Studying population flow patterns is essential for comprehending regional population changes and economic and social development trends. Using data from the sixth and seventh national population censuses to classify China's interprovincial population flows into four types: rural-urban, rural-rural, urban-urban, and urban-rural, this paper analyzes the spatial characteristics of population flow networks and their influencing factors using a spatial autoregressive negative binomial model. The results show that: The proportion of rural-urban and urban-urban population flows has increased, while the proportion of rural-rural population flows has decreased. Rural-rural and rural-urban population flows tend to move from west to east, while urban-urban and urban-rural population flows are diverse and bi-directional. China's population center is shifting from a single city (province) to an urban agglomeration. While economic factors play a significant role in rural-urban and rural-rural population flows, the factors influencing urban-rural and urban-urban population flows are complex and diverse. The degree of influence of economic factors on these flows is weakening.

Interethnic marriage can be viewed as a social relation system characterized by a set of ethnic groups and their intermarriage ties. Therefore, Interethnic marriage data are relational data. This paper is the first attempt to use social network analysis methods and tools to depict the structural characteristics of Interethnic marriage relations in China. Based on 2010 census data, this research suggests that a national Interethnic marriage circle centered on the Han nationality has formed. Meanwhile, there are 8 local intermarriage subcircles which consist of different minority ethnic groups. Such structure demonstrated a diversified but integrated Chinese nation. Social network analysis is a reliable and valid approach to understand the structure of Interethnic marriage relations. The graphical presentation of social networks, centrality measurement and community identification technology are especially useful.

Frailty index has been widely used to study the speed of change in frailty among older adults, and to depict the dynamic process of frailty caused by aging in recent years. Taking life course perspective as theoretical background, this study emphasizes the implications of observing and understanding the frailty trajectory within cohort, and also assumes that a framework for understanding the intra-cohort pattern of frailty should have three essential properties: random variability, trajectory heterogeneity, and cumulative disadvantage. Furthermore, relating these three properties to the specific parameters for growth curve models, datasets from China Longevity and Heath Longitudinal Survey is applied to test them. The primary results indicate that frailty trajectory follows a Ushaped curve, but there is significant betweenperson variation, and withingroup rather than between-group cumulative disadvantage mainly explains how the frailty trajectory differentiates.

Since China’ s reform and opening up，connections between the regions in China are getting increasingly closer，with more and more frequent population migration．The reason why people migrate from one region to another is because of the attraction of the inflow area．This paper uses the 6th national population census data and the attractiveness measurement indicator RIA to calculate the attraction index for China’ s 31 provinces．The result shows that the east coastal zone，which represented by Guangdong，Zhejiang，Shanghai， Jiangsu and Beijing，has the largest attraction for migrants．On the other hand，the far west region，defined as restricted development region，which represented by Gansu，Qinghai，Ningxia and Tibet，has the least attrac- tion for migrants．Policy implications are discussed regarding industrial upgrading，population control，environ- mental protection，and targeted poverty alleviation．

Using the data from the third wave survey of the Social Status of Women in China，this study investigates the inequality of both educational outcome and educational opportunity，and how they vary with cohorts. There are two main findings. First，regardless of gender，the degree of inequality of educational
outcome increases with cohorts，but the acceleration rate tends to decrease. This trend mainly results from the increase in both of the inequality of opportunity and the weight of importance which is due to the expansion of population at risk and the raised expected gain at the junior-to-senior high school transition. Second，among all cohorts，inequality of educational outcome for men is lower than for women，because women experience higher inequality of opportunity at all transitions，but the gender gap at every transition tends to vanish with cohort. The paper concludes with discussion of the methodological and substantive significance of this research.

Based on datasets from 1995 and 2002 China Household Income Survey,this paper investigates income and wealth inequality in urban China,with household as the unit of analysis.Analytic results suggest that most of inequality measures show a significant increase in income inequality,while a somewhat decrease in wealth inequality among urban households between 1995 and 2002.By demographic decompositions,we find that economic regions,household head’s education and the membership of CCP have more important contributions to overall household income and wealth inequalities.In general,for urban China from 1995 to 2002,the sorting mechanism plays a more important role in generating resource inequality among households.