SEARCH THE DATABASE

This paper examines collaboration between artists and social scientists in urban studies. The author was a participant in experimental research commissioned by a new cultural institution, which examined how this institution might participate in the making of a public space. In this paper she analyses the methodologies of investigation and the discussions about forms and representations, and shows the difficulties and rewards of this type of collaboration. To what extent may research based on art and social sciences, and rooted in references to the methodologies and theories of both, be a relevant and alternative way to explore, investigate and represent an urban issue?

The National Study of Protest Events (NSPE) employed hypernetwork sampling to generate the first-ever nationally representative sample of protest events. Nearly complete information about various event characteristics was collected from participants in 1,037 unique protests across the United States in 2010 to 2011. The first part of this article reviews extant methodologies in protest-event research and discusses how the NSPE overcomes their recognized limitations. Next, we detail how the NSPE was conducted and present descriptive statistics for a number of important event characteristics. The hypernetwork sample is then compared to newspaper reports of protests. As expected, we find many differences in the types of events these sources capture. At the same time, the overall number and magnitude of the differences are likely to be surprising. By contrast, little variation is observed in how protesters and journalists described features of the same events. NSPE data have many potential applications in the field of contentious politics and social movements, and several possibilities for future research are outlined.

This paper draws upon a model of the publicness of publicly owned and managed spaces by means of fuzzy logic modelling. The value of this approach is that it is practical in simplifying and emphasizing both the interdependent nature of the concept of publicness and its complexity. The proposed model aims to effectively evaluate and compare the publicness of public space. The paper highlights different methodologies in understanding this publicness by considering various conceptual approaches at the heart of the debate about public space. In doing so, the paper is organized into four main parts. The first part considers the complex and fuzzy nature of the concept. The second presents the proposed model of publicness based on management, access and user dimensions by analyzing the leading discourse and previous models of publicness. The third part draws upon research methodology and fuzzy logic modelling, and the fourth part explains the findings of the case study in Istanbul.

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.

Definitions of neighbourhood in the Social Sciences are complex, varying in their characteristics (for example, perceived boundaries and content) and between residents of that neighbourhood (for example, by class and ethnicity). This study employs an under-utilised methodology offering strong potential for overcoming some of the difficulties associated with neighbourhood definitions. A mental mapping exercise involving local residents is showcased for an ethnically diverse working-class neighbourhood in south Liverpool. The results demonstrate distinctions between residents in the geographical demarcation of the area and the features included, with important implications for how neighbourhood is best measured and understood. We suggest that one size does not fit all in definitions of neighbourhood, and that mental mapping should form a more common part of a neighbourhood researcher’s toolkit.

Ordinary kriging, a spatial interpolation technique, is commonly used in social sciences to estimate neighborhood attributes such as physical disorder. Universal kriging, developed and used in physical sciences, extends ordinary kriging by supplementing the spatial model with additional covariates. We measured physical disorder on 1,826 sampled block faces across four U.S. cities (New York, Philadelphia, Detroit, and San Jose) using Google Street View imagery. We then compared leave-one-out cross-validation accuracy between universal and ordinary kriging and used random subsamples of our observed data to explore whether universal kriging could provide equal measurement accuracy with less spatially dense samples. Universal kriging did not always improve accuracy. However, a measure of housing vacancy did improve estimation accuracy in Philadelphia and Detroit (7.9 percent and 6.8 percent lower root mean square error, respectively) and allowed for equivalent estimation accuracy with half the sampled points in Philadelphia. Universal kriging may improve neighborhood measurement.