面向提高全民科学素质服务的统计指标降维方法及应用研究  

Investigating statistical index dimension reduction methods and applications to enhance national scientific quality

作　　者：程豪 Cheng Hao(National Academy of Innovation Strategy CAST,Beijing 100038,China)

机构地区：[1]中国科协创新战略研究院,北京100038

出　　处：《今日科苑》2024年第1期78-93,共16页Modern Science

基　　金：国家自然科学基金委青年科学基金项目(项目编号:72001197);国家统计局全国统计科学研究项目(项目编号:2021LY052);北京工商大学数字商科与首都发展创新中心项目(项目编号:SZSK202317)。

摘　　要：科学素质是国民素质的重要组成部分,是社会文明进步的基础。本文从《中国科学技术协会统计年鉴2022》中关于提高全民科学素质服务的指标数据出发,通过统计描述的方法刻画科普基础设施建设、科普宣讲活动、科普传播等方面的基本情况。在此基础上,聚焦基层服务全民科学素质工作开展情况,进一步反映基层科普的基本规律和特点。面对科普指标数量较多的问题,本文采用经典的主成分分析方法,分别对全指标体系和经业务判断删除部分指标后的指标体系进行主成分降维分析,以期为相关部门进行指标修订和删减提供参考与借鉴。Scientific literacy is an important component of national quality and the foundation of social civilization and progress.The starting point for this article is from the indicator data in the"Statistical Yearbook of the China Association for Science and Technology 2022"on improving the scientific literacy services forthe entire population,and uses statistical description methods to depict the basic situation of science popularization infrastructure construction,science popularization propaganda activities,and science popularization dissemination.On this basis,the article focus on the development of grassroots services for the scientific literacy of the whole people,and further reflect the basic laws and characteristics of grassroots science popularization.To address the issue of a large number of popular science indicators,this article utilizes the traditional principal component analysis method to conduct principal component dimensionality reduction analysis on the entire indicator system and the indicator system after deleting some indicators through business judgment,in order to provide reference and reference for relevant departments to revise and delete indicators.

关 键 词：全民科学素质 基层组织 主成分分析 

分 类 号：G63[文化科学—教育学]