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河北省县域贫困度多维评估
引用本文:袁媛,王仰麟,马晶,魏海,彭建.河北省县域贫困度多维评估[J].地理科学进展,2014,33(1):124-133.
作者姓名:袁媛  王仰麟  马晶  魏海  彭建
作者单位:北京大学城市与环境学院地表过程分析与模拟教育部重点实验室, 北京100871
基金项目:国家自然科学基金重点项目(41130534)
摘    要:在京津冀加快区域经济一体化的背景下,河北省出现环绕京津地区的贫困带引起了学界与公众的普遍关注。目前国内贫困县的设定往往以经济指标为唯一度量标准,本文在经济维度基础上增加社会维度(代表人类贫困)和自然维度(代表自然贫困)两方面评价指标,构建县域贫困度多维评价指标体系,对河北省136 个县的贫困状况分别进行经济单维度与经济—社会—自然三维评估,并基于SOFM网络将全省县域贫困度划分为五级,与河北省现有各类贫困县分布进行对比。结果表明,基于经济单维度与经济—社会—自然多维度评估的聚类分析得到的高贫困度县域均与现有贫困县有很好的对应,与河北省贫困县分布现状基本吻合;由于经济—社会—自然的多维度贫困度评估综合考虑了贫困现状及其潜在可能性,评估更加全面和深入。基于自然维度的潜在贫困度对多维贫困度的影响分析表明:环京津地区的贫困现状比较严重、且潜在贫困程度高,应积极依托京津,承接产业转移。而在冀中南地区,尽管贫困现状较为严重,但潜在贫困程度较低,因其较易脱贫而容易被忽视;同时,还存在大量非贫困县转化为贫困县的可能性;应进一步加强对该地区贫困问题的关注,分类扶贫、防治结合、区域联动,促进京津冀区域一体化、社会财富同步增长。

关 键 词:SOFM  多维贫困度  河北省  经济—社会—自然  潜在贫困度  
收稿时间:2013-08-01
修稿时间:2013-11-01

Multidimensional evaluation of county poverty degree in Hebei Province
YUAN Yuan,WANG Yanglin,MA Jing,WEI Hai,PENG Jian.Multidimensional evaluation of county poverty degree in Hebei Province[J].Progress in Geography,2014,33(1):124-133.
Authors:YUAN Yuan  WANG Yanglin  MA Jing  WEI Hai  PENG Jian
Institution:Laboratory for Earth Surface Processes, Ministry of Education, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
Abstract:With the economic integration of the Beijing-Tianjin-Hebei Region, there exists a poverty belt around Beijing and Tianjin within Hebei Province, which has received attention from academia and the public, so as to put the setting standards of poor counties into the spotlight. Despite some applications of not merely economic indicators but also social and natural indexes to identify poverty in academic researches, the setting of poor counties is only based on economic indicators in China. This paper adds indicators in social dimension representing human poverty and in natural dimension representing natural poverty to build a multidimensional poverty index system, and utilizes SOFM (self-organizing feature mapping) nonlinear clustering tool to classify all of the 136 counties in Hebei Province into 5 categories in view of the county poverty degree by the economic dimension & economic-social-natural dimensions separately. Clustering maps are compared with the map of currently poor counties in Hebei Province afterwards. The results show that the counties with low grades are the ones with high poverty degree. Meanwhile, counties with low grades are the majority, suggesting a high poverty degree all over Hebei Province. About the clustering results, whether in the single economic dimension or economic-social-natural dimensions, they are both consistent with the current distribution pattern of poor counties in Hebei Province which helps the transformation of "relative poverty" to "absolute poverty". Besides, in comparison to the results based on the single (economic) dimension, multidimensional (economic-social-natural) evaluation is more comprehensive because it takes current situation and potential of poverty into overall consideration. Furthermore, potential poverty degree in the natural dimension influences the comprehensive poor degree, indicating that both the current and potential poverty degree of poverty areas around Beijing and Tianjin are high and the region should cooperate with Beijing and Tianjin actively. In contrast, the potential poverty degree of poor counties in the south and middle Hebei Province is relatively low and the region is more easily to be lifted out of poverty. Moreover, these regions covers many counties that are not considered to be poor ones but very likely to become poor ones. Therefore, these regions deserve more attention and being treated differently. To make advances in the poverty relief and development work, the government should not only deal with things distinctively but also combine prevention with treatment and link the areas together. In this way we can expect the achievement of Beijing-Tianjin-Hebei coordinated development and the harmoniously simultaneous growth of wealth of society.
Keywords:economic-social-natural  Hebei Province  multidimensional poverty  potential poverty  SOFM  
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