[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"item-3594":3,"related-3594":37},{"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,"search_phrases":31,"slug":34,"view_count":35,"doi":8,"paper":8,"created_at":36},3594,"云南举办林下经济'政科企'对接活动——'农科云品'品牌培育孵化平台集中亮相","https:\u002F\u002Fwww.yn.news.cn\u002F20260925\u002Fef619cfaa5204d0daa6e5729af1564fc\u002Fc.html","云南省林下经济'政科企'对接暨'农科云品'助农增收招商推介昆明专场在云南省农业科学院举办。活动由昆明市人民政府、云南省林业和草原局、云南省农业科学院、中国农业科学院都市农业研究所、云南省投资控股集团有限公司主办，以'聚林下势能 塑云品品牌'为主题。'农科云品'依托农产品全链条数字化运营体系，整合全省农林优质资源，构建直播电商、供应链协同、品牌孵化于一体的产业矩阵。9月22日至24日，第九届中国农民丰收节暨'农科云品'助农增收产销对接活动在云南省农科院品牌运营中心开展，共设置标准展位280个。",null,"新华网云南频道 2026-09-25","2026-09-25T00:00:00Z","报道",10,false,65,{"impact":16,"substance":17,"depth":18,"authority":19,"freshness":20,"relevant":21,"comment":22},18,15,13,12,7,1,"省级政科企对接活动，含数字化运营与品牌孵化实质内容，但属常规推介报道，增量有限。",[24],{"name":9,"url":6},[26,27,28,29,30],"数字乡村","农产品电商","林下经济","品牌孵化","政科企对接",[32,33],"云南 农科云品 林下经济","云南省农科院 农科云品 产销对接","云南农科云品林下经济-3594",0,"2026-09-27T00:05:16.850557Z",{"total":38,"page":21,"page_size":38,"items":39},6,[40,80,111,133,167,200],{"id":41,"title":42,"url":43,"summary":44,"summary_zh":45,"content":8,"source_name":46,"source_url":43,"published_at":47,"category":48,"cover_url":8,"hotness":12,"is_selected":13,"score":49,"score_detail":50,"sources":55,"tags":57,"search_phrases":61,"slug":64,"view_count":35,"doi":65,"paper":66,"created_at":79},3264,"Rural industrial integration and household-driven scale in agribusiness: the role of e-commerce sales and contract premium","https:\u002F\u002Fdoi.org\u002F10.3389\u002Ffsufs.2026.1897280","Rural industrial integration (RII) serves as a core pathway for driving comprehensive rural revitalization, with leading agribusiness firms acting as key drivers of this integration while also bearing the important social responsibility of promoting the development of rural households. To investigate the impact of RII on the scale of households driven by leading agribusiness firms, this study employed panel data from monitoring surveys of leading agribusiness firms in Jiangxi Province from 2021 to 2023, and applied random-effects models and mediation models for analysis. The results show that (1) RII significantly expands the scale of households driven by leading agribusiness firms (2) exploratory boundary condition analyses suggest that this promoting effect appears to be relatively stable across firms with different debt levels and management quality levels; and (3) mechanism analysis reveals that e-commerce sales serves as a significant transmission pathway through which RII influences the expansion of household scale, with its indirect effect being positive and statistically significant; the transmission effect of the contract premium pathway, however, does not receive sufficient statistical support. Based on these findings, we recommend the continued promotion of rural industrial integration, with a focus on supporting the development of e-commerce sales channels, while cautiously exploring and refining the contract premium mechanism.","农村产业融合（RII）是推动乡村全面振兴的核心路径，而农业产业化龙头企业既是这一融合的关键驱动者，也承担着带动农户发展的重要社会责任。为探究农村产业融合对龙头企业带动农户规模的影响，本研究采用江西省2021年至2023年龙头企业监测调查的面板数据，运用随机效应模型和中介模型进行分析。结果表明：（1）农村产业融合显著扩大了龙头企业带动的农户规模；（2）探索性边界条件分析显示，这一促进效应在不同负债水平和管理质量水平的企业间似乎相对稳定；（3）机制分析发现，电商销售是农村产业融合影响农户规模扩大的显著传导路径，其间接效应为正且具有统计显著性；而合同溢价路径的传导效应则未获得充分的统计支持。基于上述发现，我们建议继续推进农村产业融合，重点支持电商销售渠道的发展，同时审慎探索和完善合同溢价机制。","Frontiers in Sustainable Food Systems","2026-09-23T00:00:00Z","论文",77,{"impact":51,"substance":52,"depth":53,"authority":18,"freshness":12,"relevant":21,"comment":54},16,21,17,"基于江西省龙头企业2021—2023年面板数据的实证研究，证实产业融合通过电商渠道带动农户规模扩张，结论对数字乡村与联农带农政策有参考价值。",[56],{"name":46,"url":43},[26,27,58,59,60],"订单农业","农村产业融合","农业龙头企业",[62,63],"江西 龙头企业 农村产业融合","农产品电商 订单农业 农户","江西龙头企业农村产业融合-3264","10.3389\u002Ffsufs.2026.1897280",{"doi":65,"openalex_id":67,"authors":68,"venue":46,"cited_by_count":35,"oa_url":43,"card":72,"direction":76,"ingested_from":78},"W7214063617",[69],{"name":70,"orcid":71},"Jian Zhou","https:\u002F\u002Forcid.org\u002F0009-0000-9869-364X",{"tldr":73,"method":74,"finding":75,"direction":76,"opportunity":77},"基于江西龙头企业面板数据，研究农村产业融合如何带动农户规模。","2021-2023年江西龙头企业面板数据，随机效应与中介模型。","产业融合显著扩大带动农户规模，电商销售是有效中介，合同溢价机制不显著。","数字乡村与农业信息化","可探究电商销售中介的异质性及合同溢价失效原因，优化利益联结机制。","openalex","2026-09-23T23:30:07.244996Z",{"id":81,"title":82,"url":83,"summary":84,"summary_zh":8,"content":8,"source_name":46,"source_url":8,"published_at":85,"category":48,"cover_url":8,"hotness":12,"is_selected":13,"score":86,"score_detail":87,"sources":91,"tags":93,"search_phrases":97,"slug":100,"view_count":35,"doi":101,"paper":102,"created_at":110},3244,"Determinants of farmers' intention to adopt agricultural e-commerce livestreaming: a sequential mixed-methods study in Beijing（农户农产品电商直播采纳意愿的驱动因素：北京序贯混合方法研究）","https:\u002F\u002Fwww.frontiersin.org\u002Fjournals\u002Fsustainable-food-systems\u002Farticles\u002F10.3389\u002Ffsufs.2026.1944907\u002Ffull","Frontiers in Sustainable Food Systems 10:1944907 发表研究：基于2026年北京农户序贯混合方法研究，综合扎根理论与结构方程模型探讨农户采纳农产品电商直播的意愿及其驱动因素。研究指出，农产品电商直播作为精准农业的关键应用，越来越多地采用人工智能（特别是人工神经网络）以提升作物预测、推荐、生产力和农事决策。研究识别出农户采纳意愿的核心驱动机制：相对优势、复杂性、兼容性、社会影响、感知风险以及政府支持等关键变量。研究强调了数字农商人才培养的重要性，为数字赋能小农户衔接大市场提供理论框架与政策启示。","2026-09-21T00:00:00Z",70,{"impact":19,"substance":88,"depth":51,"authority":18,"freshness":89,"relevant":21,"comment":90},20,9,"基于北京农户的序贯混合方法研究，方法规范、结论有新意，但属区域样本的学术成果，公共影响有限，适合作为主题页聚合素材而非头条精选。",[92],{"name":46,"url":83},[26,94,95,27,96],"农业人工智能","农户采纳","直播助农",[98,99],"北京 农户 农产品电商直播","农户采纳意愿 结构方程","北京农户农产品电商直播-3244","10.3389\u002Ffsufs.2026.1944907\u002Ffull",{"doi":101,"openalex_id":8,"authors":103,"venue":8,"cited_by_count":35,"oa_url":8,"card":104,"direction":76,"ingested_from":109},[],{"tldr":105,"method":106,"finding":107,"direction":76,"opportunity":108},"基于北京农户序贯混合方法，研究农产品电商直播采纳意愿的驱动因素。","扎根理论结合结构方程模型，调查北京农户采纳意愿数据。","相对优势、兼容性、社会影响、政府支持等显著影响农户采纳意愿。","可延伸至AI直播推荐、数字农商人才培养与政府支持政策的交互机制研究。","agent","2026-09-23T00:04:32.988284Z",{"id":112,"title":113,"url":114,"summary":115,"summary_zh":8,"content":116,"source_name":117,"source_url":8,"published_at":118,"category":11,"cover_url":8,"hotness":12,"is_selected":13,"score":119,"score_detail":120,"sources":123,"tags":125,"search_phrases":128,"slug":131,"view_count":35,"doi":8,"paper":8,"created_at":132},555,"屯溪区数字乡村:5G 茶园、智慧大棚、乡村直播间'三位一体'赋能乡村振兴","https:\u002F\u002Fwww.hkcd.com.hk\u002Fhkcdweb\u002Fcontent\u002F2026\u002F08\u002F13\u002Fcontent_8769470.html","安徽屯溪区紧扣'数字乡村'建设,将物联网、大数据、AI 技术根系深扎乡土。奕棋镇数字化大棚实现全自动播种+智能催芽,瑶干村植保无人机单日作业 500-600 亩,黎阳镇'微行知'农耕研学基地依托黄山学院食药用菌团队羊肚菌亩产达 876 公斤。江村直播间累计开播 200 余场,带动农产品销售额突破 150 万元。","數字的春風，不僅吹富了口袋，更吸引着遠方的「數字候鳥」棲居徽州鄉野。\n\n走進屯光鎮篁墩村，一座以「星際移民」為理念的數字遊民公社隱於白牆黛瓦之間。DN黃山數字遊民公社建築面積達5251平方米，配套了涵蓋辦公、生活、社交等20餘類共享空間。自2025年3月正式開放以來，公社持續處於滿員狀態，吸引了大量文創、互聯網IP、設計等領域的高學歷從業者，平均停留時長達58天，成為數字青年棲居鄉野的理想之地。\n\n目光轉向奕棋鎮下林塘，「回來計劃」農文旅項目創新打造田園科創與數字遊民空間，已吸引30餘名數字遊民入駐，為鄉村發展注入新鮮活力。今年「五一」試營業以來，該項目累計接待市民遊客超9000人次，營業額達13.2萬元。\n\n數字遊民走進了鄉村，鄉土的好物也走了出去。教育繳費、醫療健康、養老服務等10餘種民生場景藉由「慧黃山」平台植入鄉村。數據多跑路，群眾少跑腿，「留下來」變得從容，「走出去」不再艱難。\n\n讓算法聽懂農時，讓數據認得來路，讓遠方的人願意留下，讓留下的人望得見遠方。在屯溪，數字與鄉土，本就可同一種顏色。(記者 吳敏 通訊員 程夢君)","香港商报网 2026-08-13","2026-08-13T04:00:18Z",43,{"impact":121,"substance":19,"depth":12,"authority":38,"freshness":20,"relevant":21,"comment":122},8,"地方数字乡村案例报道，有具体数据但深度一般，信源为地方媒体。",[124],{"name":117,"url":114},[26,126,127,27],"安徽","5G茶园",[129,130],"农产品电商 数字乡村 5G茶园 安徽","农产品电商 数字乡村","农产品电商数字乡村5G茶园安徽-555","2026-08-15T23:54:30.763197Z",{"id":134,"title":135,"url":136,"summary":137,"summary_zh":8,"content":8,"source_name":138,"source_url":8,"published_at":139,"category":48,"cover_url":8,"hotness":12,"is_selected":140,"score":141,"score_detail":142,"sources":148,"tags":150,"search_phrases":155,"slug":158,"view_count":35,"doi":8,"paper":159,"created_at":166},3599,"数字赋能何以激发内生动力？——数字乡村建设的扶智扶志效应及其协同机制研究","https:\u002F\u002Fwww.toutiao.com\u002Farticle\u002F7689001773884834319","周迪、李书曼、王雪芹在《数量经济技术经济研究》2026年第9期发表。文章基于2018年与2020年县域数字乡村指数与中国家庭追踪调查（CFPS）的匹配数据，构建包含数字乡村建设、人力资本积累与个体努力程度的世代交叠理论模型，运用数值模拟呈现不同数字化水平下个体技能与信心的动态演化路径，并采用双重机器学习模型进行因果推断。研究发现：数字乡村建设整体上对脱贫地区个体的技能提升与未来信心均具有显著正向作用；扶智效应主要通过拓宽信息渠道与促进非农就业实现，扶志效应借助改善职业环境与提升收入达成；对低技能、原深度连片贫困县和山区县的群体产生更为明显的扶志扶智效应。","三农直通车（今日头条）2026-09-24","2026-09-24T00:00:00Z",true,84,{"impact":143,"substance":144,"depth":145,"authority":146,"freshness":38,"relevant":21,"comment":147},22,23,19,14,"核心期刊论文，基于CFPS与县域数字乡村指数匹配数据，方法新颖、结论可靠，对数字乡村激发内生动力具有政策参考价值。",[149],{"name":138,"url":136},[26,151,152,153,154],"双重机器学习","非农就业","CFPS","扶智扶志",[156,157],"数字乡村 扶智扶志 CFPS","县域数字乡村指数 双重机器学习","数字乡村扶智扶志CFPS-3599",{"doi":8,"openalex_id":8,"authors":160,"venue":8,"cited_by_count":35,"oa_url":8,"card":161,"direction":76,"ingested_from":109},[],{"tldr":162,"method":163,"finding":164,"direction":76,"opportunity":165},"基于县域数字乡村指数与CFPS数据，实证检验数字乡村建设对脱贫地区个体的扶智扶志效应及协同机制。","世代交叠模型数值模拟与双重机器学习因果推断，匹配2018、2020年县域数字乡村","数字乡村建设显著提升脱贫地区个体技能与未来信心，扶智靠信息渠道与非农就业，扶志靠职业环境与收入改善。","可探究数字乡村扶智扶志效应的长期动态演化及不同数字化水平的门槛与空间溢出效应。","2026-09-27T00:05:18.097742Z",{"id":168,"title":169,"url":170,"summary":171,"summary_zh":172,"content":8,"source_name":173,"source_url":170,"published_at":139,"category":48,"cover_url":8,"hotness":12,"is_selected":13,"score":35,"score_detail":174,"sources":176,"tags":178,"search_phrases":180,"slug":183,"view_count":35,"doi":184,"paper":185,"created_at":199},3567,"Dira App: AI-Driven Decision Support for Career Path and Employment Opportunity Recommendations: A Case Study of Tanzania","https:\u002F\u002Fdoi.org\u002F10.37284\u002Feajit.9.2.5847","Career and employment decisions among Tanzanian secondary school students and graduates are still largely shaped by informal advice from parents, relatives, and peers rather than by objective, data-driven guidance. Graduate unemployment in Tanzania remains high, and structured support for self-employment remains limited. This paper presents the Dira App, Dira being the Swahili word for \"compass\", reflecting the system's role in helping users navigate career and employment decisions. It is a web and mobile Decision Support System (DSS) that combines a machine learning Career Predictor, an AI assistant (Dira AI) that personalises guidance using each user's academic history and predictions, and a booking and video counselling subsystem for continuous, personalised support. The system was developed using Agile methodology on a Vue.js, Flask, and PostgreSQL stack. A questionnaire-based needs assessment of 114 respondents (20 secondary students and 94 graduates) confirmed the problem: 60% of graduate respondents were unemployed, only 7% were formally employed, and a combined 86% expressed willingness to pursue self-employment, while career decisions among student respondents were shown to be predominantly influenced by parents and peers. These findings directly informed the system's functional requirements, architecture, and machine learning feature set. The resulting system integrates five core subsystems: role-based User Management, ML Career Prediction, Dira AI, Booking & Video Counselling, and Reporting & Analytics behind a secure, role-based interface. The developed system successfully centralised user profiling and career\u002Femployment data, automated personalised recommendation generation through a Career Predictor trained with a Random Forest Classifier (test accuracy 94.76%, train accuracy 95.66%), and supported continuous AI-driven and human counsellor guidance for informed career decision-making. The evaluation reported here is limited to a single-institution needs assessment and functional\u002Ftechnical testing rather than field deployment with end users, and the predictive model was trained on data reflecting the Tanzanian context, which may limit generalisability elsewhere. By combining locally grounded predictive modelling with continuous AI-driven and human-counsellor support, the Dira App directly addresses both the local data gap and the continuity gap identified in existing career guidance literature, offering a validated, replicable decision support model for other resource-constrained East African institutions.","坦桑尼亚中学生和毕业生的职业与就业决策在很大程度上仍由父母、亲戚和同伴的非正式建议所塑造，而非基于客观的数据驱动指导。坦桑尼亚的毕业生失业率仍然居高不下，而对自主创业的结构性支持依然有限。本文介绍了Dira应用，Dira在斯瓦希里语中意为“指南针”，体现了该系统帮助用户导航职业与就业决策的作用。它是一个基于网页和移动端的决策支持系统（Decision Support System, DSS），集成了机器学习职业预测器、利用每位用户的学业历史和预测结果提供个性化指导的AI助手（Dira AI），以及用于持续个性化支持的预约与视频咨询子系统。该系统采用敏捷方法论，基于Vue.js、Flask和PostgreSQL技术栈开发。一项基于问卷的需求评估调查了114名受访者（20名中学生和94名毕业生），证实了上述问题：60%的毕业生受访者处于失业状态，仅7%有正式工作，合计86%表示愿意从事自主创业，而学生受访者的职业决策被证明主要受父母和同伴影响。这些发现直接为系统的功能需求、架构和机器学习特征集提供了依据。最终形成的系统集成了五个核心子系统：基于角色的用户管理、机器学习职业预测、Dira AI、预约与视频咨询，以及报告与分析，均置于安全的基于角色的界面之后。所开发的系统成功实现了用户画像和职业\u002F就业数据的集中管理，通过使用随机森林分类器（测试准确率94.76%，训练准确率95.66%）训练的职业预测器自动生成个性化推荐，并支持持续的AI驱动和人工咨询师指导，以促进明智的职业决策。本文所报告的评价仅限于单一机构的需求评估和功能\u002F技术测试，而非面向最终用户的实地部署，且预测模型是在反映坦桑尼亚背景的数据上训练的，这可能限制其在其他地区的普适性。通过将扎根当地的预测建模与持续的AI驱动及人工咨询师支持相结合，Dira应用直接弥补了现有职业指导文献中发现的本地数据缺口和连续性缺口，提供了一种经过验证、可复制的决策支持","East African Journal of Information Technology",{"impact":35,"substance":35,"depth":35,"authority":35,"freshness":35,"relevant":35,"comment":175},"该论文聚焦坦桑尼亚学生职业与就业决策支持系统，属教育信息化与就业服务领域，与三农、农业信息化、智慧农业、数字乡村等主题无直接关联，不建议进入每日精选。",[177],{"name":173,"url":170},[26,94,179],"就业决策支持",[181,182],"Dira App 坦桑尼亚","AI 职业推荐 决策支持系统","DiraApp坦桑尼亚-3567","10.37284\u002Feajit.9.2.5847",{"doi":184,"openalex_id":186,"authors":187,"venue":173,"cited_by_count":35,"oa_url":192,"card":193,"direction":197,"ingested_from":78},"W7214211658",[188,190],{"name":189,"orcid":8},"Ester Philipo Lulale",{"name":191,"orcid":8},"Alfred Kajirunga","https:\u002F\u002Fjournals.eanso.org\u002Findex.php\u002Feajit\u002Farticle\u002Fdownload\u002F5847\u002F6175",{"tldr":194,"method":195,"finding":196,"direction":197,"opportunity":198},"开发Dira App，用机器学习与AI助手为坦桑尼亚学生和毕业生提供职业与就业决策支持。","敏捷开发Vue.js\u002FFlask\u002FPostgreSQL，随机森林分类器，114人","60%毕业生失业，86%愿自雇；职业预测模型测试准确率94.76%。","农业人工智能与决策模型","可将该职业决策支持框架迁移至农业领域，为农户或农技人员提供就业与创业智能推荐。","2026-09-26T23:30:50.413537Z",{"id":201,"title":202,"url":203,"summary":204,"summary_zh":205,"content":8,"source_name":206,"source_url":203,"published_at":10,"category":48,"cover_url":8,"hotness":207,"is_selected":13,"score":208,"score_detail":209,"sources":211,"tags":216,"search_phrases":221,"slug":224,"view_count":35,"doi":225,"paper":226,"created_at":248},3562,"Toward Common Prosperity: Spatially Heterogeneous Effects and Mechanisms of Digital Village Construction on the Urban–Rural Income Gap in Mountainous China","https:\u002F\u002Fdoi.org\u002F10.3390\u002Fland15101801","Mountainous regions are critical to promoting inclusive growth and reducing spatial inequality worldwide. Digital village construction offers a new pathway to overcome geographical constraints and reshape urban–rural income distribution in these areas. Using county-level data for 2020 and focusing on mountainous China, this study integrates the Theil index, IV-2SLS, MGWR, and mediation models to characterize the spatial pattern of the urban–rural income gap (URIG) and identify the spatially heterogeneous effects and potential mechanisms of digital village construction across different geomorphological settings. The results indicate that: (1) Large and highly dispersed URIG are concentrated in mountainous regions. On average, the gap is approximately twice as large as that in non-mountainous regions and varies markedly across geomorphological types. URIG is highest in mountain counties, shows the greatest variation in plateau counties, and tends to be lower in hill counties. (2) Digital village construction exerts a significant negative effect on URIG in mountainous China, with the effect being stronger than in non-mountainous regions and generally increasing in magnitude from east to west. (3) The effects of different DVI dimensions on URIG exhibit substantial spatial heterogeneity and vary in their spatial scales of influence. Rural economy digitalization shows widespread and consistently negative effects and emerges as the dominant dimension across most mountainous regions, while the effect of other dimensions is more localized, particularly rural life digitalization, which shows stronger negative effects in mountain counties, plateau counties, and underdeveloped mountainous counties. (4) Agricultural operation modernization and labor allocation optimization constitute potential channels underlying the association between digital village construction and a narrower URIG, with the estimated indirect effect being more pronounced through labor allocation optimization. These findings provide empirical evidence for advancing inclusive development in mountainous regions amid China’s common prosperity agenda, with broader implications for place-based digital village construction.","山区对于促进包容性增长和缩小全球空间不平等至关重要。数字乡村建设为这些地区突破地理约束、重塑城乡收入分配格局提供了新路径。本研究以2020年县级数据为基础，聚焦中国山区，综合运用泰尔指数、IV-2SLS、MGWR和中介模型，刻画城乡收入差距（URIG）的空间格局，并识别数字乡村建设在不同地貌条件下的空间异质性效应及其潜在机制。结果表明：（1）规模较大且高度分散的URIG集中于山区。其平均值约为非山区的两倍，且在不同地貌类型间差异显著。URIG在山区县最高，在高原县变异最大，在丘陵县则趋于较低水平。（2）数字乡村建设对中国山区URIG具有显著负向影响，其效应强于非山区，且总体上呈自东向西递增态势。（3）数字乡村建设不同维度对URIG的影响表现出显著的空间异质性，且其影响的空间尺度各异。农村经济数字化呈现出广泛且稳定的负向效应，并在大多数山区成为主导维度，而其他维度的效应则更具局部性，尤其是农村生活数字化，在山区县、高原县及欠发达山区县表现出更强的负向效应。（4）农业经营现代化和劳动力配置优化构成数字乡村建设与URIG缩小之间关联的潜在渠道，其中通过劳动力配置优化的间接效应更为明显。上述发现为中国共同富裕议程下推进山区包容性发展提供了经验证据，并对因地制宜推进数字乡村建设具有更广泛的启示。","Land",25,80,{"impact":16,"substance":143,"depth":16,"authority":18,"freshness":89,"relevant":21,"comment":210},"基于县域数据的实证研究，方法扎实、结论对山区数字乡村政策有参考价值，但属学术论文，公共传播热度有限。",[212,213],{"name":206,"url":203},{"name":214,"url":215},"MDPI Land 15(10), 1801 2026-09-25","https:\u002F\u002Fwww.mdpi.com\u002F2073-445X\u002F15\u002F10\u002F1801",[26,217,218,219,220],"县域经济","农业数字化","山区农业","城乡收入差距",[222,223],"数字乡村 城乡收入差距 山区","县域 数字乡村 泰尔指数","数字乡村城乡收入差距山区-3562","10.3390\u002Fland15101801",{"doi":225,"openalex_id":227,"authors":228,"venue":206,"cited_by_count":35,"oa_url":203,"card":243,"direction":76,"ingested_from":78},"W7214349448",[229,232,235,238,240],{"name":230,"orcid":231},"Xueting Yang","https:\u002F\u002Forcid.org\u002F0000-0003-4633-2185",{"name":233,"orcid":234},"Xiaoping Qiu","https:\u002F\u002Forcid.org\u002F0000-0001-6310-5959",{"name":236,"orcid":237},"Fubiao Zhu","https:\u002F\u002Forcid.org\u002F0000-0002-4606-3336",{"name":239,"orcid":8},"Mingkai Xu",{"name":241,"orcid":242},"Yun Xu","https:\u002F\u002Forcid.org\u002F0000-0002-2442-7792",{"tldr":244,"method":245,"finding":246,"direction":76,"opportunity":247},"研究数字乡村建设对中国山区城乡收入差距的空间异质性影响及机制。","用2020年县级数据，结合泰尔指数、IV-2SLS、MGWR与中介模型。","数字乡村建设显著缩小山区城乡收入差距，效应自东向西增强，且存在地貌与维度异质性。","可深入探究不同地貌下数字乡村各维度的空间尺度差异及劳动力配置中介的微观路径。","2026-09-26T23:30:38.665617Z"]