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Beyond Residential Segregation: Mobility-Based Connectedness and Rates of Violence in Large Cities

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Abstract

A longstanding finding is that neighborhood racial segregation is linked to violence. In this paper, we look beyond neighborhoods of residence to consider the everyday mobility of urbanites in their daily rounds. Analyzing estimates of neighborhood mobility from largescale social media data in the 50 largest American cities, we find that residential segregation by race is not only associated with higher violence but also lower equitability of travel across neighborhoods and a lower concentration of visits to common hubs. Further, the interaction of equitable and concentrated mobility is significantly associated with rates of violence, controlling for both racial and income segregation, education, city size, and density. There is little evidence, however, that patterns of everyday mobility mediate the influence of residential racial segregation. Both dimensions of the structural connectedness of cities—one rooted in place of residence, and the other encompassing interneighborhood exposure based on travel throughout the metropolis—are implicated in violence.

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Notes

  1. Violent crimes include homicide, rape or sexual assault, robbery, aggravated assault, and simple assault.

  2. Income category cut points are (in thousands of dollars): 10, 15, 20, 25, 30, 35, 40, 45, 50, 60, 75, 100, 125, 150, and 200 plus.

  3. Phillips et al. (2019) assume that each resident of a city is equally important for a neighborhood’s contact with other neighborhoods, and thus each observed resident’s visits are normalized to have an outdegree of one, rendering each resident’s visits to a neighborhood a proportion of their total visits. They also assume that each neighborhood has equal importance in the structural connectedness of a city, thereby normalizing each neighborhood to have an outdegree of 1 by dividing its residents’ aggregated proportions of visits to other neighborhoods by the sending neighborhood’s total number of residents. Finally, they assume that travelers to a city (or tourists) play a different and less important role than residents in the structural connectedness of a city, and so they remove travelers from the calculation of connectedness. This decision aligns with our corresponding focus on the racial segregation of city residents.

  4. Although the share of residents holding a bachelor’s degree is highly correlated with median household income (.79), the educational measure is correlated with equitable mobility at a higher level than median income (.31 vs. .19). We thus use percent of adults with a bachelor’s degree as the main control. The results for our mobility-based predictions of violence are nonetheless very similar when we control for median income instead.

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Funding

Funding was provided in part by the National Science Foundation Grants SES- #1637136 and SES #1735505.

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Authors and Affiliations

  1. Department of Sociology, Harvard University, Cambridge, USA

    Robert J. Sampson

  2. Department of Sociology and Anthropology, George Mason University, Fairfax, USA

    Brian L. Levy

Authors
  1. Robert J. Sampson
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  2. Brian L. Levy
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Correspondence to Robert J. Sampson.

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Appendices

Appendix A: OLS Regression Models of 2016 Log Violent Crime Rate per 100,000 Population (n = 49)

 

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Model 7

Racial segregation

3.128*** [0.665]

2.867*** [0.634]

 

3.230*** [0.659]

2.607*** [0.695]

  

Income segregation

 

3.445 [2.942]

 

2.79 [3.407]

5.392 [3.282]

  

% BA

  

− 1.603* [0.639]

− 0.302 [0.551]

− 0.244 [1.269]

 

0.208 [1.264]

ln(population)

  

− 0.185+ [0.104]

− 0.210* [0.0945]

− 0.350** [0.123]

 

− 0.401** [0.122]

ln(pop. density)

  

0.175* [0.066]

− 0.001 [0.069]

− 0.000 [0.056]

 

0.083 [0.058]

Equitable mobility

    

− 3.953 [2.797]

− 2.497 [1.787]

− 7.395* [2.802]

Concentrated mobility

    

1.059 [3.416]

− 4.141** [1.538]

− 3.363 [3.156]

Eq. mobility * conc. mobility

    

120.9** [35.31]

132.8** [41.35]

101.1* [39.18]

Constant

5.763*** [0.215]

5.283*** [0.518]

8.366*** [1.363]

8.263*** [1.411]

9.906*** [1.460]

6.669*** [0.0653]

11.41*** [1.618]

R 2

0.336

0.359

0.153

0.431

0.558

0.235

0.333

AIC

53.79

54.07

69.77

54.27

47.85

64.75

64.02

  1. Standard errors in brackets. Sample size reduced to 49 because violent crime data for Raleigh are unavailable
  2. +p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001

Appendix B: OLS Regression Models of 2016 Log Homicide Rate Per 100,000 Population (n = 50)

 

Model 1

Model 2

Model 3

Model 4

Model 5

Model 6

Model 7

Black–white exposure index

− 2.595*** [0.415]

− 2.460*** [0.461]

 

− 3.459*** [0.481]

− 3.221*** [0.385]

  

Income segregation

 

3.89 [3.160]

 

− 1.364 [3.087]

1.203 [2.169]

  

% BA

  

− 3.361** [1.153]

− 1.137 [0.701]

− 0.311 [1.676]

 

1.731 [2.029]

ln(population)

  

− 0.296+ [0.172]

− 0.261*

− 0.500*** [0.105]

 

− 0.606** [0.176]

ln(pop. density)

  

0.251* [0.103]

− 0.254* [0.103]

− 0.285*** [0.0701]

 

0.041 [0.078]

Equitable mobility

    

− 6.554* [2.788]

− 4.373+ [2.299]

− 13.17*** [3.518]

Concentrated mobility

    

0.13 [4.015]

− 10.47*** [2.021]

− 11.99** [4.240]

Eq. mobility * conc. mobility

    

140.8*** [32.73]

168.6*** [44.72]

119.0** [41.27]

Constant

3.440*** [0.210]

2.757*** [0.652]

5.528* [2.341]

9.975*** [1.747]

12.69*** [1.465]

2.321*** [0.091]

9.667*** [2.320]

R 2

0.514

0.526

0.207

0.704

0.799

0.345

0.438

AIC

82.58

83.29

111.00

65.75

52.41

101.40

99.77

  1. Standard errors in brackets. Models 3, 6, and 7 replicate those in Table 3; we present the full set of results for ease in comparison of coefficients across Appendix B
  2. +p < 0.10, *p < 0.05, **p < 0.01, ***p < 0.001

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Sampson, R.J., Levy, B.L. Beyond Residential Segregation: Mobility-Based Connectedness and Rates of Violence in Large Cities. Race Soc Probl 12, 77–86 (2020). https://doi.org/10.1007/s12552-019-09273-0

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