自然资源学报 ›› 2022, Vol. 37 ›› Issue (2): 396-407.doi: 10.31497/zrzyxb.20220209

• 新时期自然资源利用与管理 • 上一篇    下一篇

基于农户视角的脱贫类型划分与路径研究——以新晃侗族自治县84个出列村为例

谭雪兰(), 王振凯, 余航菱, 安悦, 蒋凌霄, 罗家欣, 任辉   

  1. 湖南农业大学资源环境学院,长沙 410128
  • 收稿日期:2021-01-18 修回日期:2021-04-16 出版日期:2022-02-28 发布日期:2022-02-16
  • 作者简介:谭雪兰(1978- ),女,湖南茶陵人,博士,教授,博士生导师,研究方向为城乡规划、乡村地理及乡村土地利用。E-mail: txl780120@163.com
  • 基金资助:
    国家自然科学基金项目(41971219);国家自然科学基金项目(41601097);湖南省自然科学基金项目(2020JJ4372);湖南省哲学社会科学基金项目(18ZDB015)

Research on classification and optimization paths of poverty elimination from the perspective of farmers: A case study of 84 villages in Xinhuang Dong autonomous county

TAN Xue-lan(), WANG Zhen-kai, YU Hang-ling, AN Yue, JIANG Ling-xiao, LUO Jia-xin, REN Hui   

  1. College of Resources Environment, Hunan Agricultural University, Changsha 410128, China
  • Received:2021-01-18 Revised:2021-04-16 Online:2022-02-28 Published:2022-02-16

摘要:

以新晃侗族自治县(以下称“新晃县”)84个出列村农户为研究对象,从基础设施、教育医疗、收入状况、产业发展四个方面构建脱贫成效指标体系,对2019年新晃县出列村农户脱贫成效的空间格局、脱贫类型划分与路径进行研究。结果表明:(1)新晃县出列村农户脱贫成效呈现出明显的空间分异特征,基础设施脱贫成效平均得分为2.53,整体呈“北高南低”的态势;教育医疗脱贫成效平均得分为2.65,呈现出“东南高、西北低”的空间分布格局;收入脱贫成效平均得分为2.48,呈高、中、低得分区域交替分布态势;产业脱贫成效平均得分为4.23,但差异明显,仅东部、南部少数村域得分较高。(2)新晃县出列村农户脱贫类型可分为单因素主导脱贫型、双因素驱动脱贫型、多因素综合脱贫型三个大类和F因素主导型、F-E因素驱动型、P-E-I因素综合型等13个小类,同时针对不同脱贫类型提出巩固脱贫成效的策略与路径。

关键词: 脱贫成效, 空间分异, 类型划分, 农户, 新晃侗族自治县

Abstract:

Taking farmers in 84 villages in Xinhuang Dong autonomous county as examples, which were removed from the poverty list, we construct an evaluation system of rural households' poverty alleviation in Xinhuang county from four aspects, including infrastructure, education and medical care, farmers' income and industrial development, and studies the spatial pattern, types and optimization path of poverty elimination effects in the study area in 2019. Results show that: (1) There are obvious spatial differences of the farmer's poverty elimination effects: the average score of the effectiveness of infrastructure poverty alleviation was 2.53, characterized by "higher in the north, but lower in the south"; the average score of poverty alleviation in education and medical care was 2.65, showing a spatial pattern of "higher in the southeast, while lower in the northwest"; the average score of income poverty alleviation effect was 2.48, showing an alternating distribution of high, medium and low scores; the average score of industrial poverty alleviation effect was 4.23, with only a few villages with higher scores in the eastern and southern parts. (2) Three types of poverty alleviation were identified, namely, single factor leading poverty elimination, double-factor driven poverty elimination, multi-factor comprehensive poverty elimination, and they were divided into 13 subtypes including F factor leading poverty elimination, F-E factor driven poverty elimination, P-E-I comprehensive poverty elimination. In addition, effective strategies and paths for different types of poverty elimination were proposed to consolidate poverty eradication achievements.

Key words: poverty alleviation, spatial differentiation, classification, farmers, Xinhuang Dong autonomous county