Gender and daily mobility in a New Zealand city, 1920–1960

Although it is widely accepted that transport—like other social practices—is gendered, the concept of gender used in transport research is often one‐dimensional, with the focus on gendered variations in behaviour rather than on gendered meaning and identities. In this paper, I develop a more complex and multi‐stranded way of approaching the issue of gender and transport (or rather, daily mobility). A case study of a neighbourhood in the New Zealand city of Dunedin in the early decades of last century is presented to explore how the practices of daily mobility constituted gender. A three‐part concept of gender is developed as a basis for analysis: gender as a pattern of social relations, a cultural system of meaning and a component of personal identity. This is then used to analyse a collection of sixty oral histories. The period 1920–1960 is particularly interesting; in these decades extensive and widely used public transport systems (notably electric trams) shared urban streets with bicycles and pedestrians, and the emerging private modes of motorcycle and motor car. As new transport technologies were taken up, they offered the opportunity for new social practices to be formed around their use, for cultural meanings to be assigned to the technologies and for embodied individual subjectivities to be constructed. I argue that we can usefully interpret the shifting patterns of transport use through the lens of gender, and that we can come to understand the process by which gender is constructed by attention to everyday trip‐making and presence on the street.     

HISTORY,INSTITUTIONS, AND CITIES: A VIEW FROM THE AMERICAS*

ABSTRACT Every nation, formally or informally, defines and establishes the lines of political and fiscal authority among its national, regional, and local governments. Historically, centralized governments tend to restrict the power and autonomy of provincial and local governments. In this paper, we exploit the quasi‐experimental distribution of political institutions in the Americas caused by variation in European colonial experience to examine the impact of institutions on urban and local development, specifically on the degree of urban primacy, the size distribution of cities, the number and density of local government units, and the fragmentation of metropolitan areas. We argue that centralization of political power at the national level, as experienced in many countries in Latin America, contributes to urban primacy and a size distribution of cities favoring large cities. Additionally, even in more politically decentralized countries such as Canada and the U.S., variance in political centralization at the provincial (state) level over local governments led to significant divergences in urban primacy, the distribution of city sizes, as well as the form, number, and density of local governments. While we cannot rule out the importance of other factors, our findings suggest that political centralization affects spatial economic development.     

YANGJEN-THE FIRST TIBETAN FEMALE LAWYER

As the first group of Tibetan lawyers in Tibet and actually the first female lawyer,the first lawyer to open a collective law firm in Tibet and the first individual to open a private law consultation firm,Yangjen holds manyfirstin Tibetan law.     

Analyzing Hotspots of Crime Using a Bayesian Spatiotemporal Modeling Approach: A Case Study of Violent Crime in the Greater Toronto Area

Conventional methods used to identify crime hotspots at the small‐area scale are frequentist and employ data for one time period. Methodologically, these approaches are limited by an inability to overcome the small number problem, which occurs in spatiotemporal analysis at the small‐area level when crime and population counts for areas are low. The small number problem may lead to unstable risk estimates and unreliable results. Also, conventional approaches use only one data observation per area, providing limited information about the temporal processes influencing hotspots and how law enforcement resources should be allocated to manage crime change. Examining violent crime in the Regional Municipality of York, Ontario, for 2006 and 2007, this research illustrates a Bayesian spatiotemporal modeling approach that analyzes crime trend and identifies hotspots while addressing the small number problem and overcoming limitations of conventional frequentist methods. Specifically, this research tests for an overall trend of violent crime for the study region, determines area‐specific violent crime trends for small‐area units, and identifies hotspots based on crime trend from 2006 to 2007. Overall violent crime trend was found to be insignificant despite increasing area‐specific trends in the north and decreasing area‐specific trends in the southeast. Posterior probabilities of area‐specific trends greater than zero were mapped to identify hotspots, highlighting hotspots in the north of the study region. We discuss the conceptual differences between this Bayesian spatiotemporal method and conventional frequentist approaches as well as the effectiveness of this Bayesian spatiotemporal approach for identifying hotspots from a law enforcement perspective.     

A Bayesian Approach to Modeling Binary Data: The Case of High‐Intensity Crime Areas

This paper reports the fitting of a number of Bayesian logistic models with spatially structured or/and unstructured random effects to binary data with the purpose of explaining the distribution of high‐intensity crime areas (HIAs) in the city of Sheffield, England. Bayesian approaches to spatial modeling are attracting considerable interest at the present time. This is because of the availability of rigorously tested software for fitting a certain class of spatial models. This paper considers issues associated with the specification, estimation, and validation, including sensitivity analysis, of spatial models using the WinBUGS software. It pays particular attention to the visualization of results. We discuss a map decomposition strategy and an approach that examines properties of the full posterior distribution. The Bayesian spatial model reported provides some interesting insights into the different factors underlying the existence of the three police‐defined HIAs in Sheffield.