The items on this page are fairly brief presentations of different products of research work. So as well as short text pieces they include charts, maps, software and so on. They’re here in part simply to illustrate some of my work to a general audience. There’s also a particular focus on the production and circulation of data, charts, maps and so on - so on the making and uses of research.
This is an introduction to using the sample survey Households Below Average Income in the R Statistics Package. With this you have all you need to carry out analysis of the distribution of income in the UK using the world’s finest open-source software.
This is lightly adapted from a blog post for the LSE policy and politics blog, which also appeared on the RSS’s website Stats Life
In the course of research on trends in poverty in London from 2000 to 2011, some interesting findings on the spatial distribution of poverty in the city emerged. These suggested that, at neighbourhood level, poverty rates in much of the historically deprived inner city had fallen, sometimes quite dramatically. Over the same period poverty rates had increased in suburban areas.
Data on welfare benefits are widely used in research and public administration to describe spatial variations in the prevalence of poverty in the UK. Many poor households, however, receive no benefits, and not all benefit recipients are income-poor. Are statistics on benefits receipts, then, really good proxies for describing the geography of poverty?
The maps show the parts of London where housing is affordable and accessible for low-income private tenants who get Housing Benefit to help pay their rent. Changes to Housing Benefit introduced in 2010 were very likely to reduce the amount of housing affordable to low-income tenants, especially in inner London.
Since around 2001 I’ve been using the Ruby programming language for everyday programming needs. Amongst other things, I used the WxRuby package to write desktop applications using Ruby, most notably the Weft QDA software for analysing qualitative data analysis. For several years from around 2006 I also led development of WxRuby.
Weft QDA is/was a free, open-source package for the analysis of qualitative (unstructured text) data. I originally wrote it in 2003-2004 to analyse interviews and field notes from my MSc dissertation research on credit unions in South London.