摘要
本研究基于北京大学2009年度全国高校毕业生就业抽样调查数据,针对社会科学研究中的高度复杂性、非线性和不确定性特征,运用复杂性科学研究中的神经网络拟合仿真方法,较好地分离出性别差异对我国高校毕业生就业工作特征和流动特征的影响。研究表明:性别因素将会导致10.89%的薪金差距;男性获得就业地户口的机率比女性高出9.27%;从整体上看,男女大学生就业单位性质的差异并不明显。相对上述就业工作特征,毕业生流动特征的性别差异较为显著:男性毕业生比女性具有更强的流动性,除了就业流动以外,上学流动、毕业流动的性别差异度分别是19.5%和23.77%,全流动差异更是达到了40.57%;而男女毕业生就业流动概率的差异度仅有2.77个百分点,其主要是女性的"流动惰性"所造成的。
This study is based on national employment survey data of college graduates by Peking university in 2009. For the highly complex, nonlinear and uncertain characteristics in social science research, the study make use of neural network fitting simulation method, to better isolate the impact degree of gender differences in job characteristics and flow characteristics in China. The results show that: gender will result in 10.89% wage gap; the probability of men access to account is 9.27% ??higher than women; in the whole; the nature difference of the employment unit between male and female college graduates is not significant. Relative to the above-mentioned job characteris- tics, flow characteristics of graduates have more significant gender differences: male graduates have a greater mobility than female. Except for employment flow, gender differences in school flow, working flow is 19.5% and 23.77%, gender differences in full flow is reached 40.57%. Gender differences in employment flow is only 2.77 percentage point, this is mainly caused by female's “current inertia ”.
出处
《教育与经济》
CSSCI
北大核心
2011年第2期1-7,共7页
Education & Economy
基金
普通高校人文社会科学重点基地重大项目(2009JJD880002)
教育部人文社会科学研究青年基金项目(10YJC880002)
中国博士后科学基金项目(20100470108)
关键词
复杂系统仿真
性别差异
高校毕业生
就业
simulation of complex systems
gender differences
college graduates
employment