太阳成8722(中国)有限公司-GREEN NO.1

标题: What Dominates the Female Class Identification? Evidence From China

作者: Cheng, P (Cheng, Peng); Zhou, J (Zhou, Jing); Jiang, P (Jiang, Ping); Zhang, ZJ (Zhang, Zhijun)

来源出版物: FRONTIERS IN PSYCHOLOGY 卷: 12 文献号: 627610 DOI: 10.3389/fpsyg.2021.627610 出版年: FEB 22 2021

摘要: In advocating gender equality today, we should not only pay attention to women's social status but also call for the women's psychological identification of class equality. What dominates female class identification? To answer this question, based on the data of the Chinese General Social Survey (CGSS) in 2015, this study constructs a female class identity framework from five aspects: the mother's intergenerational influence, female personal characteristics, lifestyle, gender consciousness, and spouse status. In this study, the ordered logit model is used to empirically analyze the impact of various factors on female class identification, and the results show the following: (1) gender consciousness has a significant impact on female class identification. (2) Lifestyle has a significant impact on the situation of having a spouse. (3) Spouse status has a significant positive effect on female class identification. But (4) the mother's intergenerational influence has no effect on female class identification. Therefore, this paper suggests that we should improve laws and regulations to protect women's normal rights, encourage women to establish an independent and self-improvement character, and enhance the class consciousness of women, especially rural women, in order to achieve the overall improvement of female class and psychological identification.

入藏号: WOS:000626024400001

PubMed ID: 33692726

语言: English

文献类型: Article

作者关键词: female class; gender equality; psychological identification; ordered logit model; China

地址: [Cheng, Peng; Jiang, Ping] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

[Zhou, Jing] Guangxi Univ, Sch Publ Adm, Nanning, Peoples R China.

[Zhang, Zhijun] MNR, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen, Peoples R China.

通讯作者地址: Jiang, P (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.

电子邮件地址: longkangkang@whu.edu.cn

影响因子：2.067