社会技术融合:政策信息学的由来、范畴与框架

Socio-technical Integration:The Origins,Scope and Framework of Policy Informatics

政策信息学是涉及政策科学、信息学等多学科的新兴交叉领域,从情报学视角去观察和梳理政策信息学的由来、范畴与框架,能为政策信息学提供学科发展的土壤,并增强情报学的话语权和生命力。首先,本文基于社会技术系统理论,从社会和技术两方面系统阐述了政策信息学的缘起由来,并阐明其研究范畴,对代表性概念及研究进行总结和辨析。其次,从社会技术融合视角构建了面向政策过程全生命周期的政策信息学分析框架,梳理政策信息学分析的研究问题、方法和工具。最后,对政策信息学的研究与应用进行展望,认为未来政策信息学将继续进行社会技术融合,并围绕全流程分析、全数据挖掘、全主体服务、全方位评价、全时空推演等五个方面深化拓展。图5。表3。参考文献66。

Policy informatics is an emerging interdisciplinary field that encompasses policy science, information science, and other related disciplines. Examining and organizing the origins, scope, and framework of policy informatics from the perspective of information science can provide a foundation for the development of relevant disciplines and enhancing the discourse and vitality of information science. Policy informatics arises from the policy analysis needs for social progress, technological innovation, and integration of social and technological factors. Through conceptual clarification and differentiation, this paper proposes that policy informatics is a comprehensive interdisciplinary field that encompasses the whole lifecycle of the policy process. It utilizes big data such as government document data, departmental transaction system data, and online public sentiment data as the foundation, while employing methods from public administration, computer science, and econometrics to conduct policy knowledge discovery and simulation. The ultimate goal is to achieve intelligent support of decision-making processes for government. Based on the “seven-stage theory” of policy process, this paper considers that the whole lifecycle of policy process includes four processes: policy problem, policy formulation, policy implementation and policy optimization. In combination with the information analysis process of information demand analysis, information organization and management, information dissemination and application, and information service optimization, a framework for policy informatics analysis is proposed, including policy demand mining, policy text metrics, policy result measurement, policy effect assessment and policy strategy simulation. This framework deeply reflects the nature of scientific and technological intelligence work as “detector, scout and consultant”,in which “detector” requires scientific and technological intelligence work to be able to search, scan and organize information for decision makers in the complex environment. The policy demand mining, text metrics and result measurement research are just manifestation. The “scout” adds a strategic and urgent dimension to basic intelligence, such as providing early warning by policy effects assessment. On the basis of “what” and “why”,“consultant” requires intelligence work to address the question of “how to do”,which is also an important manifestation of the function of scientific and technological intelligence as a think tank. In the future, policy informatics will continue to carry out social and technological integration, and deepen and expand around the five aspects of whole-process analysis, whole-data mining, whole-subject service, all-round evaluation, and whole space-time deduction. 5 figs. 3 tabs. 66 refs.