深圳市新移民社会空间分异

基于第六次全国人口普査数据,通过计算分异指数、隔离指数和区位爛,分析了深圳这一典型移民城市的新移民社会空间格局及其分异状况,并采用线性回归模型深入探讨新移民空间分异的影响因素,在此基础上与广州市进行对比。研究表明:1)深圳的社会空间存在5类人口因子,出现精英阶层聚居区、工薪阶层聚居区、离退休人口聚居区、本地村镇人口聚居区和新移民聚居区5类社会阶层聚居区。2)新移民在空间分布总体上表现出“差序格局”:由关内(福田区、罗湖区、南山区和盐田区)到关外(宝安区、龙岗区、光明新区、龙华新区、坪山新区和大鹏新区),“省内新移民”减少而“省外新移民”增加。3)深圳新移民与本地常住人口的分异指数为0.47,隔离指数为0.64,与广州新移民的指数相比,深圳新移民的隔离程度较高。4)制度因素(户口属性)对深圳新移民聚居区的影响减弱,市场因素的作用正不断增强,符合“市场转型论”的假设。同时人口和家庭因素对新移民聚居有一定影响,其中年龄结构和教育水平是影响新移民聚居的重要因素。5)对比广州市,广州新移民聚居同时受到制度因素和市场因素的双重影响,户籍制度影响依然具有一定的历史延续性,同时年龄结构与婚姻状况也具有显著影响。由此可见,新移民的空间分异及其影响机制具有异质性,深圳市作为改革开放的窗口,体现T中国社会主义市场转型对社会空间的影响效应。

Socio-spatial Segregation of New Migrants in Shenzhen,China

Boosted by industrialization and urbanization, China’s economy has become more oriented to growth. Along with this trend, the “urban era” is emerging, and the gap between rich and poor is increasing sharply within China’s cities. Available living space is therefore being rapidly reconstructed, and social space continuously differentiated. On the basis of data from the Sixth National Census, this paper explores the socio-spatial differentiation of the new migrants in Shenzhen, a typical migrants’ city in China, through calculations of the dissimilarity index, the isolation index and the Location Quotient. In addition to applying a linear regression model, this paper also analyzes the factors influencing spatial differentiation of new migrants in Shenzhen and compares these with Guangzhou to explore the similarities and differences of socio-spatial differentiation and its influencing mechanism in different cities. The empirical analysis shows that, first, there are five types of social spaces in Shenzhen, including elite-stratum neighborhoods, working-class ghettos, retired-population neighborhoods, urban villages, and new-migrant neighborhoods. Second, the spatial distribution of new migrants is uneven at the city level: the intra-province migrants are more concentrated inside the special economic zone (SEZ) of Shenzhen (where Futian District, Luohu District, Nanshan District and Yantian District locate), while inter-province migrants concentrate outside the SEZ (where Baoan District, Longgang District, Guangming New District, Longhua New District, Pingshan New District and Dapeng New District locate). Third, the dissimilarity index between the new migrants and the local residents is 0.47 and the isolation index is 0.64 in Shenzhen, higher than the same indices in Guangzhou, which indicates a higher degree of isolation among new migrants in Shenzhen. Moreover, there are significant differences on the degree of isolation between the districts of the SEZ and those outside the SEZ. This situation mainly stems from the differences in the level of economic development and the industrial structure, which is different from the suburbanization of migrants dominated by market factors in other Chinese cities like Guangzhou. Fourth, the results of the linear regression model show that the effects of institutional factors (Hukou-account attributes) on the spatial pattern of new migrants have decreased, while the role of market factors is increasing in this regard, in line with the assumption of “transition to a market-oriented economy”. Besides, demographic characteristics have significant influence on the spatial pattern of new migrants, especially with regard to the effects of age and educational level. Fifth, by contrast, the spatial pattern of new migrants in Guangzhou is impacted not only by the dual influences of institutional and market factors but also by the age structure and marital status. The household registration system continues to exert influence on spatial patterns in Guangzhou. It can be seen that the socio-spatial differentiation of new migrants and its mechanism show a pattern of heterogeneity in different cities. At the leading edge of the reform and opening-up policy, Shenzhen reflects the characteristics of social space under the influence of China’s transformation of socialist market. After the reform and opening-up policy more than 30 years ago, the shifting influences of “system-market” factors and the effect of the transition are particularly evident in Shenzhen. Against the historical background of the government and the market’s influence, the socio-spatial pattern in urban China is gradually developing into a “market-oriented” model.