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作 者:李娉[1] 杨宏山[2] Li Ping;Yang Hongshan(School of Humanities and Social Sciences,North China Electric Power University,Beijing,102206,China;School of Public Administration and Policy,Renmin University of China,Beijing,100872,China)
机构地区:[1]华北电力大学人文与社会科学学院,北京102206 [2]中国人民大学公共管理学院,北京100872
出 处:《公共管理学报》2022年第3期71-83,170,共14页Journal of Public Management
基 金:国家社科基金重大项目(19ZDA123);中央高校基本科研业务费专项资金资助(2022MS055)。
摘 要:政策试验既是决策系统通过方法设计,科学识别政策效果的过程;也是增进政社互动,提升政策合法性的行动。政策试验的已有文献多关注于府际互动的宏观制度安排,对知识生产的微观行动机制研究较少。本文基于知识生产的视角,区分了政策试验过程中知识生产的四种模式:技术测试、方案组合、回应学习、综合调适;选择Y市四项垃圾分类试点进行案例研究,总结知识生产的发生逻辑。研究发现,当议题的客观性强,需提供确定性知识时,政策试验遵循科学检验逻辑,设定刚性指标,通过演绎法、溯因法开展知识生产,证实或修正已有认知;当议题的社会性较强时,政策试验采取倡议机制,提供柔性激励,构建包容性学习网络,鼓励试点方进行知识创造,基于协商议事生成新方案。知识整合者、转译者、践行者三方的持续互动,推进了知识分享与政策生成。知识生产不仅为理解政策试验提供了新的理论视角,对于提升政策试验的有效性也具有启示:决策系统既要构建激励相容的制度安排,规避试点方的策略性行为;也要搭建容纳多方主体的议题网络,推进系统化的知识生产。Policy experimentation is not only a process for policymakers to scientifically identify the effects of policies,but it is also an action to enhance the interaction between politics and society.The existing research of policy experimentation mostly focuses on the institutional arrangement of intergovernmental interaction,and there are few literatures on the micro action mechanism of knowledge production.The objective of this paper is to distinguish four modes of knowledge production in policy experimentation process from the perspective of knowledge production:Technical testing,scheme combination,response learning,and comprehensive adapta-tion.And then an exploratory multi-case study,involving four garbage classification pilot projects in Y city,was conducted to summarize the knowledge production logic.The analysis reveals that when the objectivity of the issue is strong and certain knowledge needs to be provided,the policy experimentation follows the logic of scientific examination,sets rigid indexes,carries out knowledge production through deductive and abductive methods,and confirms or revises the existing cognition.When the issue is in social field,the policy experimentation adopts the initiative mechanism,provides flexible incentives,constructs the inclusive learning network,encourages the pilot implementer to carry out knowledge creation,and generates new schemes based on consultation and discussion.Continuous interaction of knowledge integrator,translator and practitioner promote knowledge sharing and policy generation.And this study not only constructs an analytical framework for policy experimentation,but also provides enlightening suggestions to improve the effectiveness of policy experimentation:The decision-making system needs to ensure incentive compatibility of pilot designs to avoid the strategic behavior of pilots.But it is also necessary to build a network of issues that can accommodate multiple actors to promote systematic knowledge production.
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