It is well established that living in a high‐poverty area often leads to lower levels of well‐being for residents. While these deleterious effects of place‐based poverty are well‐documented, the conceptual mechanisms linking poverty of place to negative outcomes remain debated, and the our understanding of the spatial patterning of poverty remains underdeveloped. In this paper, we problematize simple conceptualizations of the negative impacts of poverty exposure by illustrating the dynamic patterns poverty displays across cities on a daily basis. The vast majority of prior research on poverty of place has relied upon data anchored to place of residence. Thus, poverty rates broadly reflect poverty as it exists at night. This bias toward nighttime statistics leaves us with an incomplete understanding of spatial inequalities because daytime poverty rates can differ markedly from nighttime poverty rates due to work‐related commuting patterns. Here, we use novel data from the Census Transportation Planning Products to fully illustrate diurnal patterns in poverty at the census tract level in metropolitan America. Through a combination of descriptive, spatial, and statistical analyses, we show that the majority of census tracts experience changes in poverty throughout the day. Through a series of regression models, we also show that diurnal patterns in poverty are unevenly distributed along the lines of suburbanization, race, economic status, age composition, and industrial structure. Overall, our findings provide analytic insights into properly documenting poverty across space, while further problematizing lingering culture of poverty frameworks.

中文翻译：

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地方贫困的进一步复杂化：跨空间的日常贫困动态

众所周知，生活在高度贫困地区往往会导致居民的福祉水平较低。尽管基于地点的贫困的这些有害影响已有充分记录，但将地点贫困与负面结果联系起来的概念机制仍然存在争议，而且我们对贫困空间格局的理解仍然不充分。在本文中，我们通过说明贫困在城市中每天表现出的动态模式，对贫困暴露的负面影响的简单概念提出了问题。先前关于地方贫困的绝大多数研究都依赖于居住地的数据。因此，贫困率广泛反映了夜间存在的贫困情况。这种对夜间统计数据的偏见使我们对空间不平等的理解不完整，因为由于与工作相关的通勤模式，白天贫困率可能与夜间贫困率存在显着差异。在这里，我们使用来自人口普查交通规划产品的新数据来充分说明美国大都市人口普查区层面贫困的昼夜模式。通过描述性、空间和统计分析的结合，我们表明大多数人口普查区的贫困状况在一天中都会发生变化。通过一系列回归模型，我们还表明贫困的日间模式在郊区化、种族、经济地位、年龄构成和产业结构方面分布不均匀。总的来说，我们的研究结果为正确记录跨空间的贫困提供了分析见解，同时进一步解决了挥之不去的贫困文化框架的问题。