Exploring the synergy types and optimization paths between Poverty Alleviation Effectiveness and Rural Revitalization is necessary for achieving the two centenary goals.Taking poverty alleviation counties in Hunan Pro...Exploring the synergy types and optimization paths between Poverty Alleviation Effectiveness and Rural Revitalization is necessary for achieving the two centenary goals.Taking poverty alleviation counties in Hunan Province,China as an example,our study proposed an indicator to measure the synergistic development between Poverty Alleviation Effectiveness and Rural Revitalization using the multi-index integrated evaluation method.Then,the coupling types were classified based on both the proposed indicator and regional characteristics.Besides,the corresponding optimization path for each coupling type was proposed to promote the synergistic development of Poverty Alleviation and Rural Revitalization.Results are as follows:1)Lower synergy focused on the southwestern Hunan,while low synergy is widely distributed(such as the west,southwest,northwest,and midland).Moderate synergy is in the midland,such as Huaihua and Chenzhou cities.High synergy is distributed in Yongzhou,Huaihua,Xiangxi cities,etc.Besides,only Hecheng City belongs to the higher synergy.2)This paper proposes corresponding development paths for different development characteristics and main problems from multiple perspectives of the protection system,industrial planning,and rural market.Continuously consolidate and enhance the effectiveness of Poverty Alleviation and Rural Revitalization to achieve coupled and synergistic development of the two systems.Our research results can provide theoretical support for implementing Poverty Alleviation and Rural Revitalization in Hunan Province,China.展开更多
Objective:To calculate the health poverty vulnerability index of elderly households in rural areas of central and western China,and then to classify these samples,lastly to decompose their influencing factors.Methods:...Objective:To calculate the health poverty vulnerability index of elderly households in rural areas of central and western China,and then to classify these samples,lastly to decompose their influencing factors.Methods:First,based on survey data in 2018,the three-stage feasible generalized least squares was used to calculate the health poverty vulnerability index of elderly households,and then combined with whether the household income was below the poverty line and whether the family was healthy poverty vulnerability,the sample households were divided into four categories,and then used multiple unordered logistic regression to analyze various types of influencing factors,and finally used the Shapley index to decompose the contribution of each influencing factor.Results:The average vulnerability of health poverty was 0.5979±0.25199,with 1169 households greater than or equal to 0.5,accounting for 63.26%;the number of households stuck in poverty,temporary poverty,potential poverty,and escaped from poverty were 489,300,680,and 379 households,accounting for 26.46%,16.23%,36.80%,and 20.51%of the total sample;compared with escaped from poverty families,the three variables of marital status,the number of chronically ill patients,and the number of annual hospitalizations were the common influencing factors of other three types families;The Shapley decomposition showed that the interviewees’education level and family members engaged in non-agricultural work have contributed significantly to the three types,however two indicators:time required to visit a medical institution and self-assessment of health status of the main interviewees showed great differences in different types of families.Conclusion:Rural elderly households have a high level of vulnerability to health poverty;potential poverty households and persistent poverty households account for a large proportion,and continuous intervention should be carried out;it is necessary to unify the implementation of basic poverty alleviation work,but also to enhance ref展开更多
以贫困形势严峻和地理环境空间异质性显著的贵州省为案例,将分类与回归树(Classification and Regression Tree,CART)模型引入贫困研究,分析了贫困空间格局影响因素并制定了相关对策。结论表明:①贵州省的贫困格局呈现出典型的敞口“马...以贫困形势严峻和地理环境空间异质性显著的贵州省为案例,将分类与回归树(Classification and Regression Tree,CART)模型引入贫困研究,分析了贫困空间格局影响因素并制定了相关对策。结论表明:①贵州省的贫困格局呈现出典型的敞口“马蹄”形结构,黔东、南和西部地区高而中部及北部较低。②基于CART模型的贵州省贫困影响因素重要性的排序为平均隔离度>路网密度>水域比例>平均偏远度>NDVI>年均降水。③根据CART模型决策规则,对贵州省扶贫攻坚提出以下对策建议:首先,应采取更加“精准”的易地扶贫和村镇体系规划降低居民点隔离度,确保居民点之间平均隔离度小于4847 m。其次,在居民点距离确定的基础上,应科学改善区域的生产生活用水条件,将水域面积比例尽可能提升至0.8%以上,保障生活用水和生产灌溉,提升水资源承载能力。最后,在确保居民点隔离度改善,水资源丰度提升的前提下,应重视喀斯特石漠化地区的生态保护修复,将县域的NDVI提升至0.45以上,提高区域生态资产,提升贫困社区韧性,将生态保护与脱贫攻坚相结合,促进区域人地关系和谐发展。展开更多
基金Under the auspices of the National Natural Science Foundation of China(No.41971219,41571168)Natural Science Foundation of Hunan Province(No.2020JJ4372)Philosophy and Social Science Fund Project of Hunan Province(No.18ZDB015)。
文摘Exploring the synergy types and optimization paths between Poverty Alleviation Effectiveness and Rural Revitalization is necessary for achieving the two centenary goals.Taking poverty alleviation counties in Hunan Province,China as an example,our study proposed an indicator to measure the synergistic development between Poverty Alleviation Effectiveness and Rural Revitalization using the multi-index integrated evaluation method.Then,the coupling types were classified based on both the proposed indicator and regional characteristics.Besides,the corresponding optimization path for each coupling type was proposed to promote the synergistic development of Poverty Alleviation and Rural Revitalization.Results are as follows:1)Lower synergy focused on the southwestern Hunan,while low synergy is widely distributed(such as the west,southwest,northwest,and midland).Moderate synergy is in the midland,such as Huaihua and Chenzhou cities.High synergy is distributed in Yongzhou,Huaihua,Xiangxi cities,etc.Besides,only Hecheng City belongs to the higher synergy.2)This paper proposes corresponding development paths for different development characteristics and main problems from multiple perspectives of the protection system,industrial planning,and rural market.Continuously consolidate and enhance the effectiveness of Poverty Alleviation and Rural Revitalization to achieve coupled and synergistic development of the two systems.Our research results can provide theoretical support for implementing Poverty Alleviation and Rural Revitalization in Hunan Province,China.
基金supported by the National Natural Science Foundation of China(No.72074086&No.71673093)Humanities and Social Sciences of Ministry of Education Planning Fund of China(No.16YJA840013).
文摘Objective:To calculate the health poverty vulnerability index of elderly households in rural areas of central and western China,and then to classify these samples,lastly to decompose their influencing factors.Methods:First,based on survey data in 2018,the three-stage feasible generalized least squares was used to calculate the health poverty vulnerability index of elderly households,and then combined with whether the household income was below the poverty line and whether the family was healthy poverty vulnerability,the sample households were divided into four categories,and then used multiple unordered logistic regression to analyze various types of influencing factors,and finally used the Shapley index to decompose the contribution of each influencing factor.Results:The average vulnerability of health poverty was 0.5979±0.25199,with 1169 households greater than or equal to 0.5,accounting for 63.26%;the number of households stuck in poverty,temporary poverty,potential poverty,and escaped from poverty were 489,300,680,and 379 households,accounting for 26.46%,16.23%,36.80%,and 20.51%of the total sample;compared with escaped from poverty families,the three variables of marital status,the number of chronically ill patients,and the number of annual hospitalizations were the common influencing factors of other three types families;The Shapley decomposition showed that the interviewees’education level and family members engaged in non-agricultural work have contributed significantly to the three types,however two indicators:time required to visit a medical institution and self-assessment of health status of the main interviewees showed great differences in different types of families.Conclusion:Rural elderly households have a high level of vulnerability to health poverty;potential poverty households and persistent poverty households account for a large proportion,and continuous intervention should be carried out;it is necessary to unify the implementation of basic poverty alleviation work,but also to enhance ref
文摘以贫困形势严峻和地理环境空间异质性显著的贵州省为案例,将分类与回归树(Classification and Regression Tree,CART)模型引入贫困研究,分析了贫困空间格局影响因素并制定了相关对策。结论表明:①贵州省的贫困格局呈现出典型的敞口“马蹄”形结构,黔东、南和西部地区高而中部及北部较低。②基于CART模型的贵州省贫困影响因素重要性的排序为平均隔离度>路网密度>水域比例>平均偏远度>NDVI>年均降水。③根据CART模型决策规则,对贵州省扶贫攻坚提出以下对策建议:首先,应采取更加“精准”的易地扶贫和村镇体系规划降低居民点隔离度,确保居民点之间平均隔离度小于4847 m。其次,在居民点距离确定的基础上,应科学改善区域的生产生活用水条件,将水域面积比例尽可能提升至0.8%以上,保障生活用水和生产灌溉,提升水资源承载能力。最后,在确保居民点隔离度改善,水资源丰度提升的前提下,应重视喀斯特石漠化地区的生态保护修复,将县域的NDVI提升至0.45以上,提高区域生态资产,提升贫困社区韧性,将生态保护与脱贫攻坚相结合,促进区域人地关系和谐发展。
