{"title":"Community Prosperity/Poverty (Prospov) Maps: Development and Usefulness","authors":"Danie Francois Toerien","doi":"10.1080/10875549.2023.2259884","DOIUrl":null,"url":null,"abstract":"ABSTRACTThe number of poor people and the total number of people in United States counties are strongly and non-linearly correlated, illustrated by power laws. The total number of people and the number of enterprises in U.S. counties and micropolitan statistical areas are also non-linearly correlated. Graphs of power law data points of the latter relationship visually map the relative prosperity/poverty levels of more than 3000 counties or more than 500 micropolitans despite orders of magnitude differences in population or enterprise numbers. The utility of Prospov maps is illustrated by superimposition of different socioeconomic and entrepreneurial characteristics on them.KEYWORDS: MappingpovertyprosperityU.S. countiesU.S. micropolitan statistical areas AcknowledgmentsThe Centre for Environmental Management, University of the Free State, provided administrative and research support. Alumnus services of the Massachusetts Institute of Technology provided online scholarly journal access. Jean le Roux provided technical assistance. The author reports there are no competing interests to declare.Disclosure statementNo potential conflict of interest was reported by the author(s).","PeriodicalId":46177,"journal":{"name":"Journal of Poverty","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Poverty","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/10875549.2023.2259884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOCIAL WORK","Score":null,"Total":0}
引用次数: 0
Abstract
ABSTRACTThe number of poor people and the total number of people in United States counties are strongly and non-linearly correlated, illustrated by power laws. The total number of people and the number of enterprises in U.S. counties and micropolitan statistical areas are also non-linearly correlated. Graphs of power law data points of the latter relationship visually map the relative prosperity/poverty levels of more than 3000 counties or more than 500 micropolitans despite orders of magnitude differences in population or enterprise numbers. The utility of Prospov maps is illustrated by superimposition of different socioeconomic and entrepreneurial characteristics on them.KEYWORDS: MappingpovertyprosperityU.S. countiesU.S. micropolitan statistical areas AcknowledgmentsThe Centre for Environmental Management, University of the Free State, provided administrative and research support. Alumnus services of the Massachusetts Institute of Technology provided online scholarly journal access. Jean le Roux provided technical assistance. The author reports there are no competing interests to declare.Disclosure statementNo potential conflict of interest was reported by the author(s).
【摘要】美国县域贫困人口数量与总人口呈幂律关系,呈强烈的非线性相关关系。美国县和小城市统计区的人口总数和企业数量也是非线性相关的。后一种关系的幂律数据点图表直观地描绘了3000多个县或500多个微型城市的相对繁荣/贫困水平,尽管人口或企业数量存在数量级差异。Prospov地图的效用是通过叠加不同的社会经济和企业特征来说明的。关键词:MappingpovertyprosperityU.S。countiesU.S。自由邦大学环境管理中心提供了行政和研究支助。麻省理工学院的校友服务提供在线学术期刊访问。Jean le Roux提供了技术援助。作者报告说,没有相互竞争的利益需要申报。披露声明作者未报告潜在的利益冲突。
期刊介绍:
The Journal of Poverty is the first refereed journal to recognize the inequalities in our social, political, and economic structures, presenting progressing strategies that expand society"s increasingly narrow notions of poverty and inequality. The journal"s broad understanding of poverty—more inclusive than the traditional view—keeps the focus on people"s need for education, employment, safe and affordable housing, nutrition, and adequate medical care, and on interventions that range from direct practice to community organization to social policy analysis. The journal"s articles will increase your knowledge and awareness of oppressive forces such as racism, sexism, classism, and homophobia that contribute to the maintenance of poverty and inequality.