The Structural Analysis Of Women Migrant Workers Social Support Networks

Migrant workers, as a social vulnerable group, have been constructing the beautiful city, but they, especially the group of women, was subjected to unequal treatment at the same time. Thus, enhancing the female migrant workers’social support network is of a certain practical significance for continued resolving social conflicts, masses problems and for achieving social justice to promote women’s groups to better integrate into the city. In addition, it is benefit to promote the development of social interaction, social networks and social capital theory to be perfect.On the basis of the literature review, this paper updated research methods, trying to use the perspective of social network to dedicate to study structural characteristics, elements, content classification, value base and target paths of migrant workers’social support networks. Thus, we can understand women migrant workers’existing support networks objectively and systematically. The article made quantitative description through the social support factors’integration research.Finally,female migrant workers social support structure diagram and regression models were constructed. This study differs from previous micro-level individual network analysis (the tendency of subjective view), it uses the relationship as the unit of analysis,and it constructs and grasps the density and the core-edge structure of women migrant workers’social support network from a macro perspective.This study adopts positivist methodology, and the data is from the "Chinese General Social Survey"(CGSS) that Chinese National People’s Congress conducted from October to December,2008.This survey involved urban residents from28provinces and cities, and the content included employment, working and living conditions, and their thoughts about the current social issues. This study had a sample of households, and used SPSS, UCINET (University of California at Irvine NET work, translated as social network analysis)software to analyze the data. At the same time, by screening cases the article selected697cases from6000samples for analysis according to gender (female), the current account (agricultural accounts),the current nature of the work(non-agricultural)).Other variables selected are: gender,age, marriage, education level,household, employment, social sector knowledge,personal income,social mobility,the relationship between industry competitiveness, views about working by relationship and so on. And the research carried out detailed analysis and processing respectively from the social support network structure, social support network size, the level of social support network,social network density,network core measure latitude. In addition, to meet analysis’needs, the study constructed dummy variables such as social support score and the level of support networks which mean average score of career’s social prestige of the crowd the family contacted.The study found that compared with male migrant workers, female migrant workers had some characteristics, such as younger, unmarried tendencies and low level of education, and women migrant workers were in a weak position in the movement, employment, income and so on. Women migrant workers’social network density is smaller than male migrant workers’social network density. It shows women migrant workers’support network is sparse and is easy to form a social network structure where the core is industrial workers,chefs,cooks,unemployed,legal staff,the edge is college teachers,school teachers, doctors,nurses,hotel waiter,marketing, scientific researchers, economic business,administrative clerks, engineers, government agencies responsible person, the person in charge of party organizations, enterprises and institutions responsible person, the family nanny, hourly workers. Social support network of women migrant workers was constructed mainly in the scope of genetic, geographical, industry, and it showed the trend that relatives, geopolitical relations gradually extrapolated. The study also found that women migrant workers’overall network size was smaller than men migrant workers’and their human capital is also less than men. Data showed that the social network focused on0-5people mostly, its precise statistical average, women3.27, men3.58.Overall score of social support was between3-46. In the25%range, social support score was3-7points, and in the75%range, it was8-13points. The total average score was11.09, and males’was higher than females’, the average score of social support for men was11.48, and10.53for females. Also in the survey of665migrant workers, the average of network level is1.47, and the minimum value was0and the maximum was9.5.Finally, the paper constructed linear model about affecting migrant workers social support network. According to the model, contribution rate of human capital was63.8%, the objective support was19.5%, the net top was6%. These illustrated that social network level was affected by the human capital, objective support and industry that had the highest occupational prestige. After coming into the city, empirical factors, like the experience of the number of network people, had an impact on the characteristics of number of migrant workers social support network. The data showed that before movement, migrant workers account scored a minimum of3and a maximum of46, and after migration, the maximum value was25, the minimum was unchanged, and the average was dropped to10.85from the original 11.21. It showed the support from the community was reduced after migrant workers came into the city, and it revealed the score of number of social support network probably had an impact on attitude and behavior toward actors, and people who were of high network level were more competitive at work, and they could use relationship more flexible. So, higher requirements about constructing more female migrant workers’social support platforms were put forward. Whether microscopic or macroscopic, it was of positive significance to integrate social resources and it was helpful for women migrant workers utilizing of human capital and better integrating into society.