'Local voting figures shed new light on EU referendum'

'Local voting figures shed new light on EU referendum'

Organisation: BBC Political Programmes (United Kingdom)

Publication Date: 03/12/2017

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Size of team/newsroom:large

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Description

On 23 June 2016 the United Kingdom voted narrowly to leave the European Union, by 52% to 48%. The results of the referendum were counted and announced in 399 official counting areas, largely based on local councils. This was the most important political decision in the UK for many years. We wanted to explore the underlying voting patterns in as much detail as possible, so we decided to undertake the extensive data-gathering exercise of trying to obtain from each council voting data at the most detailed geographical level available. This led to a major 3,700 word analysis on the BBC News website. Although the UK has a Freedom of Information Act, the electoral returning officers in councils who oversee voting arrangements are excluded from it. While a few councils issued such figures on their own initiative, in most cases we had to persuade councils to release data, sometimes with a great deal of persistence over several months. Some refused and others could not release anything useful because of the way ballot boxes had been mixed before counting, but we obtained significant information from 178 of the 399 areas. The most useful data was where councils provided voting figures for individual wards, which are the smallest local government administrative units. Since the UK census provides demographic data at this level, we were then able to conduct a multi-linear regression analysis of the relationship between voting figures and demographic factors. The headline results were: * The level of education had a higher correlation with the voting pattern than any other major demographic measure from the census, with lower qualified populations more likely to vote Leave. * The age of voters was also important, with older electorates more likely to choose Leave. * Ethnicity was crucial in some places, with ethnic minority areas generally more likely to back Remain. However this varied, and in parts of London some Asian populations were more likely to support Leave. * The combination of education, age and ethnicity accounted for the large majority of the variation in votes between different places As well as this overall picture, we were also able to identify the characteristics and locations of many particular places with interesting voting details. This included parts of the country with very high Leave or Remain votes, areas which were close to being nationally representative, neighbouring places which voted in very different ways, places with a different outcome to the official counting area of which they were part, etc. And we identified a common broad pattern in several urban areas of deprived, predominantly white, housing estates towards the urban periphery voting Leave, while inner cities with high numbers of ethnic minorities and/or students voted Remain. The data therefore provided us with both a uniquely powerful and insightful national analysis and also many interesting previously unknown stories at the local level.

What makes this project innovative? What was its impact?

Through the project we were able to put into the public domain a great deal of local voting data on this crucial topic, which would otherwise have remained secret. And we were able to explain some of its significance, at the national and local level. It thus made a unique and important contribution to public understanding of the most important political development in the UK's history for a considerable time. It had huge impact. Within a week of publication the story had over 2 million page views on the BBC website, and was shared extensively on social media, including over 30,000 shares on Facebook. The article also received over 4,300 online comments. The story was followed up in other media and provoked a great deal of discussion. We made the individual ward data available in a downloadable spreadsheet. Others have since used this data to publish their own statistical investigations of the results, confirming but also extending our findings. Our research and analysis were praised on the UK's leading electoral analysis websites, and were also referred to in Parliamentary debate. The report prompted a range of political responses from those on opposing sides of the UK's Brexit debate. But we were clear our task was simply to obtain as much information as possible, make it publicly accessible, and impartially analyse the collected data, in order to improve public understanding and promote better-informed political discussion.

Technologies used for this project:

The main tool was Excel. The figures obtained from councils were entered into Excel, and the data selected and downloaded from the national census website was also imported into Excel. We then used Excel for the multi-linear regression analysis, other statistical tests, generating scatter plots, checking the totals of our data against the official results, and all the other necessary calculations. A good part of the effort involved was the traditional journalistic process over several months of emailing and phoning hundreds of councils and persuading as many as possible to release the data, and chasing the stragglers. While some could not comply for reasons already explained, in the end there were just three councils who had not responded with a definite decision by the time we decided to publish the story. Most of the contact with councils was done by the BBC's freedom of information researcher, George Greenwood. The detailed statistical analysis of the figures and the reporting of them was done by the BBC's freedom of information specialist and political producer, Martin Rosenbaum. The project arose out of a piece Martin wrote for the BBC News website in the few days after the referendum, http://www.bbc.co.uk/news/uk-politics-36703570. This analysed the ward level voting data for Birmingham, one of the few councils which published these results at its own initiative.
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