How does higher education contribute to political divisions in the UK?
As my colleague Jim Dickinson argues, HE is both an opportunity that helps people get the opportunity to live the lives they want and a means of separating them from their background. A referendum and an election have shared to highlight this – and have seen MPs develop an interest in the views of “ordinary people”. Higher education, it turns out is a touchstone that polarises people – our national relationship with academia is more complex than we may care to admit.
But how do we measure how people have been exposed to or engaged with HE – and how do we use these measurements to examine voting patterns?
With the UK parliamentary constituency as my unit, I’ve chosen three variables that might offer us a glimpse of how each part of the UK has engaged with HE.
POLAR4 is the one you might be most familiar with – a measure of the rate of young participation in HE. POLAR was developed by Mark Corver (now of DataHE) when he was at HEFCE, and the Office for Students now owns the dataset. The measure is traditionally shown as five quintiles, with quintile 1 representing those areas with lowest rates of participation in HE. POLAR4 is usually calculated for Mid-level Super Output Areas – I’m grateful to ONS for helping me come up with a constituency variant, though all errors are my own.
Application rates comes from the UCAS release of application numbers by their 15 January deadline – which is made available by constituency each year. There’s a time series right back to 2008.
Number of institutions and FTE staff/students as % of voters are two troublesome data points of my own – both drawn from my new-found ability to map institutions to constituencies via postcodes. Expressing the FTE for staff and students as a percentage of the constituency electorate does not imply all of these people vote in this constituency – you could see it more as the number of “HE people” you might find in the constituency on a given weekday. Clearly some, but not all, will reside in the constituency – but a transitory population of a significant size may have an impact on the character of an area. This data is derived from what is available from HESA – but is my fault, not theirs – and FTE for staff and students is taken from the most recent figures available in each case.
For general political information, the House of Commons Library has some great data from the 2017 election, and the constituency estimates for the percentage Leave vote in 2016 is taken from the work of Chris Hanretty. Constituency boundaries are from the very handy tableaumapping.bi.
In the maps above you can use the three sliders at the bottom to filter the visualisations by the number of institutions, POLAR4 quintile, and application rates – setting minimum and maximum values. You can also use the filters to find constituencies (and MPs) of interest, and there’s also a filter by the political party that held the constituency after the 2017 election.
What it shows us – Brexit
The young participation rates that underpin POLAR4 are the best of my three measures for predicting the likelihood of a constituency voting leave – with a reasonable correlation between constituencies with a high participation rate and constituencies with a low leave vote estimate.
UCAS applications show a similar but less pronounced pattern for 2019, and even going back to 2016 or earlier only shows a vague relationship. There’s very little correlation between HE people as a percentage of the electorate and the Brexit vote – here I’ve plotted only those constituencies with one or more large providers.
A high application rate is of course an indicator of an affluent neighbourhood. This effect is more reliable at the smaller (MSOA) scale, but it still works for constituencies, although less well-off parts of affluent constituencies may be hidden at this scale.
But I’m surprised by the lack of a relationship between the population linked to HE and a Brexit vote – I suspect that our “Remain by default” perception is down to a small group of very vocal academic staff – and I’d love to see a more detailed survey taking in all staff.
What it shows us – 2017 elections
In contrast – FTE as a % of the electorate is a fascinatingly good predictor of the winning party – only one of the top 20 on this measure elected Conservative (and that was the notable outlier of the City of London and Westminster, which curiously has a HE population larger than it’s actual electorate!)
In the next ten constituencies, we find only Filton and Bradley Stoke (UWE) and Welwyn Hatfield (Hertfordshire) voting Conservative – each has a lowish majority and would certainly be worth watching come the next election.
In comparison POLAR and application rates do not really seem to have much of a bearing on the winning party, surprising given the close relationship with Remain and Leave voting. What this suggests to me is that the 2016 referendum was a much more existential question, prompting deeper reflection, than a parliamentary election typically would.
There are numerous stories we can tell around why this might be the case. But why does participation in HE by young people from a constituency link to a Remain vote? And why does the presence of a lot of students and staff in a constituency link to a Labour, SNP, or Green vote? We don’t claim to have the answers to these questions – but the relationship between HE and political behaviour is clearly more complicated than is generally thought.