Residential sorting across Auckland neighbourhoods

This paper addresses the extent to which people in Auckland exhibit residential location patterns that differ between groups, i.e. the extent to which they are spatially sorted. To measure patterns of residential location, the paper uses the index of segregation, an isolation index, Gini coefficients, Ellison & Glaeser and Maurel & Sédillot concentration measures, Moran’s I and Getis and Ord’s G*. Results are presented based on a classification of the population in different ways: ethnicity, income, education, age and country of birth. Both city-wide and local measures are considered. We find that ethnic-based sorting is the strongest indicator of residential sorting patterns, but soring by income, education and age is also present. Sorting by income and qualifications is strongest at the top and, to lesser extent, at the bottom of the income and qualifications range. Age segregation is most pronounced for older residents. Clustering is strongest within a range of up to one kilometre and declines significantly over greater distances. Local analysis by means of Getis and Ord’s G* calculations suggest significant ethnic clustering. Apart from Maori and Pacific Islanders, ethnic groups tend to locate way from each other, as confirmed with cross-Moran’s I calculations. When considering interactions between ethnicity and income we find that the location of ethnicity income subgroups is more strongly related to neighbourhood income

Does ethnic diversity erode trust? Putnams hunkering down thesis reconsidered

We use a multi-level modelling approach to estimate the effect of ethnic diversity on measures of generalized and strategic trust using data from a new survey in Britain with a sample size approaching 25,000 individuals. In addition to the ethnic diversity of neighbourhoods, we incorporate a range of indicators of the socio-economic characteristics of individuals and the areas in which they live. Our results show no effect of ethnic diversity on generalized trust. There is a statistically significant association between diversity and a measure of strategic trust, but in substantive terms, the effect is trivial and dwarfed by the effects of economic deprivation and the social connectedness of individuals

The construction of neighbourhoods and its relevance for the measurement of social and ethnic segregation: evidence from Denmark

In this paper we propose a model for constructing neighbourhoods based on georeferenced data and administrative data. The 431,233 inhabited hectare cells in Denmark are clustered into 9,404 small and 2,296 large neighbourhoods, inhabited on average in 2004 by 572 and 2,343 persons respectively. The priorities in the clustering process are to obtain neighbourhoods that are unaltered over time, delineated by physical barriers, compact, homogeneous in terms of type of housing and ownership, relatively small, homogeneous in terms of number of inhabitants, and comprised of a contiguous cluster of cells. To illustrate the importance of detailed neighbourhood information we compare social and ethnic segregation measured by Isolation and Dissimilation indices on the levels of municipalities and of small neighbourhoods. Our findings demonstrate substantial variation in the residential mix in neighbourhoods within a given municipality, and thus show the importance of having information on a more detailed geographical level than that of the municipality

Explicating the role of partnerships in changing the health and well-being of local communities: a profile of neighbourhood renewal activity focused on promoting health and well-being in Salford and the north west region and the north east of England

This scoping and mapping report is one of three outputs from a project: Explicating the role of partnerships in changing the health and well-being of local communities, one of a number of projects in a larger Higher Education Funding Council Strategic Development Fund project ( HEFCE ) entitled: Urban Regeneration: Making a Difference. This was a collaborative venture between Manchester Metropolitan University, Northumbria University, University of Salford and University of Central Lancashire. Bradford University was an affiliated partner