Different Ways of Winning
In a previous post, we looked at voting patterns in one constituency in UP – Muzaffarnagar – which, in 2013, saw serious communal riots. The hypothesis was that the riots would polarise voting across the area. To see if this was true, we looked at the vote share of the biggest party (i.e. the one scoring the most votes) in each polling booth. What was apparent was that many,many booths across the constituency essentially turned into winner-take-all contests. In these booths, the largest party ended up with a very high vote share – often in excess of 90%. Whole villages or areas under a single booth chose to vote sharply one way or the other. This was in contrast to 2009, where the average booth saw a much more diverse pattern of voting behaviour.
The map below essentially extends that analysis to the whole of UP. The darker areas saw more polarised voting, and the lighter areas saw less. What we see is a sharp difference between Western UP (where Muzaffarnagar is located), and the rest of the state. Voting in both central and Eastern UP was far less polarised than it was in the West. The white spaces on the map are those for which the data could not be compiled.
This map needs some explanation of how it was constructed, so here goes.
There are over 1.3 lakh data points underlying this map – one for each booth (but with gaps). I could have plotted each point on the map, coloured by the vote share of the largest party. This would have been overkill simply because multiple booths are located at one point (thus overlapping each other on a map). The problem was to aggregate data for booths in the same locality but without aggregating so much as to lose some of the complexity of voting patterns, even within a single constituency.
The technique I used (explained in much greater detail here), was to overlay the map with a number of cells. These are the tiny hexagons you see on the map – just zoom in and they will be more visible. Each of these cells is exactly the same area. I look at the polling booths which fall within the bounds of each cell, and take the median of the vote shares of the largest parties in just those booths. Then we color the cell according to that median value – darker red for higher vote shares and lighter colors for lower vote shares. The grey lines are the actual boundaries of each of the 80 parliamentary constituencies in the state.
The white areas you see on the map are those for which either the locations of polling booths werent available or for which data did not exist. You’ll also notice a number of points which fall outside the boundaries of the state – these are obviously incorrectly located, but I left them in anyway. This post owes a huge debt to Raphael Susewind who actually put the polling booth location data together and cleaned it up.
A couple of broader points :
* There are a couple of outliers in this map. The darker area in central UP is Rae Bareli, the stronghold of the Gandhi family. The lighter coloured area in Western UP is Sambhal, which saw distinctively lower polarised voting than other constituencies in the region. Then there are constituencies like Ghaziabad (to the left of Sambhal on the UP border) which saw both types of voting behaviour – some areas saw a pattern of sharply polarised voting, but other parts of the constituency didn’t.
*The BJP won 71 of 80 seats in UP. It emerged strong across the state, irrespective of geographic location. What this map shows (and this is true of political parties in general I think), is that it had many different ways of winning. In context of an immediate election outcome this may not matter much (winning is winning, after all). But for journalists and researchers, exploring this idea of how a party won in different areas is, it seems to me, an idea very much worth exploring analytically and empirically.
For those already tired of UP election data, and election analysis in general, my apologies. But I may do just one more piece on this idea of ‘ways of winning’.
Here’s a version of the map which is also (a bit more) interactive. Caution : clicking on this, loads a 7 MB csv file, so you have been warned. It may take a minute or two to render, especially on a slow machine and/or internet connection. Mouse over a constituency to see details for that constituency. Unfortunately it’s also this part which is a bit buggy. Sometimes, the mouse over works, and sometimes it doesn’t, for some reason. I am trying to fix it.
July 4, 2014