Measuring the scales of segregation: looking at the residential separation of White British and other schoolchildren in England using a multilevel index of dissimilarity

Abstract

Within the segregation literature there has been a movement away from measuring ethnic segregation at a single scale, using traditional indices, to instead treating segregation as a multiscale phenomenon about which measurement at a range of scales will shed knowledge. Amongst the contributions, several authors have promoted multilevel modelling as a way of looking at segregation at multiple scales of a geographical hierarchy, estimating the micro‐, meso‐ and macro‐effects of segregation simultaneously. This paper takes the approach forward by outlining a multilevel index of dissimilarity that combines the advantages of using a widely understood index with a means to identify scale effects in a way that is computationally fast to estimate with freely available software to do so. To demonstrate the method, a case study is made looking at the residential separation of White British pupils from six other ethnic groups in England in 2011. It examines a claim made by the Casey Review into opportunity and integration that schoolchildren are more residentially segregated than the population at large. The results suggest that schoolchildren were indeed more residentially divided but comparison with earlier data and the general uplift in the scales at which patterns of segregation are evident suggest a trend of decreasing segregation overall and the spreading out of ‘minority’ groups.

Mapping the changing residential geography of White British secondary school children in England using visually balanced cartograms and hexograms

“…With reference to the geography we have mapped, although the spatial retrenchment of the White British into more semi-rural and rural locations appears to have continued beyond the 2011 Census, it does not follow that the country is becoming more segregated because the evidence is that those locations are becoming more ethnically mixed (Harris, 2017) and some urban locations have had an increase in their White British populations. The notion of 'white avoidance' raised by Cantle and Kaufmann (2016) seems, at a minimum, to be an over-generalisation of more complex demographic changes and their causes.…”

“…To that end, we follow Harris (2017) and turn to an alternative source of data, which is the National Pupil Data (NPD) for England for the years 2011 (the year of the last UK Census) and 2017 (the most recent data). The NPD has been described by the Department for Education as one of the richest education datasets in the world, holding a wide range of information about students.…”

Implementing a Multilevel Index of Dissimilarity in R with a case study of the changing scales of residential ethnic segregation in England and Wales

“…The statistical basis for the MLID has been outlined elsewhere (Harris, 2017a). Here, we avoid unnecessary duplication but expand upon some areas of relevance, particularly about partitioning the variance to look at spatial clustering and on the nature of the relationship between the variance and the ID.…”

“…Equation (5) shows that the ID is proportional to the sum of the magnitudes of the residuals from the regression model. Each residual can be treated as a localised measure of the over-or under-representation of the one group in relation to the other at each location in the study region (Harris, 2017a).…”

“…The third is that in comparison to other multilevel approaches it is more computationally tractable to run. In addition, the paper expands upon the statistical foundations provided by Harris (2017a) to consider three topics in greater detail: first, to show how the multilevel index measures the spatial clustering of segregation; second, to look at what other authors have advocated, which is to use variance as a measure of (spatial) unevenness, and how that relates to the ID; third, to suggest how the patterns of segregation may be visualised at each scale.…”