我国美育政策工具的使用及改进策略--基于政策文本的分析

改革开放以来,我国美育政策体系建设取得了长足进步。作为达成政策目标的手段,美育政策工具对促进美育政策体系建设和美育功能的实现有着重要的作用。我国美育政策体系建设坚持从目标设定、任务规划、管理保障等方面不断进行调整、完善,不断适应教育改革与发展需求。但不可否认,我国美育政策工具的使用仍存在不足,有待进一步改进和完善。借助罗斯威尔和赛格菲尔德的政策工具分类理论,通过构建美育政策文本内容和政策工具类型的二维分析框架,对改革开放以来我国美育政策工具的使用情况进行全面系统的分析研究。研究发现,美育政策工具的使用呈现出三个明显的特征:供给型政策工具的使用较少;环境型工具的使用所产生的影响显著;需求型工具的使用明显不足。为增强政策工具效用、促进美育政策体系的完善,我国美育政策体系建设应进一步改进政策工具的使用,需要注重三个方面:补足美育政策工具短板,发挥政策工具使用的组合优势;细化美育政策实施标准,提升政策工具使用的精准度;建立和完善美育政策补充调整机制,增强政策工具使用的灵活性。     

从“精细化”到“精准化”:乡村公共服务供给的逻辑转向

“项目进村”是国家力量嵌入乡村社会治理的重要变量，也是重塑国家资源分配体制的重要渠道。现行资源下乡体制下，乡村公共服务“项目制”供给构筑了一整套“精细化”的公共产品分配、管理和输送体系。这在确保国家意图高效率投射乡村的同时，也因过度技术性的流程把控削减了对乡村实际面向的关照，从而出现产品供需脱节、服务目标替代、内生服务能力削弱等“公共服务弱化”的意外后果。对此，厘清涉及“需求识别”“定向配置”“长效管理”等价值的公共服务“精准化”供给逻辑，对改善“项目进村”效果具有重要现实意义。时下乡村公共服务“精准化”供给不仅应推动现有服务资源供给评价方式和多元参与模式的改良，也应促进公共服务数字赋能和内生机制的革新，实现“过程精细”和“结果精准”的有机结合。     

Effectiveness of random payment in Experiments: A meta-Analysis of dictator games

Monetary incentives remain an integral component of economics experiments. However, the experimental economics literature is inconclusive when it comes to the effectiveness of random payment mechanisms, specifically in non-strategic individual decision experiments. To contribute to the literature on incentives in experiments, this study performed a meta-analysis of 94 dictator game studies and examined the effect of two frequently used random payment mechanisms on behavior. The mechanisms analyzed were the random problem selection procedure (RPSP) and between-subject random incentivized system (BRIS). The meta-analysis showed that RPSP and BRIS did not significantly alter behavior when compared to a single incentivized decision and incentivizing all subjects, respectively. The results support the effectiveness of RPSP and BRIS in nonstrategic individual decision experiments.     

Statistical inference for Cox proportional hazards models with a diverging number of covariates

For statistical inference on regression models with a diverging number of covariates, the existing literature typically makes sparsity assumptions on the inverse of the Fisher information matrix. Such assumptions, however, are often violated under Cox proportion hazards models, leading to biased estimates with under-coverage confidence intervals. We propose a modified debiased lasso method, which solves a series of quadratic programming problems to approximate the inverse information matrix without posing sparse matrix assumptions. We establish asymptotic results for the estimated regression coefficients when the dimension of covariates diverges with the sample size. As demonstrated by extensive simulations, our proposed method provides consistent estimates and confidence intervals with nominal coverage probabilities. The utility of the method is further demonstrated by assessing the effects of genetic markers on patients' overall survival with the Boston Lung Cancer Survival Cohort, a large-scale epidemiology study investigating mechanisms underlying the lung cancer.     

细长轴加工精度问题的探讨

从细长轴的结构特点出发 ,分析了影响细长轴加工精度的因素 ,并针对产生误差的根源 ,从改变加工方式、工装结构和刀具参数等方面着手 ,提出了相应的解决措施