Electoral research and mapping

Over the past two decades staff in the Centre have collaborated with human geographers and in the process have seen the value of ‘seeing’ aggregate data patterns revealed through mapping processes. The first example came with a paper published in Political Geography and co-authored with Daniel Dorling, then of Bristol University (Dorling, Rallings et al. 1998). In fact, the idea began following a map that was published by the London Borough of Kingston that showed the distribution of seats at local elections beginning in 1964. This appeared to show a pattern in the growth of the Liberals (later the Alliance and more recently the Liberal Democrats.). The pattern suggested that following an initial victory or two the party would then expand its control of seats in a particular way with new seats being won that touched the boundaries of wards that had already been won by the party. Rallings and

Thrasher supplied the voting data but Dorling took the analysis a stage further by displaying national maps that sought to demonstrate that the spread of the Liberals was similar to that of a disease – spreading through contact and association (Figure 5.1 and Figure 5.2). This is why the title included the word ‘epidemiology’.

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During this research Dorling would prepare maps for separate parts of the country and then share these with the Plymouth team. Being able to see the growth and pattern of the growth was vital to aid the understanding of the dynamics of Liberal Democrat success. Maps enabled the researchers to visualize the process more effectively than would have possible using other types of methodology, for example that would include data in table formats. Another Elections Centre collaboration, this time involving the geographer Scott Orford of Cardiff University again used mapping to display patterns in the data (Orford, Rallings et al. 2008; Orford, Rallings et al. 2009; Orford, Rallings et al. 2011). This research focused on election turnout but gathered at much lower levels of aggregation than normal. It is the case for turnout to general elections that turnout is only provided at the constituency level. For local elections the turnout is given at the ward level. But some local authority election officers retain details for polling stations. Rallings and Thrasher discovered that some election officers kept very good records, not only keeping turnout figures for different types of election but also having an archive over time. As with the previous collaboration with Dorling the research process began with Plymouth assembling the aggregate voting turnout data for each polling station area, including post code identifiers for each station. Orford then used GIS to map these stations (Figure 5.3) providing the researchers with the capacity to test different hypotheses about the relationships between geography (distance to polling station, nature of the terrain, proximity to road networks) and the level of turnout for three types of election (parliamentary, European and local elections) (Figure 5.4 and Figure 5.5). Once again, it is clear to see the advantages the maps bring to understanding where polling stations were located (often for administrative convenience) and where they might be better located if the aim was to improve turnout at low turnout elections for the European parliament and some local elections.

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Figure ‎5.3: Wards, polling districts, and polling stations in the London Borough of Brent, 2001

Polling station

Site of maximum voter density

2.01 - 4.38 1.18 - 2.00 0.54 - 1.17 0.17 - 0.53 0.00 - 0.16

Figure ‎5.4: Percentage differences in predicted turnout when re-siting polling stations for European elections

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Following these collaboration the Elections Centre staff began to use GIS to examine some characteristics of patterns of voting at elections for the Greater London Authority. Here, the mapping process greatly assisted the visualisation of first, the geography of support for four small parties (Green, BNP, UKIP and Respect – see Figure 5.6 - Figure 5.9) (Borisyuk, Rallings et al. 2007) and second, whether small parties can use the knowledge gained from one type of electoral experience to help it win votes and seats at another type of election ((Thrasher, Borisyuk et al. 2012), Figure 5.11).

Polling station

Site of maximum voter density

Figure ‎5.5: Percentage differences in turnout when re-siting polling stations for local elections

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In the case of the first four maps relating to the 2004 elections the aim was to see whether there were any spatial patterns in the data. Although the elections were for the Greater London Authority the London Elects organisation that administered the elections using electronic counting provided information about party votes at the ward level. The Centre then used ward level GIS mapping coordinates to visualise the distribution of support for the Green party, Respect, BNP and UKIP. This had not been possible to do before since these are small parties and do not have candidates contesting local elections in every ward. But the Greater London Authority elections uses List voting and therefore everyone in London could now vote for these parties.

Mapping the data (Figure 5.6 - Figure 5.9) meant that the researchers could now see those areas that gave relatively strong support (dark shaded areas) to each one of these parties and where the support was weak (lighter shading). It was immediately clear that the anti-Iraq war Respect party which drew support from non-white Muslim populations, was strong in a group of wards slightly to the north east of central London while the anti-immigrant BNP (in wards dominated by white working class populations) were strongest in the wards that were

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Figure ‎5.6: Distribution of percentage vote shares for Respect

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Figure 5.9 is presented here in order to demonstrate how publishers, particularly the publishers of academic journals are lagging behind developments in computer software. Figure 5.9a and Figure 5.9b are identical apart from the obvious fact that the first map has

(a) (b)

Figure ‎5.8: Distribution of percentage vote shares for UKIP

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picture and the other is presented in grey-scales. When the article was accepted for

publication the publisher asked for maps to be re-submitted in the version on the right. The amount of information that is lost from this map by moving from a single colour to black and white is enormous. Some journals in political science are moving towards colour printing but there is still a great deal of limitation on the types of graphics that can be submitted which reduces the power of the authors to make their case.

Following the 2008 Greater London Authority elections the Centre conducted further

research that took advantage of the fact the data for these elections was being provided at the ward level by London Elects. It was decided to undertake a comparative analysis of voter support for the Green party in local elections across the London boroughs and compare that with how the party did at the GLA elections. The research focused on whether or not the Green party could learn from GLA elections about the wards where it was attracting votes and then use that information to fight those same wards in local elections.

Because the paper was being sent to the same journal for consideration there was

considerable discussion about the best method for overcoming the switch from colour to black and white. On this occasion the objective was not only to scale vote share for the Green party but also three configurations of whether or not a Green candidate had contested a ward at a previous and a subsequent election to the GLA election.

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Figure ‎5.10 Pattern of Green Party competition and 2004 London Assembly list vote

Figure 5.10 and Figure 5.11, for example, use four shades for vote share categories which are then overlaid by cross-hatching that describes Green party competition for seats. The dark shading is noticeable in two parallel lines running west to east but the real purpose of the map and the paper is the pattern of party competition. Some of the detail is lost simply because the ward areas located in central London are smaller because of higher population densities. With hindsight it might have been better to have used cartograms rather than physical maps. This would have avoided the problem of seeing the detail in small areas but the compromise of shading and cross-hatching did result in better mapping than was used in the earlier article.

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Figure ‎5.11 Pattern of Green Party competition and 2008 London Assembly list vote