificial Intelligence +″ initiative in the agricultural sector and accelerating the digital-intelligent transformation and upgrading of agriculture constitute an important approach to empowering the high-quality development of agriculture. From a theoretical perspective, artificial intelligence promotes productivity improvement by optimizing factor endowments, alleviates information asymmetry to enhance supply-demand matching, drives efficient resource utilization to strengthen the synergy between ecological and economic development, facilitates the internationalization of value chains to optimize global resource allocation, and balances interest distribution to consolidate the foundation for common prosperity. However, the current application of artificial intelligence to empower high-quality agricultural development is confronted with practical dilemmas, including bottlenecks in key core technologies, weak rural infrastructure, fragmented agricultural data resources, and a shortage of interdisciplinary and professional talents. Moving forward, it is essential to intensify research on key technological breakthroughs and accelerate the transformation and extension of technological achievements; improve agricultural infrastructure and build an artificial intelligence service system; construct a high-quality agricultural data system and establish a secure data sharing mechanism; strengthen talent team development and carry out tiered and categorized training programs. By doing so, we can fully unleash the potential of the integrated empowerment of ″Artificial Intelligence +″ to effectively drive the high-quality development of agriculture.

Key Words：artificial intelligence; high-quality development; agricultural modernization; technology empowerment; digital-intelligent transformation

1. Research Center for Rural Economy， Ministry of Agriculture and Rural Affairs

2. College of Management, Sichuan Agricultural University

Abstract：Grain loss reduction is one of the crucial pathways to safeguarding food security. The rapid development of the new generation of artificial intelligence (AI) has injected new momentum into cultivating this ″invisible fertile land″ of grain loss reduction. This paper sorts out the internal logic of AI empowering grain loss reduction, analyzes the realistic conditions and existing problems of AI supporting grain loss reduction, and puts forward policy optimization paths on this basis. The key findings are as follows: (1) The application of AI helps improve grain production technologies and optimize the management mode of the entire grain industry chain, thereby providing guarantee and support for grain loss reduction. (2) Although the technological conditions and infrastructure for AI application in grain loss reduction are constantly improving, it still faces constraints such as institutional gaps and shortage of professional talents. (3) Different from the viewpoints of previous studies, this paper proposes that governments, enterprises and farmers should establish a close linkage mechanism, rationally share the costs of AI application, and synergistically amplify the actual effect of all stakeholders in achieving grain loss reduction through AI.

Key Words：artificial intelligence; grain loss reduction; technology empowerment; food security

a.School of Advanced Agricultural Sciences; b.China Center for Agricultural Policy,Peking University.

Abstract：The aging population and empty-nest phenomenon in rural China are becoming increasingly severe. The declining capacity of family-based elderly care combined with the insufficiency of public services poses significant challenges. Artificial Intelligence (AI) offers a potential solution to these challenges. Drawing on Human Capital Theory, the Life-Cycle Hypothesis, and Public Economics, this paper develops an economic framework for AI-enabled rural elderly care. It explains how AI counteracts the depreciation of elderly skills by revitalizing their tacit knowledge as productive assets, and facilitates transformation of the resource allocation for the purpose of elderly care from static intertemporal savings into a dynamic risk-sharing system. Taking into account the essential demand, policy support, technological maturity, and infrastructure upgrades, the paper proposes four pathways: 1.Intelligent Guardianship to mitigate health risks through multimodal monitoring; 2.Resource Decentralization by channeling urban medical expertise into rural areas via telemedicine; 3.Value Reinvention by extending the elderly′s human capital;  4.Social Security Optimization to ensure smooth intertemporal protection through smart actuarial planning. However, these pathways also face risks and challenges, including the digital divide, service gaps, affordability constraints, and algorithmic discrimination. Therefore, it is urgent to develop a comprehensive and integrated policy framework of age-friendly adaptation, intelligent coordination, diversified financing, and public governance, to ensure that the elderly benefit equitably from technological innovation.

Key Words：artificial intelligence; rural elderly care; silver economy; smart elderly care

Institute of Agricultural Economics and Development, Chinese Academy of Agricultural Sciences

Abstract：The conceptual framework of agricultural production factors has long been anchored in a static-triad paradigm encompassing land, labor, and capital. This traditional model faces persistent challenges in surmounting the bottlenecks that impede the qualitative advancement of agricultural productive forces. A critical imperative thus emerges: to fundamentally reconfigure the operational logic and redefine the boundary dimensions of the agricultural system through the innovative allocation of production factors. This transformation is essential to establish a foundational underpinning for cultivating agricultural new quality productive forces. Accordingly, this study constructs a theoretical framework positioning the innovative allocation of production factors as a fundamental driver of agricultural new   quality productive forces, conducts a diagnostic assessment of the core bottlenecks hindering the innovative allocation of agricultural production factors, and further proposes corresponding policy suggestions. Our investigation reveals: innovation in traditional factors is constrained by: persistent structural contradictions coupled with an aging workforce; dual bottlenecks comprising inefficient land transfer mechanisms and land fragmentation; and a diminishing trend in capital input. Innovation in emerging factors confronts practical challenges such as: the dual constraints of  ″digital incapacity″ and lagging institutional supply; and ethical and biosafety risks inherent in the application of emerging technologies (e.g., biotechnology). The transition between traditional (″old″) and emerging (″new″) factors is hampered by structural contradictions: insufficient investment in agricultural science and technology; fragmented governance structures and platform deficiencies that impede structural coupling; and divergent factor attributes that complicate systemic adaptability, consequently escalating the difficulty of institutional regulation. To address these challenges, it is imperative to adhere to Xi Jinping Thought on Socialism with Chinese Characteristics for the New Era, uphold the principles of preserving the essence while fostering innovation and prioritizing people-centered development. Guided by a tripartite strategic approach-entailing institutional supply, technology-driven development, and robust data governance-we advocate a phased implementation pathway. This involves short-term breakthroughs, mid-term deepening, and long-term restructuring. Concretely, this requires optimizing the allocation of traditional factors, systematically deploying the innovative application of emerging factors, and synergistically resolving the structural contradictions inherent in the old-new factor transition.

Key Words：agricultural new quality productive forces; factors of production; production relations; factor allocation

College of Agriculture and Rural Development, Renmin University of China

Abstract：Raising rural residents′ income is central to narrowing the urban-rural income gap and achieving common prosperity. Using county-level panel data from 2016 to 2023 and taking the 2021 implementation of the targeted assistance policy for counties in rural revitalization as a quasi-natural experiment, this paper employs a difference-in-differences (DID) framework combined with spatial econometric models to systematically evaluate the policy′s impact on rural residents′ per capita disposable income, its regional heterogeneity, and spatial spillover effects. The findings are as follows: (1) The targeted  assistance policy significantly increases the per capita disposable income of rural residents in pilot counties, and this conclusion remains valid across multiple robustness tests; (2) The policy exerts its income-increasing effect mainly through promoting non-agricultural employment, expanding financial support, and increasing educational investment; (3) There are significant regional differences in the policy effect, with more prominent effects in non-ethnic minority areas, non-revolutionary base areas, areas with low natural disaster risks, and non-ecological function zones; (4) The policy has significant spatial spillover effects, which also drive income growth in neighboring counties. In view of this, while maintaining the overall stability of the policy, we should strengthen differentiated regional assistance and cross-regional coordination mechanisms to improve the overall effectiveness of the policy.

Key Words：targeted assistance policy for counties in rural revitalization; per capita disposable income of rural residents; non-agricultural employment transfer; spatial spillover effect; regional heterogeneity

a.School of Management; b.Research Center for Green Development and Environmental Governance,Jiangsu University

Abstract：Enhancing agricultural ecological network resilience is a key guarantee for maintaining sustainable agricultural development and strengthening the defense line of agricultural ecological security. As an important agricultural core area and agricultural ecological security barrier in China, the improvement of resilience in the Yangtze River Economic Belt is of great significance to the stable development of regional and national agriculture and the realization of agricultural ecological security goals. Based on the theory of complex networks, on the basis of constructing a resilience evaluation index system, combined with methods such as kernel density estimation and Geographical Detector, the spatial-temporal characteristics, influencing factors and improvement paths of agricultural ecological network resilience in the Yangtze River Economic Belt from 2000 to 2023 are revealed. The research finds that the spatial structure of the agricultural ecological network in the Yangtze River Economic Belt is unbalanced. In terms of temporal evolution characteristics, the resilience level shows a fluctuating and intermittent upward trend, and the resilience level of each region generally presents a distribution characteristic of ″downstream>upstream>midstream″. Spatially, it presents an overall pattern of ″higher in the north and lower in the south″. Kernel density estimation indicates that the overall resilience of the agricultural ecological network in the Yangtze River Economic Belt has improved, but the growth rate in the downstream is fast, the polarization in the upstream and midstream has weakened, and the spatial differences across the region first expanded and then converged. Markov chain analysis indicates that the resilience level of the Yangtze River Economic Belt is prone to type transfer under different time spans, and tends to develop positively as the time span increases; after considering the spatial effect, the transfer of resilience level shows significant spatial dependence and weakens the ″grade locking″ phenomenon. Analysis of influencing factors indicates that the dominant factor for the resilience level has shifted from the optimization of planting structure to the improvement of waterlogging control; the key synergy combination has shifted from ″planting structure×agricultural insurance″ to ″waterlogging control×agricultural insurance″, and financial support for agriculture needs to be coordinated with other elements to exert an efficiency enhancement effect. The improvement path indicates that the enhancement of resilience level requires the differentiated implementation of single-driven, dual-driven or regional linkage strategies according to regional dominant factors.

Key Words：agricultural ecological network resilience; Yangtze River Economic Belt; spatial-temporal characteristics; waterlogging control; agricultural insurance

1.School of Mathematics and Information; 2.School of Economics and Management,South China Agricultural University

Abstract：Inclusive finance is a critical pillar for the comprehensive revitalization of rural areas. However, due to weak industrial foundations and insufficient endogenous capacity, smallholder farmers have long faced challenges of credit self-exclusion. Drawing on the theory of capability poverty and embeddedness theory, this paper constructs an integrated ″Embedding-Empowerment-Synergy″ analytical framework. Using the practices of Resident First Secretaries in District C, City S, Eastern Guangdong as a case study, it systematically elucidates the mechanisms and pathways through which they empower smallholders to integrate into inclusive finance.The research finds: First, a phased synergy mechanism is constructed. Through a staged collaborative mechanism of ″directly embedding policy resources-indirectly building a symbiotic network of entities-mutually embedding the integration of primary, secondary, and tertiary industries″, the Resident First Secretaries dynamically consolidate the foundation of distinctive rural industries, thereby addressing the suppression of credit demand among smallholders. Second, multidimensional empowerment pathways are optimized. By leveraging policy tools, standardizing production technologies, and digitalizing market channels, they systematically remediate the capability deficits of smallholders and reshape their confidence and behavioral logic regarding credit participation. Third, innovative organizational interest-linking mechanisms are developed. Centered on ″risk sharing and credit accumulation″, these mechanisms foster innovation in financial instruments and the integration of industrial chains. This promotes a shift among smallholders from passive beneficiaries to active participants, enabling their effective engagement in inclusive finance.The paper proposes: refining the design of adaptable inclusive finance policies and strengthening financial instrument innovation; optimizing the selection and assessment mechanisms for Resident First Secretaries to enhance their capabilities in resource integration and digital governance; and reinforcing the guiding role of Party building to promote holistic integration and facilitate the convergent development of industrial chains and financial chains.

Key Words：inclusive finance; first secretary in the village; embedded governance; ability poverty; interest connection

1.School of Economics and Trade, Henan University of Technology

2.Institute of Agricultural Economy and Development，Chinese Academy of Agricultural Sciences

Abstract：Against the backdrop of the burgeoning digital economy, the pilot zones for inclusive financial reform have emerged as an innovative model to synergistize advance balanced economic development and social equity. Utilizing panel data from 278 prefecture-level cities in China spanning 2012 to 2023, this study employs the entropy weight method to measure common prosperity across three dimensions—developmental, shared, and sustainable aspects. By constructing a policy variable for the inclusive financial reform pilot and applying Difference-in-Differences (DID) and Double Machine Learning (DDML) methodologies, an empirical analysis is conducted. The findings reveal that the pilot policy significantly enhances the level of common prosperity in the respective regions, exerting positive effects on its developmental, shared, and sustainable dimensions, with the most pronounced improvement observed in the shared dimension. Mechanism analysis indicates that inclusive financial reform fosters common prosperity by boosting entrepreneurial activity, improving capital circulation efficiency, and promoting capital market integration. Heterogeneity analysis further demonstrates that the promoting effect of inclusive financial reform on common prosperity is more substantial in cities with higher levels of economic development and digital infrastructure. Additionally, under the influence of the inclusive financial reform policy, the relationship between educational resource investment, financial service capacity, and common prosperity exhibits an ″inverted U-shaped″ pattern. Further analysis suggests that the coordinated implementation of the ″Broadband China″ strategy and the inclusive financial reform policy yields a more significant synergistic effect in promoting common prosperity. This research provides empirical evidence for a deeper understanding of the role of inclusive financial reform in advancing common prosperity, holding important implications for driving high-quality economic development and achieving common prosperity.

Key Words：financial inclusion reform; common prosperity; dual machine learning; double difference method; ″double pilot″ policy

1. College of Management, Sichuan Agricultural University

2. Institute of Rural Development, Sichuan Academy of Social Sciences

Abstract：Using microdata from the China Land Economic Survey (CLES), This study empirically analyzes the influence of industrial integration on farmers′ green production transition and its mechanism.The analysis follows the dual perspectives of farmers′ decision preference and factor allocation using OLS models. The main findings are as follows. Firstly, industrial integration can promote the green production transformation of farmers. After controlling for potential endogenous problems and conducting various robustness tests, the research conclusions remain consistent. Furthermore, the driving effect is more obvious in the prenatal material input stage and the production management stage, from the perspective of the production process. Secondly, Improved industrial integration has significantly promoted the green production transformation of farmers, but the effects of different integration models vary. Among them, the internal integration type and the functional expansion type exhibit a significantly stronger incentive effect on the green production transformation of farmers than the chain extension type and the technology penetration type. Thirdly, from the perspective of decision preference, it is found that farmers′ decision preference has a moderating effect between industrial integration and green production transformation. Lower time preference (i.e., the more they prefer long-term returns) and higher risk preference conelate with more significant driving effect of industrial integration. Fourthly, from the perspective of factor allocation, it is found that the radiating  driving effect of industrial integration is more prominent in farmers with large land scales, high land fertility, and non-agricultural employment and  factor allocation characteristics. Fifthly, the analysis of the mediating effect shows that social networks and environmental literacy serve as important transmission paths for  industrial integration influences the farmers′ green production transformation.

Key Words：industrial integration; green production transformation; radiation theory; decision preference; factor allocatio

1,Enter for Studies of Media Development; 2,School of Journalism and Communication,Wuhan University

Abstract：The precise targeting of low-income assistance recipients has long been plagued by information asymmetry between the state and farmers, leading to targeting errors and institutional distortion. Based on multi-site fieldwork experiences, this study analyzes how the integration of ″virtual income″ intelligent calculation and multi-departmental data comparison mechanisms through big data technology transforms the ambiguous ″actual income″ in rural society into clear and quantifiable ″virtual income″, significantly enhancing the state′s ability to verify eligibility for low-income assistance and, to a certain extent, resolving the predicament of targeting errors. The research finds that the application of big data technology not only reverses the information advantage structure within the bureaucratic organization (superiors over subordinates) and between the state and society (state over farmers), but also drives the governance mechanism to shift from the ″contractual delegation″ model relying on grassroots agents to a ″co-governance″ model led by the state. On this basis, the study further proposes a ″information dimension″ theory of state governance, providing a new perspective for understanding the governance transformation in the process of China′s modernization.

Key Words：minimum living allowance; big data; national governance; certification capacity; digital governance

School of Public Administration，Guizhou University of Finance and Economics

Abstract：Village cadres are the key subjects of rural governance in structure, but they may not all be effective forces to promote good governance in terms of initiative. Based on the structural theory, this study introduces the analytical concept of  ″backbone village cadres″ and constructs an Explanatory framework of  ″institutional structure-action ability″ to reveal why Core village cadres, as endogenous subjects, can support the improvement of rural governance efficiency. It is found that the formation of Core village cadres is constrained or motivated by the triple institutional logic of science, market and society in the field of village governance. Its core feature is that it can transform structural constraints into governance kinetic energy through the practice of compound adjustment mechanism of discourse translation, capital reconstruction and consensus production, so as to realize the synergy of policy implementation, economic development and village stability. The Core village cadres transcend the generalized types of village cadres under the single structural constraints or individual characteristics, which is helpful to break through the passive governance of the previous ″stimulus-response″ model, and also helps to break through the traditional elite narrative thinking of village cadres, providing a new theoretical tool for understanding the effectiveness of rural governance.

Key Words：village cadres;rural governance;institutional structure;action ability

1.School of Economics and Management, Northwest University

2.Institute for Six-Sector Economy, Fudan University

Abstract：The Fourth Plenary Session of the 20th Central Committee of the Communist Party of China proposed to enhance internal driving forces and provide stratified and categorized assistance to underdeveloped regions. Scientific identification of underdeveloped areas is the foundation for improving assistance mechanisms and achieving common prosperity. A framework for the endogenous development momentum of underdeveloped regions was constructed from three dimensions economic growth, social development, and ecological environment and nine indicators. Using the AF method, a stratified and classified analysis was conducted based on 1433 county-level samples in 2022.The research identified 413 underdeveloped counties and 112 deeply underdeveloped counties based on the criterion that there are five or more and seven or more indicators of shortcomings simultaneously. The contribution of economic growth, social development and ecological environment to the index of shortcomings decreases in sequence.Among them, economic aggregate and fiscal level are the main shortcomings in the category of economic growth, educational attainment is the main shortcoming in the category of social development, and green coverage is the main shortcoming in the category of ecological environment. Among the special types of regions, the degree of underdevelopment, from high to low, is as follows: national key counties for rural revitalization assistance, counties that have been lifted out of poverty, counties for ethnic minorities, counties with ecological functions, counties in old revolutionary base areas, and counties along land borders. The underdeveloped areas are mainly distributed in the western and central regions, with a small number also distributed in the east. It is suggested that stratification be carried out based on the degree of shortage of indicators, and classification be made according to the contribution of each indicator to the shortboard index, so as to formulate more precise assistance policies. The research conclusion provides a scientific basis for establishing a stratified and classified assistance system during the 15th Five-Year Plan period.

Key Words：underdeveloped regions; endogenous development momentum; shortcoming index; assistance policies