By studying the influencing indicators of women’s social status, we perform an ordered Logit regression analysis on the data of the China Comprehensive Social Survey in 2012, 2013 and 2015, and then select the assessment of self-social status in the female sample as the dependent variable. Using the impact indicators as independent variables to explore the impact of each variable on women’s social status. At the same time, applying k-means clustering analysis based on MapReduce to mine the relationship between employment and education level between different genders. We find out the fact that women have a high level of education does not necessarily result in good employment treatment. Gender discrimination in the Chinese labor market is also persistent.
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