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The Network of Neighborhoods and Geographic Space: Implications for Joblessness While on Parole
Journal of Quantitative Criminology ( IF 4.330 ) Pub Date : 2021-04-14 , DOI: 10.1007/s10940-021-09510-z
Adam Boessen , John R. Hipp

Objectives

Few studies have examined the consequences of neighborhoods for job prospects for people on parole. Specifically, networks between neighborhoods in where people commute to work and their spatial distributions may provide insight into patterns of joblessness because they represent the economic structure between neighborhoods. We argue that the network of neighborhoods provides insight into the competition people on parole face in the labor market, their spatial mismatch from jobs, as well as their structural support.

Methods

We use data from people on parole released in Texas from 2006 to 2010 and create a network between all census tracts in Texas based on commuting ties from home to work. We estimate a series of multilevel models examining how network structures are related to joblessness.

Results

The findings indicate that the structural position of neighborhoods has consequences for people on parole’s joblessness. Higher outdegree, reflecting neighborhoods with more outgoing ties to other neighborhoods, was consistently associated with less joblessness, while higher indegree, reflecting neighborhoods with more incoming ties into the neighborhood, was associated with more joblessness, particularly for Black and Latino people on parole. There was also some evidence of differences depending on geographic scale.

Conclusions

Structural neighborhood-to-neighborhood networks are another component to understanding joblessness while people are on parole. The most consistent support was shown for the competition and structural support mechanisms, rather than spatial mismatch.



中文翻译:

邻里和地理空间网络:假释期间对失业的影响

目标

很少有研究检查邻里对假释人员的就业前景的影响。具体而言,人们上下班的社区之间的网络及其空间分布可以洞悉失业模式,因为它们代表了社区之间的经济结构。我们认为,社区网络可以洞察人们在劳动力市场上面临假释的竞争,他们与工作的空间不匹配以及他们的结构性支持。

方法

我们使用2006年至2010年在得克萨斯州发布的假释人员数据,并根据从上班到上班之间的通勤联系,在得克萨斯州所有人口普查区之间建立了网络。我们估计了一系列多级模型,这些模型检查了网络结构与失业之间的关系。

结果

研究结果表明,邻里的结构性地位对假释者的失业产生影响。较高的学位程度,反映出与其他邻居有更多外向联系的邻里,始终与较少的失业相关;而较高的学位程度,反映了与邻里有更多联系的邻里,则与更多的失业有关,特别是对于黑人和拉丁裔在假释中。也有一些证据表明差异取决于地理范围。

结论

结构化的邻里到邻网络是人们在假释期间了解失业的另一个组成部分。对于竞争和结构支持机制,显示出最一致的支持,而不是空间不匹配。

更新日期:2021-04-15
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