[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-4522":3,"related-4522":75},{"id":4,"title":5,"url":6,"summary":7,"summary_zh":8,"content":8,"source_name":9,"source_url":6,"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":52,"slug":55,"view_count":56,"doi":57,"paper":58,"created_at":74},4522,"Coupling coordination of digital village and county care industry for older adults","https:\u002F\u002Fdoi.org\u002F10.1186\u002Fs12877-026-08412-8","Coupling coordination of digital village and county care industry for older adults。BMC Geriatrics",null,"BMC 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建设22个单产提升整建制县","https:\u002F\u002Fwww.ln.gov.cn\u002Fweb\u002Fzwgkx\u002Fzfwj\u002Fszfbgtwj\u002F2026n\u002F2026101915441826587\u002Findex.shtml","规划要求农产品主产区县域深入实施新一轮千亿斤粮食产能提升行动，建设18个玉米单产提升整建制推进县、2个大豆与2个水稻整建制推进县。同时提出大力发展智慧农业，推广先进适用农机装备，稳步推进沿海盐碱地与辽西风沙地综合利用，构建「省级品牌+区域公用品牌+企业品牌」体系并提升特色农产品电商化率。","（十三）推进基础设施补短板。积极融入全省“六张网”建设，找准节点位置，打通基础设施“最后一公里”，提升县域安全韧性、产业要素、市场流通保障能力。融入全省水网建设格局，重点推动盘山、开原等灌区现代化改造，全面提升县域供水安全、粮食安全等保障能力，到2030年，农村自来水普及率达到98%。融入全省新型电网建设格局，重点推进康平、瓦房店等新型储能项目建设实施，提高城乡供电可靠性和防灾抗灾水平。实施县城老旧管网更新改造，统筹城乡防洪排涝，高质量推进城市更新，推进宜居县城建设，开展县城体检。健全县乡村三级物流配送体系，加强地邮协作，打造集中共配型县级客货邮综合服务中心、兼具中转和末端服务的乡镇客货邮综合服务站、“一站式”村级客货邮综合服务点，建有村级寄递物流综合服务站的建制村比例达到90%。实施新一轮农村公路提升行动，实现乡镇100%通双车道，建制村100%通等级路，农村公路铺装率达到98%。加快“双千兆”网络向农村延伸，缩小城乡数字基础设施差距，加快县城、乡镇和有条件的行政村接入网络10G-PON提质升级改造。加快建设提升一批农产品产地冷藏保鲜设施、农产品冷链仓储、农副产品批发市场，持续补齐农产品仓储物流产销等县域消费基础设施短板。\n\n（十四）加快推进基本公共服务均等化。强化中心镇和重点镇公共服务节点功能，引导公共服务直达基层末梢。落实县域普通高中振兴行动计划，到2030年，支持50所以上县域普通高中改善办学条件、提升办学质量，新建续建12所县域普通高中。根据人口变化统筹教育资源，优化农村学校布局，提高农村教育质量，加快城乡义务教育学校标准化建设。持续提升县级医院综合能力，深化紧密型县域医共体建设，提高乡镇卫生院基本医疗卫生服务水平。推进生育支持政策和激励措施落实，有效降低家庭生育养育教育成本，加强妇女和儿童健康服务。加强乡镇区域养老服务中心能力建设，探索村级邻里互助点、农村幸福院等农村互助性养老模式。深化农村移风易俗，提高社会文明程度，鼓励争创县级全国文明城市。","辽宁省人民政府 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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":88,"substance":190,"depth":16,"authority":191,"freshness":20,"relevant":21,"comment":192},23,13,"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。",[194],{"name":186,"url":183},[196,26,27,197,198],"数字农业","农业政策","农村创业",{"code":39,"slug":200,"name":201,"path":202,"parent_code":203},"digital-village","数字乡村与数据要素","\u002Ftopic\u002Fdigital-agriculture\u002Fdigital-village","I",[],{"status":110,"locked":13,"version":34,"method":35,"evidence":206},{"candidates":207,"agricultural_evidence":41},[208,212,219,224,228],{"code":39,"score":114,"supported":41,"title":209,"abstract":210,"tags":211},[43],[26,43],[26],{"code":213,"score":76,"supported":41,"title":214,"abstract":215,"tags":218},"I2",[],[216,217],"机器学习","machine learning",[],{"code":108,"score":125,"supported":41,"title":220,"abstract":221,"tags":223},[],[222],"rural 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Yang","https:\u002F\u002Forcid.org\u002F0009-0000-6236-3489",{"tldr":246,"method":247,"finding":248,"direction":72,"opportunity":249},"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":252,"title":253,"url":254,"summary":255,"summary_zh":8,"content":8,"source_name":256,"source_url":8,"published_at":187,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":257,"score_detail":258,"sources":260,"tags":262,"primary_topic":8,"secondary_topics":266,"classification":267,"search_phrases":280,"slug":283,"view_count":71,"doi":284,"paper":285,"created_at":293},5456,"数字赋能农业产业韧性的影响与机制研究——基于浙江省县域面板数据的实证分析 (Impact and Mechanism of Digital Development on Agricultural Resilience: Evidence from County-Level Data in Zhejiang Province)","http:\u002F\u002Fzgnjhxb.niam.com.cn\u002FCN\u002F10.13733\u002Fj.jcam.issn.2095-5553.2026.10.034","基于2014—2022年浙江省县域面板数据，用系统GMM检验数字经济对农业产业韧性的影响。数字经济有效赋能农业产业韧性，农村产业融合、涉农科技创新、农业产业化为重要传导机制。非山区县促进作用明显高于山区县。","中国农机化学报 2026-10-20",79,{"impact":16,"substance":88,"depth":18,"authority":191,"freshness":20,"relevant":21,"comment":259},"基于浙江县域面板数据的实证研究，方法规范、结论有新意，对数字乡村与农业韧性议题有参考价值，但属省级实证、影响范围有限。",[261],{"name":256,"url":254},[26,263,27,264,265],"农业经济韧性","农村产业融合","涉农科技",[],{"status":268,"locked":13,"version":34,"method":35,"evidence":269},"unclassified",{"candidates":270,"agricultural_evidence":41,"reason":279},[271,275],{"code":47,"score":56,"supported":13,"title":272,"abstract":273,"tags":274},[],[],[264,27],{"code":39,"score":21,"supported":13,"title":276,"abstract":277,"tags":278},[],[],[26],"缺少足够的主题证据",[281,282],"浙江省 县域面板 农业韧性","数字经济 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