贫困退出背景下返贫脆弱性评价——融合区域与个体的新视角  

Vulnerability assessment of return-to-poverty under poverty elimination in China:A new integrated regional and individual perspective

作　　者：严小燕[1,2] 祁新华[1,2] 潘颖 李亚桐 YAN Xiao-yan;QI Xin-hua;PAN Ying;LI Ya-tong(School of Geographical Sciences,Fujian Normal University,Fuzhou 350007,China;Institute of Geography,Fujian Normal University,Fuzhou 350007,China)

机构地区：[1]福建师范大学地理科学学院,福州350007 [2]福建师范大学地理研究所,福州350007

出　　处：《自然资源学报》2022年第2期440-458,共19页Journal of Natural Resources

基　　金：国家社会科学基金项目(18BJL126)。

摘　　要：精准识别返贫脆弱性,预防和化解返贫风险是"后扶贫时代"的工作重点。基于区域与个体尺度融合的新视角,运用BP神经网络法、熵值法和偏相关分析法对六盘山、秦巴山和大别山三大集中连片特困区进行返贫脆弱性评价与影响因素分析。研究发现:(1)三大集中连片特困区返贫脆弱度大致呈现由西向东递减的空间格局;(2)三个典型县区域和个体返贫脆弱性评价结果均显示古浪县>新县>栾川县;(3)高返贫风险县域中,高生态暴露度特征最为显著,而高返贫风险家庭中,生计动力不足特征最为明显;(4)区域返贫脆弱性主导因子为自然环境禀赋和经济发展水平,个体返贫脆弱性主导因子则为家庭劳动力综合素质、家庭收入、生计来源多样性、家庭成员健康状况和婚姻成本等。Identifying the vulnerability to return-to-poverty(or re-poverty), and comprehensively preventing and resolving the risk of re-poverty are the key points of poverty alleviation in the "post-poverty alleviation era". From the perspective of the integration of regional and individual scales, a comprehensive analysis framework is constructed. BP neural network method, entropy method and partial correlation analysis method are adapted to evaluate the vulnerability of re-poverty in three contiguous destitute areas of Liupan Mountains, Qinba Mountains and Dabie Mountains, as well as the influencing factors. Firstly, we find the vulnerability to re-poverty in the three contiguous destitute areas shows a spatial pattern of decreasing from west to east. Secondly, according to the classification order of the EEI, WSI,EAI and RVRI indexes, three typical counties of Gulang, Luanchuan and Xinxian show the characteristics of "high-high-low-high", "high-low-high-low" and "medium low-medium low-high-low", respectively. According to the classification order of LBI, LMI, LOI and IVRI indexes, however, the characteristics of these counties are "medium low-medium low-medium high-high", "medium high-high-medium low-low" and "medium high-medium low-medium low-medium low", respectively. Therefore, the evaluation results of both regional and individual vulnerability to re-poverty show an order of Gulang > Xinxian > Luanchuan. To be specific, Gulang is characterized by high vulnerability of re-poverty from both regional and individual perspectives. Xinxian has the advantage of the lowest ecological exposure, while the main problem is the low livelihood motivation. Although Luanchuan is relatively stable in poverty alleviation, the high ecological exposure is a major potential danger. Thirdly, for counties with high risk of re-poverty, high ecological exposure is the most significant characteristic, while for households with high risk, the most significant characteristic is insufficient livelihood motivation. The last finding shows that t

关 键 词：返贫脆弱性 区域与个体 BP神经网络 集中连片特困区 

分 类 号：F323.8[经济管理—产业经济]