摘要
面对充满高度复杂性和不确定性的社会,政府政策通常蕴含着多重目标追求,且在复杂情景中催生差异化的政策执行和目标实现过程。聚焦于农村宅基地改革,试点地区就占有公平性拓展和资源利用效率性提升两大政策目标,表达了对特定目标的偏好并采取了相应的政策行动。Y县从占有公平性出发,优先推进"一户一宅""户有所居";后通过土地规划、宅基地使用权能放活等达成效率目标。L市则侧重政策的效率目标,通过引入市场机制优化资源配置;又在尊重农户意愿的基础上规范宅基地获得流程和过程协商,实现对公平目标的补偿。从偏好性目标确定到补偿性政策行动,两地达成改革的双重目标设定。案例经验表明,政策目标的实现具有显著的情景适应特性,阶段性情景定位构成目标确立的重要依据,补偿性政策行动则是应对目标失衡情景的重要举措,多重政策目标经由情景适应中的偏好与补偿行动得以协调发展,由此实现政策效能的最大化。
In the complex and uncertain society,government policies usually contain multiple goals,and form differentiated process of policy implementation and goal realization due to complex scenarios.Focusing on the rural homestead reform,the pilot areas expressed specific target preferences and policy actions,according to their objective situations—fairness and efficiency.Y County chose to give priority to fairness,concentrating on promoting“one household,one house”and ensuring“households have housing”.At the same time,through land scientific planning,land use rights releasing and other policy actions,to develop efficiency goal.L City more focuses on the efficient,working on introducing market mechanism to optimize resource allocation.Besides,the city took further action to compensate fair goals,such as standardizing the homestead acquisition process.From the establishment of preference goals to compensatory policy actions,both places achieved the pursuit of dual goals.Case experience shows,the realization of policy goals has significant characteristics of scenario adaptation.Phased scenario positioning constitutes an important basis for target establishment,while compensatory policy actions are important measures to cope with target imbalance scenarios.Multiple policy objectives can be coordinated through preference and compensation actions in situational adaptation,thereby maximizing policy effectiveness.
作者
袁方成
王丹
Yuan Fangcheng;Wang Dan
出处
《南京社会科学》
CSSCI
北大核心
2021年第11期56-65,共10页
Nanjing Journal of Social Sciences
基金
2020年度中宣部马克思主义理论研究和建设工程特别委托项目“基层群众自治制度研究”(2020MYB050)的阶段性成果。
关键词
政策目标
情景
宅基地
改革
治理
policy goal
scenarios
homestead
reform
governance
