SEARCH THE DATABASE

While aerial photography is associated with vertical objectivity and spatial abstractions, street-level imagery appears less political in its orientation to the particularities of place. I contest this assumption, showing how the aggregation of street-level imagery into “big datasets” allows for the algorithmic sorting of places by their street-level visual qualities. This occurs through an abstraction by “datafication,” inscribing new power geometries onto urban places through algorithmic linkages between visual environmental qualities, geographic information, and valuations of social worth and risk. Though largely missing from media studies of Google Street View, similar issues have been raised in critiques of criminological theories that use place as a proxy for risk. Comparing the Broken Windows theory of criminogenesis with big data applications of street-level imagery informs a critical media studies approach to Google Street View. The final section of this article suggests alternative theoretical orientations for algorithm design that avoid the pitfalls of essentialist equations of place with social character.

This article assesses the sources and consequences of public disorder. Based on the videotaping and systematic rating of more than 23,000 street segments in Chicago, highly reliable scales of social and physical disorder for 196 neighborhoods are constructed. Census data, police records, and an independent survey of more than 3,500 residents are then integrated to test a theory of collective efficacy and structural constraints. Defined as cohesion among residents combined with shared expectations for the social control of public space, collective efficacy explains lower rates of crime and observed disorder after controlling neighborhood structural characteristics. Collective efficacy is also linked to lower rates of violent crime after accounting for disorder and the reciprocal effects of violence. Contrary to the “broken windows” theory, however, the relationship between public disorder and crime is spurious except perhaps for robbery.

The collection of large-scale administrative records in electronic form by many cities provides a new opportunity for the measurement and longitudinal tracking of neighborhood characteristics, but one that will require novel methodologies that convert such data into research-relevant measures. The authors illustrate these challenges by developing measures of “broken windows” from Boston’s constituent relationship management (CRM) system (aka 311 hotline). A 16-month archive of the CRM database contains more than 300,000 address-based requests for city services, many of which reference physical incivilities (e.g., graffiti removal). The authors carry out three ecometric analyses, each building on the previous one. Analysis 1 examines the content of the measure, identifying 28 items that constitute two independent constructs, private neglect and public denigration. Analysis 2 assesses the validity of the measure by using investigator-initiated neighborhood audits to examine the “civic response rate” across neighborhoods. Indicators of civic response were then extracted from the CRM database so that measurement adjustments could be automated. These adjustments were calibrated against measures of litter from the objective audits. Analysis 3 examines the reliability of the composite measure of physical disorder at different spatiotemporal windows, finding that census tracts can be measured at two-month intervals and census block groups at six-month intervals. The final measures are highly detailed, can be tracked longitudinally, and are virtually costless. This framework thus provides an example of how new forms of large-scale administrative data can yield ecometric measurement for urban science while illustrating the methodological challenges that must be addressed.

This study examined what factors best predict residents’ concerns about neighborhood safety. One-hundred and twenty-two participants were selected from a large, Midwestern metropolitan area. All participants lived in high crime areas. Participants completed a 22-item questionnaire that assessed their perceptions of neighborhood safety and vigilance. These items were clustered as: 1) Community care and vigilance, 2) neighborhood safety concerns, 3) physical incivilities, and 4) social incivilities. Police crime data were also used in the analyses. Our findings suggest that aspects of the broken window theory, collective efficacy, and place attachments/territoriality play a role in affecting residents’ concerns about neighborhood safety.