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arXiv:2505.20822v1 (physics)
[Submitted on 27 May 2025 (this version) , latest version 27 Oct 2025 (v2) ]

Title: Larger cities, more commuters, more crime? The role of inter-city commuting in the scaling of urban crime

Title: 更大的城市,更多的通勤者,更多的犯罪? 城际通勤在城市犯罪规模定律中的作用

Authors:Simon Puttock, Umberto Barros, Diego Pinheiro, Marcos Oliveira
Abstract: Cities attract a daily influx of non-resident commuters, reflecting their role in wider urban networks -- not as isolated places. However, it remains unclear how this inter-connectivity shapes the way crime scales with population, given that larger cities tend to receive more commuters and experience more crime. Here, we investigate how inter-city commuting relates to the population--crime relationship. We find that larger cities receive proportionately more commuters, which in turn is associated with higher crime levels. Specifically, each 1% increase in inbound commuters corresponds to a 0.32% rise in theft and 0.20% rise in burglary, holding population constant. We show that models incorporating both population and commuter inflows better explain crime variation than population-only models. These findings underscore the importance of considering how cities are connected -- not just their population size -- in disentangling the population--crime relationship.
Abstract: 城市吸引着大量的非居民通勤者每天涌入,这反映了它们在更广泛的都市网络中的作用——而不是孤立存在的地方。 然而,尚不清楚这种互联互通如何影响犯罪与人口规模之间的关系,因为较大的城市往往接收更多的通勤者并经历更多的犯罪活动。 在这里,我们研究了城际通勤如何与人口-犯罪关系相关联。 我们发现较大的城市接收的通勤者比例更高,而这反过来又与更高的犯罪水平相关。 具体而言,在控制人口数量的情况下,每增加1%的入境通勤者,盗窃案会上升0.32%,入室盗窃案会上升0.20%。 我们表明,同时考虑人口和通勤流入量的模型比仅基于人口的模型能更好地解释犯罪率的变化。 这些发现强调了在分析人口与犯罪关系时,考虑城市之间是如何相互连接的重要性,而不仅仅是关注人口规模。
Comments: 16 pages, 2 figures
Subjects: Physics and Society (physics.soc-ph) ; Social and Information Networks (cs.SI); Data Analysis, Statistics and Probability (physics.data-an); Applications (stat.AP); Other Statistics (stat.OT)
Cite as: arXiv:2505.20822 [physics.soc-ph]
  (or arXiv:2505.20822v1 [physics.soc-ph] for this version)
  https://doi.org/10.48550/arXiv.2505.20822
arXiv-issued DOI via DataCite

Submission history

From: Marcos Oliveira [view email]
[v1] Tue, 27 May 2025 07:31:43 UTC (1,963 KB)
[v2] Mon, 27 Oct 2025 11:09:03 UTC (1,850 KB)
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