摘要
【目的/意义】政策工具是政策目标实现的抓手,从政策工具视角探析智慧社区政策特征,以促进新时期智慧社区政策体系和制度框架的构建。【方法/过程】通过构建“政策结构-政策工具-政策主题”三维框架模型,运用文本计量法、社会网络分析法、内容分析法和LDA主题模型,对2012-2022年间106篇中央层面政策文本进行系统分析。【结果/结论】我国中央政策呈现发布量阶段性增长、发布主体多元化的特征;在政策工具的应用上,偏向于使用象征与劝诫型工具和能力建设型工具;政策工具与主题的适配性仍有待提升。建议进一步完善智慧社区政策体系、促进多元主体合作、优化政策工具的结构配置、强化政策工具与政策主题的契合度。【创新/局限】运用政策组合分析法,分别对政策结构属性和内容属性进行研究,为将来政策的科学制定提供理论参考,但并没有对央地政策差异、联系以及政策落实效能等内容进行研究,这些内容将作为后续努力的方向。
【Purpose/significance】 Policy tools are the keys to achieving policy objectives.Analyzing the characteristics of smart community policies from the perspective of policy tools is of great significance to the formulation of smart community policy systems and regulatory systems in the new era.【Method/process】 By building a three-dimensional framework of "policy structure-policy toolspolicy theme",and using text measurement,social network analysis,content analysis,and LDA topic model,we systematically analyzed 106 central policy texts from 2012 to 2022.【Result/conclusion】 China's central policies show a phased growth in release volume and a diversification of release entities;In the application of policy tools,it tends to use symbol and exhortation tools as well as capacity-building tools;The compatibility between policy tools and policy themes needs to be enhanced.It is recommended to further improve the policy system of smart communities,promote cooperation among multiple entities,optimize the structural configuration of policy tools,and strengthen the compatibility between policy tools and policy themes.【Innovation/limitation】 Using policy combination analysis method,both structural and content attributes of policies were studied,providing theoretical references for future formulation of scientific policies.However,we did not conduct research on the differences and connections between central and local policies,nor the effectiveness of policy implementation,which will serve as a direction for future efforts.
作者
俞露露
张洪艳
胡广伟
YU Lulu;ZHANG Hongyan;HU Guangwei(School of Information Management,Nanjing University,Nanjing 210023,China;Institute of Government Data Resources,Nanjing University,Nanjing 210023,China)
出处
《情报科学》
北大核心
2024年第2期24-34,55,共12页
Information Science
基金
国家社会科学基金重大项目“大数据驱动的城乡社区服务体系精准化构建研究”(20&ZD154)。