从整体性治理到智能化精准——广州市数智化社会救助的运行机制与经验启示

From Holistic Governance to Intelligent Precision—The Operation Mechanism and Empirical Insights of Digital-Intelligent Social Assistance in Guangzhou

摘要: 针对传统社会救助存在的条块分割与被动响应治理困境，数智化转型提供了破局路径。文章立足于从整体性治理到智能化精准的理论演进逻辑，系统剖析了广州市数智化社会救助的运行机制。研究表明，广州依托“穗救易”救助平台，通过三大机制破解治理难题：一是组织协同机制，通过数据联动与线上线下协同打破部门壁垒，重塑整体性数据资源库；二是智能触发机制，基于大数据画像变被动申请为主动发现，大幅前置救助窗口期；三是精准匹配机制，依据数字画像实施分层分类，实现救助资源精准投放。该探索显著提升了社会救助的效能，但在实践中也面临数据隐私风险、数字排斥、基层压力增大、算法局限性等挑战。广州经验启示我们，数智化精准救助需坚持体制创新引领与多元主体协同，未来应通过推进数字包容、完善法律规制及赋予基层柔性裁量权，进一步推动数智化社会救助体系高质量发展。

Abstract: Digital transformation offers a viable path to overcome the governance dilemmas of fragmented authority and passive response inherent in traditional social assistance systems. Grounded in the theoretical evolution from holistic governance to intelligent precision, this paper systematically analyzes the operational mechanisms of Guangzhou’s digitalized social assistance. The study reveals that Guangzhou, leveraging its “Suijiuyi” platform, addresses these governance challenges through three core mechanisms: first, an organizational synergy mechanism, which breaks down departmental barriers via cross-departmental data linkage and online-offline collaboration to reshape a holistic data repository; second, an intelligent triggering mechanism, which utilizes big data profiling to shift the paradigm from passive application to proactive detection, thereby significantly advancing the assistance window; and third, a precision matching mechanism, which implements stratified and classified assistance based on digital profiles to achieve the targeted allocation of relief resources. This exploration has significantly enhanced the efficacy of social assistance, yet its implementation is confronted with challenges, including data privacy risks, digital exclusion, increased workload for grassroots workers, and limitations of algorithms. The Guangzhou experience indicates that digitally intelligent and precise social assistance must be driven by institutional innovation and multi-agent collaboration. Moving forward, the high-quality development of the digitalized social assistance system should be further propelled by promoting digital inclusion, perfecting legal and regulatory frameworks for data sharing, and empowering grassroots authorities with flexible discretionary power.