[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-2405":3,"related-2405":71},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":8,"published_at":10,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":14,"score_detail":15,"sources":23,"tags":25,"primary_topic":8,"secondary_topics":31,"classification":32,"search_phrases":56,"slug":59,"view_count":40,"doi":8,"paper":60,"created_at":70},2405,"信息基础设施建设与农民共同富裕：来自中国地级市面板数据的证据","https:\u002F\u002Fwww.ebiotrade.com\u002Fnewsf\u002F2026-9\u002F20260909171624823.htm","Sage Open。基于2010-2024年中国252个地级市面板数据，实证分析信息基础设施建设如何影响农民共同富裕。研究显示信息基础设施建设显著有助于提升农民共同富裕水平；异质性分析表明在市场化程度较高的地区正向效应更为明显，地形复杂地区效应显著减弱。机制分析揭示农村创业活力和产业结构升级是重要传导通道。门槛效应分析证实双重门槛特征。",null,"Sage Open | 2026-09-09","2026-09-09T00:00:00Z","论文",10,false,76,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,22,17,13,6,1,"基于252个地级市十年面板数据的实证研究，机制与门槛分析扎实，对数字乡村政策有参考价值，但属学术论文且时效性一般。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字乡村","农民增收","共同富裕","信息基础设施","农村创业",[],{"status":33,"locked":13,"version":34,"method":35,"evidence":36},"unclassified","2026-10-22.2","rules",{"candidates":37,"agricultural_evidence":54,"reason":55},[38,44,49],{"code":39,"score":40,"supported":13,"title":41,"abstract":42,"tags":43},"G4",2,[],[],[28,30],{"code":45,"score":21,"supported":13,"title":46,"abstract":47,"tags":48},"G6",[],[],[27],{"code":50,"score":21,"supported":13,"title":51,"abstract":52,"tags":53},"I6",[],[],[26],true,"缺少足够的主题证据",[57,58],"信息基础设施 共同富裕 农村创业 农民增收","信息基础设施 共同富裕","信息基础设施共同富裕农村创业农民增收-2405",{"doi":8,"openalex_id":8,"authors":61,"venue":8,"cited_by_count":62,"oa_url":8,"card":63,"direction":67,"ingested_from":69},[],0,{"tldr":64,"method":65,"finding":66,"direction":67,"opportunity":68},"基于252个地级市面板数据，实证检验信息基础设施对农民共同富裕的影响及机制。","2010-2024年地级市面板数据，固定效应、异质性、机制与门槛回归。","信息基础设施显著促进农民共同富裕，市场化高地效应更强，地形复杂区减弱，创业与产业升级为通道。","数字乡村与农业信息化","可探究信息基础设施对农户内部收入差距的非线性影响及数字鸿沟的调节作用。","agent","2026-09-14T00:06:33.691383Z",{"total":20,"page":21,"page_size":20,"items":72},[73,147,214,269,321,365],{"id":74,"title":75,"url":76,"summary":77,"summary_zh":78,"content":8,"source_name":79,"source_url":76,"published_at":80,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":81,"score_detail":82,"sources":85,"tags":87,"primary_topic":91,"secondary_topics":96,"classification":97,"search_phrases":124,"slug":127,"view_count":62,"doi":128,"paper":129,"created_at":146},5581,"How Does Digital Literacy Promote Inclusive Rural Growth? Micro-Level Evidence from Income Inequality Among Farm Households","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fsu182010689","Against the backdrop of the coordinated advancement of digital village construction and the common prosperity strategy, the widespread improvement in rural households’ digital literacy is emerging as a key force in reshaping rural income distribution and enabling sustainable rural development. Whether digital dividends can equitably benefit farm households with heterogeneous endowments has a direct bearing on the inclusive growth outcomes of digital village construction and the sustainable advancement of the common prosperity goal. Using three waves of panel data from the China Family Panel Studies (CFPS) covering 2018 to 2022, this paper empirically examines the impact of digital literacy on income inequality among rural households. The findings indicate that improvements in digital literacy significantly reduce rural household income inequality, and this conclusion remains robust across a series of robustness checks. Mechanism analysis reveals that digital literacy mainly curbs the widening of rural household income gaps through two core channels: expanding social capital and alleviating credit constraints. Heterogeneity analysis shows that the inequality-reducing effect of digital literacy is more pronounced among households that depend on non-agricultural income, have lower levels of human capital, or fall into relatively lower income brackets. Further analysis demonstrates that digital literacy significantly reduces inequalities in wage income, business income, and property income across rural households, whereas its mitigating effect on transfer income inequality is not statistically significant. Meanwhile, digital literacy significantly raises the probability of upward income mobility among rural households, thereby alleviating income inequality from a dynamic perspective. On the basis of these findings, this paper proposes policy implications in several areas: building a hierarchical and categorized rural digital literacy cultivation system, fostering a virtuous cycle of digital empowerment, equal opportunity, and income convergence, and optimizing income distribution structures and dynamic mobility mechanisms, with the aim of accelerating progress toward common prosperity.","在数字乡村建设与共同富裕战略协同推进的背景下，农户数字素养的普遍提升正成为重塑乡村收入分配格局、实现乡村可持续发展的重要力量。数字红利能否公平惠及禀赋异质性农户，直接关系到数字乡村建设的包容性增长成效与共同富裕目标的可持续推进。本文利用中国家庭追踪调查（CFPS）2018—2022年三期面板数据，实证检验数字素养对农户收入不平等的影响。研究发现，数字素养的提升显著降低了农户收入不平等，这一结论在一系列稳健性检验后依然成立。机制分析表明，数字素养主要通过拓展社会资本与缓解信贷约束两条核心渠道抑制农户收入差距的扩大。异质性分析显示，数字素养的减不平等效应在依赖非农收入、人力资本水平较低或处于相对较低收入区间的农户中更为明显。进一步分析发现，数字素养显著缩小了农户工资性收入、经营性收入和财产性收入的不平等，而对转移性收入不平等的缓解作用在统计上不显著。同时，数字素养显著提高了农户收入向上流动的概率，从而从动态视角缓解了收入不平等。基于上述发现，本文从构建分层分类的农户数字素养培育体系、形成数字赋能—机会均等—收入收敛的良性循环、优化收入分配结构与动态流动机制等方面提出政策启示，以期为加快共同富裕进程提供参考。","Sustainability","2026-10-21T00:00:00Z",80,{"impact":16,"substance":17,"depth":16,"authority":19,"freshness":83,"relevant":21,"comment":84},9,"基于CFPS三期面板数据的微观实证，方法规范、结论有新意，对数字乡村与共同富裕政策有参考价值，值得进入每日精选。",[86],{"name":79,"url":76},[26,88,28,89,90],"数字素养","农民收入","收入不平等",{"code":50,"slug":92,"name":93,"path":94,"parent_code":95},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":98,"locked":13,"version":34,"method":35,"evidence":99},"classified",{"candidates":100,"agricultural_evidence":54},[101,107,113,120],{"code":50,"score":102,"supported":54,"title":103,"abstract":104,"tags":106},8,[],[26,105],"digital village",[26,88],{"code":45,"score":20,"supported":54,"title":108,"abstract":109,"tags":112},[],[110,111],"农户收入","rural income",[],{"code":114,"score":115,"supported":54,"title":116,"abstract":117,"tags":119},"G",3,[],[118],"rural development",[],{"code":39,"score":21,"supported":13,"title":121,"abstract":122,"tags":123},[],[],[28],[125,126],"CFPS 数字素养 农户收入","数字素养 农村收入差距","CFPS数字素养农户收入-5581","10.3390\u002Fsu182010689",{"doi":128,"openalex_id":130,"authors":131,"venue":79,"cited_by_count":62,"oa_url":76,"card":140,"direction":67,"ingested_from":145},"W7223105459",[132,135,138],{"name":133,"orcid":134},"Yong Feng","https:\u002F\u002Forcid.org\u002F0000-0002-8151-8594",{"name":136,"orcid":137},"Shuokai  kai Wang","https:\u002F\u002Forcid.org\u002F0009-0002-7439-1764",{"name":139,"orcid":8},"Fangping Cao",{"tldr":141,"method":142,"finding":143,"direction":67,"opportunity":144},"基于CFPS三期面板数据，实证检验数字素养对农户收入不平等的影响。","使用CFPS 2018-2022三期面板数据，进行机制与异质性分析。","数字素养通过扩展社会资本和缓解信贷约束显著缩小农户收入差距。","可延伸研究数字素养对不同收入来源不平等的差异化机制及动态收入流动路径。","openalex","2026-10-22T11:20:47.675827Z",{"id":148,"title":149,"url":150,"summary":151,"summary_zh":152,"content":8,"source_name":153,"source_url":150,"published_at":154,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":155,"score_detail":156,"sources":159,"tags":161,"primary_topic":165,"secondary_topics":166,"classification":167,"search_phrases":195,"slug":198,"view_count":62,"doi":199,"paper":200,"created_at":213},5469,"How institutional digitalization reshapes entrepreneurial activity in new agricultural business forms: quasi-natural experimental evidence from China's Digital Village Pilot Policy","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1946061","New agricultural business forms are a key driving force for developing countries to overcome the constraints of traditional agriculture and achieve sustainability in food systems. However, it remains unclear whether institutional digitalization can effectively stimulate entrepreneurial vitality in new agricultural business forms. This study develops a theoretical framework of “opportunity creation–opportunity identification–opportunity transformation” and treats China's Digital Village Pilot Policy (DVPP), implemented in 2020, as a quasi-natural experiment. Based on panel data from 1,743 counties in China from 2014 to 2023, this study employs Double Machine Learning (DML) and Spatial Durbin Difference-in-Differences (SDM-DID) models, among other methods, to systematically identify the impact, transmission mechanisms, heterogeneous effects, and spatial spillover effects of institutional digitalization on Entrepreneurial Activity in New Agricultural Business Forms (EANA). The results reveal that: (1) DVPP significantly enhances EANA, and this finding remains robust after a series of tests, including placebo tests, Propensity Score Matching–Difference-in-Differences (PSM-DID), Synthetic Control Method–Difference-in-Differences (SCM-DID), and instrumental variable (IV) estimation; (2) agricultural technological innovation, digital infrastructure development, and digital financial development serve as mediating mechanisms; (3) the policy effects are more pronounced in counties with higher levels of digital access, better-developed transportation infrastructure, and higher levels of digital financial development, exhibiting a pattern of Central > Western > Eastern regions, and are significantly stronger in areas with advantages in characteristic agricultural products; (4) DVPP generates a significant negative spatial spillover effect on EANA in neighboring counties. This study expands theoretical understanding of the relationship between institutional digitalization and entrepreneurship in new agricultural business forms and provides empirical evidence for China and other developing countries to optimize digital rural development and foster new agricultural business forms.","农业新业态是发展中国家突破传统农业约束、实现食物系统可持续发展的关键驱动力。然而，制度数字化能否有效激发农业新业态的创业活力仍不明确。本研究构建了“机会创造—机会识别—机会转化”的理论框架，并将中国2020年实施的数字乡村试点政策（Digital Village Pilot Policy，DVPP）视为准自然实验。基于中国1743个县2014—2023年的面板数据，本研究采用双重机器学习（Double Machine Learning，DML）和空间杜宾双重差分（Spatial Durbin Difference-in-Differences，SDM-DID）等模型，系统识别制度数字化对农业新业态创业活动（Entrepreneurial Activity in New Agricultural Business Forms，EANA）的影响、传导机制、异质性效应和空间溢出效应。结果表明：（1）DVPP显著提升了EANA，且该结论在经过安慰剂检验、倾向得分匹配—双重差分（PSM-DID）、合成控制法—双重差分（SCM-DID）和工具变量（IV）估计等一系列检验后依然稳健；（2）农业技术创新、数字基础设施建设和数字金融发展发挥中介机制作用；（3）政策效应在数字接入水平较高、交通基础设施较完善和数字金融发展水平较高的县更为显著，呈现出中部>西部>东部的格局，且在特色农产品优势区显著更强；（4）DVPP对邻近县的EANA产生显著的负向空间溢出效应。本研究拓展了关于制度数字化与农业新业态创业之间关系的理论认识，为中国及其他发展中国家优化数字乡村发展、培育农业新业态提供了经验证据。","Frontiers in Sustainable Food Systems","2026-10-20T00:00:00Z",85,{"impact":17,"substance":157,"depth":16,"authority":19,"freshness":83,"relevant":21,"comment":158},23,"基于1743个县面板数据的准自然实验，方法扎实、结论有政策参考价值，值得进入每日精选。",[160],{"name":153,"url":150},[162,26,163,164,30],"数字农业","县域经济","农业政策",{"code":50,"slug":92,"name":93,"path":94,"parent_code":95},[],{"status":98,"locked":13,"version":34,"method":35,"evidence":168},{"candidates":169,"agricultural_evidence":54},[170,175,182,186,190],{"code":50,"score":171,"supported":54,"title":172,"abstract":173,"tags":174},15,[105],[26,105],[26],{"code":176,"score":20,"supported":54,"title":177,"abstract":178,"tags":181},"I2",[],[179,180],"机器学习","machine learning",[],{"code":114,"score":115,"supported":54,"title":183,"abstract":184,"tags":185},[],[118],[],{"code":39,"score":40,"supported":13,"title":187,"abstract":188,"tags":189},[],[],[30,163],{"code":191,"score":21,"supported":13,"title":192,"abstract":193,"tags":194},"I1",[],[],[162],[196,197],"数字乡村试点 新农业业态","DVPP 农村创业","数字乡村试点新农业业态-5469","10.3389\u002Ffsufs.2026.1946061",{"doi":199,"openalex_id":201,"authors":202,"venue":153,"cited_by_count":62,"oa_url":150,"card":208,"direction":67,"ingested_from":145},"W7223041086",[203,205],{"name":204,"orcid":8},"Su Li",{"name":206,"orcid":207},"Changjun Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":209,"method":210,"finding":211,"direction":67,"opportunity":212},"用双重机器学习与空间DID评估数字乡村试点政策对新农业业态创业活力的影响。","基于1743县2014-2023面板数据，用DML与SDM-DID做准自然实验。","试点政策显著提升新农业业态创业，经技术创新、数字基建与数字金融中介，并对邻县有负向溢出。","可探究政策负向空间溢出的形成机制及跨县协同激励设计，避免创业资源虹吸。","2026-10-21T23:30:07.205317Z",{"id":215,"title":216,"url":217,"summary":218,"summary_zh":8,"content":8,"source_name":219,"source_url":8,"published_at":8,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":220,"score_detail":221,"sources":224,"tags":226,"primary_topic":230,"secondary_topics":234,"classification":235,"search_phrases":257,"slug":260,"view_count":62,"doi":8,"paper":261,"created_at":268},5361,"数智技术与农民增收:基于 31 省 2012-2023 年面板数据的影响效应与作用机制","https:\u002F\u002Ftwnt.fjnyxb.cn\u002F","基于 2012—2023 年 31 个省份面板数据并构建计量回归模型,系统探究数智技术发展对农民增收的影响效应与作用机制。研究发现:数智技术能显著推动农村居民可支配收入提升,结论经多重稳健性检验后依然成立。增收作用通过提升技术成果转化效率、培育粮食新质生产力两条路径实现。数智技术的增收效应存在显著异质性,在数字基础更优的东部地区、产业结构多元的非粮食主产区表现更为突出。DOI: 10.16006\u002Fj.cnki.twnt.2026.04.004。","《台湾农业探索》48(4):37-45 2026",74,{"impact":16,"substance":17,"depth":16,"authority":222,"freshness":40,"relevant":21,"comment":223},14,"基于31省11年面板数据的实证研究，方法规范、结论有新意，但属学术论文且发布日期不明，时效性弱，适合主题聚合而非每日精选。",[225],{"name":219,"url":217},[26,27,227,228,229],"数智技术","面板数据","粮食新质生产力",{"code":45,"slug":231,"name":232,"path":233,"parent_code":114},"rural-integration","帮扶与城乡融合","\u002Ftopic\u002Frural-services\u002Frural-integration",[],{"status":98,"locked":13,"version":34,"method":35,"evidence":236},{"candidates":237,"agricultural_evidence":54},[238,243,249,253],{"code":45,"score":239,"supported":54,"title":240,"abstract":241,"tags":242},12,[27],[27],[27],{"code":244,"score":115,"supported":54,"title":245,"abstract":246,"tags":248},"G1",[],[247],"成果转化",[],{"code":191,"score":21,"supported":13,"title":250,"abstract":251,"tags":252},[],[],[227],{"code":50,"score":21,"supported":13,"title":254,"abstract":255,"tags":256},[],[],[26],[258,259],"数智技术 农民增收","台湾农业探索 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