Understanding ethnically integrated schools in the UK

This research examines the factors that contribute to creating more integrated schools in ethnically diverse areas. More specifically, it asks:
Which school, neighbourhood and city level characteristics are most associated with more ethnically integrated schools?
It addresses this research question through the following objectives:
1a) Describe the patterns of school level segregation since the 2001 census in five UK cities - at a student, school, neighbourhood and city level.
1b) Describe the key societal changes (social, economic, political, educational and demographic) since the 2001 census that are likely to have impacted school segregation.
2) Explore the associations between the measures of segregation and the measures of societal change.
3) Explore and identify causal mechanisms for the associations found.
4) Offer generalisable findings that may be applicable to all five cities, as well as other UK cities.
Methodology
Population and sample
This research will focus on five UK cities (Leicester, Birmingham, Manchester, Bradford and Nottingham) which all have a high percentage of non-White British residents - making for a fairer comparison in regards to segregation. As each city is contained within a single Local Authority I will use existing district boundaries to define the geographical parameters of my study.1
The sample will contain all state funded primary and secondary schools over a period of approximately 16 years from 2001-2017. This time period was chosen to align with the 2001 national census, as well as the dramatic increase in immigration from 1998 onwards (Migration Watch UK, 2017) which began the UK's move towards becoming a multi-ethnic society.
The sample for the 2017 school year contains a total student number of 404472, within 745 primary schools and 182 secondary schools. As the research takes place over a 16-year period, these figures will not be consistent throughout the research.
Quantitative analysis
The quantitative analysis will draw on publicly available databases from The Office of National Statistics and The National Pupil Database from the Department for Education. The investigation will be primarily centred on finding associations between measures of segregation and different societal variables.
To measure segregation I will use a variety of outcome variables depending on the unit of analysis (student, school, LA or city). These include:
Shared Peer Ethnicity (Mitchell, forthcoming 2017)
Proportion of one ethnic group in relation to another (Leckie and Golstein, 2015)
Converting a fitted model into a dissimilarity index using data simulation (Leckie et al, 2012)
As this is a relatively novel approach, I intend to do further research in my first year to ensure that my measure of segregation is valid and reliable.
For the predictor variables, I will use the results of previous research (Gorard, 2016; Casey, 2016), as well as the findings from a pilot project I conducted as part of my masters programme, to select variables that are likely to be associated with school segregation. This data will be sourced from publically available ONS databases.