摘要
家庭养老支持政策作为重塑家庭照料功能与纾解家庭照料困境的重要手段,对其进行科学评价是提高政策质量的前提基础。构建政策“工具—主题—属性”三维分析框架,通过人工编码对中国1999—2021年支持家庭养老的65项政策进行内容分析,并运用PMC指数模型重点对12项政策进行量化评价。研究发现:政府偏好运用供给型政策工具提供直接支持,而环境型和需求型工具发挥间接和拉动作用有限;政策主题以社区服务和贫困老人的经济救助为主,对带薪照料假等社会支持保障不足;政策属性以规范性政策文件为主,且作用客体对家庭整体和家庭照料者缺乏重点关注。12项具体政策的PMC均值为4.05,整体处于可接受范围。进而提出加强顶层设计、优化工具结构和丰富内容主题等建议。
As an important tool to reshape family care function and relieve family care dilemma,scientific evaluation of family care support policies is a prerequisite for improving policy quality.This study constructs a three-dimensional policy analysis framework of"instrument-theme-attribute"to analyze 65 policies on family eldercare in China from 1999 to 2021 and uses content analysis method through manual coding,and then selects the 12 specific policies to evaluate with the help of PMC index model.The results show that:the government prefers to use supply-based policy instrument to provide support directly,while environmental and demand-based instrument play limited indirect and stimulating roles;The policy theme mainly focuses on the community services and financial assistance for the elderly in poverty,with insufficient coverage of social support policies as paid care leave system;The policy attributes are mainly normative policy documents,and the object of action is lack of focus on the family as a whole and family caregivers.The average PMC of the 12 specific policies is 4.05,which is in the acceptable range overall.In the future,the policy system should be gradually improved in terms of strengthening the top-level design of policies,optimizing the structure of instrument and enrich the content themes of policies.
作者
李放
饶丹
沈苏燕
LI Fang;RAO Dan;SHEN Su-yan(College of Public Administration,Nanjing Agricultural University,Nanjing 210095,China)
出处
《人口与发展》
CSSCI
北大核心
2023年第3期84-95,共12页
Population and Development
基金
国家社科基金重大项目“农民获得更多土地财产权益的体制机制创新研究”(17ZDA076)
国家自然科学基金面上项目“子女抚育与城镇夫妻劳动配置研究:福利挤压的视角”(71974099)
江苏省社科基金青年项目“江苏农村困难群体养老服务精准化研究”(22SHC007)。
关键词
家庭养老支持政策
文本内容分析
量化评价
PMC指数
Family Eldercare Support Policies
Text Content Analysis
Quantitative Evaluation
PMC Index
