The Financial Times is on the shortlist of the Data Journalism Awards with their ‘Poor pupils catching up in exams’ (article/map). “There is hysteria about poor children falling behind which dominates British education coverage. But, actually, poor children have been closing the gap. There’s a long way to go, but it’s important to recognise a modest success.” An interview with FT journalist Chris Cook, who has been into data journalism for 2 years.
What inspired you to make ‘Poor pupils catching up in exams’?
I’m a contrarian – my first instinct is to ask “really? Is that true?’
Did you work by yourself or in a team?
Lots of colleagues help out in all sorts of ways – especially Martin Stabe and Chris Campbell and Cleve Jones, who helped visualise the data.
So too did a cast of academics.
How did you get a hold on the data you needed?
I applied to the government to be allowed to use it.
Which tools did you use?
Stata 11, and a piece of map-drawing software.
How long did it take to make ‘Poor pupils catching up in exams’?
A few weeks. I spent a long time going back and forth with academics over it.
What was the hardest part of making ‘Poor pupils catching up in exams’?
Making quite complicated maths explicable to readers.
Do you have a useful tip for starting data journalists?
A specialist reporter who is data-competent will usually outperform a general reporter with excellent data journalism skills. It’s good to know what a story would look like, and have hypotheses to test, before you pick up the dataset.