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城市定义的邻里边界在美国
Stephen Ansolabehere1, Jacob R Brown2, Ryan D Enos1
1Harvard University, Department of Government, Cambridge, MA, 02138, USA.
Scientific data
|June 19, 2025
概括
研究人员现在可以访问城市定义社区的新数据集,在规模上提供精确的本地数据. 本资源有助于理解社区对社会,经济和健康结果的影响.
科学领域:
- 城市研究 城市研究
- 社会学 社会学 社会学
- 公共卫生 公共卫生
背景情况:
- 社区显著影响社会,经济,政治和健康结果.
- 定义和测量社区是复杂的,因为不同的当地定义.
- 现有的研究往往依赖于任意的人口普查地理或难以缩放的精确数据.
研究的目的:
- 为了应对邻里数据中规模与精度的挑战.
- 为研究人员提供城市定义社区的新型数据集.
- 为了促进更准确的社区层面的研究.
主要方法:
- 收集并清理了美国206个大城市的社区边界数据.
- 集成城市定义的社区数据与区块级人口普查人口统计数据.
- 开发开源软件,以帮助研究人员利用数据集.
主要成果:
- 一个涵盖超过7700万人口的城市定义社区的综合数据集.
- 数据链接可以在精确的社区边界内分析人口特征.
- 开源工具的可用性可以提高数据的可访问性和可用性.
结论:
- 新的数据集弥合了可扩展和精确的邻里数据之间的差距.
- 授权研究人员对邻居影响进行更局部和更准确的研究.
- 促进城市研究,社会学和公共卫生研究的进步.
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