摘要
以12项代表性“双减”政策为研究对象,结合文本挖掘方法构建PMC指数模型,计算各项政策的PMC指数并绘制PMC曲面图。结果表明,所选取的12项代表性政策中,10项属于优秀级别,2项属于可接受级别。政策在校外培训机构监管、政策评价和政策成效方面表现良好,但在时效性和领域方面存在不足。
With 12 representatives of"double reduction"policies taken as the object of study,the PMC index model is constructed by integrating the text mining method,calculating the PMC index of each policy,and plotting the PMC surface chart.The results indicated that among the 12 representative policies selected,10 were of excellent level and 2 were of an acceptable level.While the policies perform favorably in the supervision of out-of-school training institutions,policy evaluation,and policy effectiveness,there are shortcomings in timeliness and domain.
作者
张筱
宇世航
ZHANG Xiao;YU Shi-hang(School of Science,Qiqihar University,Heilongjiang Qiqihar 161006,China)
出处
《齐齐哈尔大学学报(自然科学版)》
2023年第2期89-94,共6页
Journal of Qiqihar University(Natural Science Edition)
基金
黑龙江省高等教育教学改革项目(SJGY20200772)
齐齐哈尔大学学位与研究生教育教学改革研究项目(JGXM_QUG_2021012)
齐齐哈尔大学研究生创新科研项目(YJSCX2022059)。
关键词
双减
政策量化
PMC指数模型
double reduction
policy quantification
PMC index model