Given that crime events exhibit both a spatial and a temporal pattern, this study explores whether certain social and physical environment characteristics have varying relationships with crime at different times of day. The study uses a flexible nonlinear parametric approach on a large sample of street segments (and surrounding spatial area) in Southern California. The study finds different temporal and spatial patterns for key measures. The presence of total employees in the surrounding area is associated with a reduced robbery risk during the daytime, but not at night. The risk of a robbery is elevated on a high retail segment on weekends during the daytime, and on high restaurant segments into the early evening on weekends. Furthermore, the presence of retail and restaurants in the surrounding area (evidence of shopping districts) was associated with elevated robbery risk in the afternoon and well into the evening.

You can access the article by Dr. John R. Hipp and Dr. Young-an Kim in Journal of Criminal Justice entitled, “Temporal and Spatial Dimensions of Robbery: Differences across Measures of the Physical and Social Environment”.

Get it here: https://www.sciencedirect.com/science/article/pii/S0047235218303775

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Though Ray Oldenburg’s (1989) notion of “third places”, or places conducive to sociality outside of the realms of home and work, has received both scholarly and popular attention over the past several decades, many of the author’s central claims remain empirically untested. The present study considers the association between neighborhood third places, cohesion and neighbor interaction. Drawing on various literatures regarding interaction in public space and neighborhood use-value, we consider how the role of third places might vary according to neighborhood socioeconomic context. Using data from Wave I of the Los Angeles Family and Neighborhood Study (LAFANS) and data on third places from the point-based business data of ReferenceUSA, we test the effect of third places on cohesion and neighbor interaction across neighborhood poverty strata. We find support for the hypothesis that third places are associated with greater cohesion and neighbor interaction, and that neighbor interaction mediates the relationship between third places and cohesion in poor neighborhoods.

You can access the article by Seth A. Williams and Dr. John R. Hipp in Social Science Research entitled, “How Great and How Good?: Third places, neighbor interaction, and cohesion in the neighborhood context”.

Get it here: https://www.sciencedirect.com/science/article/pii/S0049089X17310116

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Although neighborhood studies often focus on the presence of some particular entity and its consequences for a variety of local processes, a frequent limitation is the failure to account more broadly for the local context. This paper therefore examines the role of parks for community crime, but contributes to the literature by testing whether the context of land use and demographics nearby parks moderate the parks and crime relationship. A key feature of our approach is that we also test how these characteristics explain crime in the park, nearby the park, and in other neighborhoods in the city with data from nine cities across the United States (N= 109,808 blocks). We use multilevel Poisson and negative binomial regressions to test our ideas for six types of street crime. Our findings show that nearby land uses and socio-demographic characteristics are a key driver of crime being located within the park or nearby the park. Our results also show a clear distance decay pattern for the impact of various land uses and socio-demographics nearby parks. The results emphasize a need for research to consider the broader socio-spatial context in which crime generators/inhibitors are embedded.

You can access the article by Dr. Adam Boessen and Dr. John R. Hipp in Social Science Research entitled, “Drugs, Crime, Space, and Time: A Spatiotemporal Examination of Drug Activity and Crime Rates”.

Get it here: https://www.sciencedirect.com/science/article/pii/S0049089X18301303

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To take stock of the neighborhood effects of drug activity, we combined theoretical insights from the drugs and crime and communities and place literatures in examining the longitudinal relationship between drug activity and crime rates at more spatially and temporally precise levels of granularity, with blocks as the spatial units and months as the temporal units. We found that drug activity on a block one month “pushes” assaultive violence into surrounding blocks the next month. Integrating perspectives form social disorganization theory with Zimring and Hawkins’ (1997) contingency causation theory, we also found that the economic resources and residential stability of the “the larger social environment”—that is, the surrounding quarter-mile egohood area—moderate drug activity’s block-level relationship to crime. These results suggest that drug activity increases assaultive violence and serious acquisitive crime rates on structurally advantaged blocks, producing a significant ecological niche redefinition for such blocks relative to others in Miami-Dade County, Florida.

You can access the article by Christopher Contreras and Dr. John R. Hipp online first in Justice Quarterly entitled, “Drugs, Crime, Space, and Time: A Spatiotemporal Examination of Drug Activity and Crime Rates”.

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https://www.tandfonline.com/doi/full/10.1080/07418825.2018.1515318

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This study explored the dynamic nature of neighborhoods using a relatively novel approach and data source. By using a nonparametric holistic approach of neighborhood change based on latent class analysis (LCA), we have explored how changes in the socio-demographic characteristics of residents, as well as home improvement and refinance activity by residents, are related to changes in neighborhood crime over a decade. Utilizing annual home mortgage loan data in the city of Los Angeles from the years 2000–2010, we 1) conducted principle components factor analyses using measures of residential in-migration and home investment activities; 2) estimated LCA models to identify classes of neighborhoods that shared common patterns of change over the decade; 3) described these 11 classes; 4) estimated change-score regression models to assess the relationship of these classes with changing crime rates. The analyses detected six broad types of neighborhood change: 1) stability; 2) urban investors; 3) higher-income home buyers; 4) in-mover oscillating; 5) oscillating refinance; 6) mixed-trait. The study describes the characteristics of each of these classes, and how they are related to changes in crime rates over the decade.

You can access the article by Nicholas Branic and Dr. John R. Hipp online first in Social Science Research entitled, “Growing Pains or Appreciable Gains? Latent Classes of Neighborhood Change, and Consequences for Crime in Southern California Neighborhoods”.

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http://www.sciencedirect.com/science/article/pii/S0049089X16307931

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