Richard Harris discusses a different approach to measuring ethnic and socio-economic segregation and fitting a multilevel index of segregation to census data in R.
The measurement of segregation has been debated in the social sciences for well over half a century.
Concerns about segregation, and the greece rcs data potential for it to harm society, are prevalent within recent Government reports and proposals, occasionally generating lurid (and often mis-leading) headlines in the media. Understandably, policy makers and other interested parties would like to know how much segregation there is and whether it is increasing.
However, their desire can be frustrated. The quest – sometimes taken by social scientists – for one perfect measure that could definitively answer those questions continues to allude researchers and always will.
Whilst much academic ink has been spent, for example, discussing the mathematical properties of different indices, there is more to the measurement than maths: different approaches reflect different conceptions of what segregation means as a process or as an outcome. Moreover, as new data, new computational tools and new thinking emerge, it is right to re-evaluate what is being measured, how and why.