mcallaghan · August 29, 2015 14:15
diff --git a/2010_results.csv b/2010_results.csv
diff --git a/foreign_born.csv b/foreign_born.csv
diff --git a/index.html b/index.html
 <!DOCTYPE html>
 <html>
 <head>
 	<meta http-equiv="X-UA-Compatible" content="IE=edge,chrome=1">
  	<meta charset="utf-8">
  	<script type="text/javascript" src="http://d3js.org/d3.v3.min.js" ></script>
 	<script src="//ajax.googleapis.com/ajax/libs/jquery/2.1.1/jquery.min.js"></script> 
 	<script src="http://d3js.org/topojson.v1.min.js"></script>
 	<link rel="stylesheet" type="text/css" href="theme.css"></link>
 </head>
 <body>
 <div id="main">
 <p>
 	<h1>Support for UKIP and Immigration Levels</h1>
 </p>
 <div class="text">

 We no longer widely dismiss UKIP or their supporters as bigots. Instead, politicians
 and the media have started to treat the phenomenon of UKIP as a manifestation
 of the real concerns of people about "the pressure immigration puts on public 
 services", among other things. The leader of the Labour Party went so far as to
 say that UKIP supporters' migration concerns are <a href="http://perma.cc/GTF2-GZEJ" target="_blank">
 'based on reality, not prejudice'</a>. If this were the case, we would 
 expect support for UKIP to be higher in areas where there were higher levels 
 of immigration, as these would be the areas where immigrants were putting pressure
 on local services.
 With the 2015 general election approaching, and UKIP claiming a lot of attention,
 results from the last general election were tested against this hypothesis. Two maps 
 of English parliamentary constituencies were created, one (on the left) 
 showing support for UKIP, and the other (on the right) showing the percentage 
 of the population that was born outside the UK. Each constituency was coloured 
 either white (representing 0) or purple (representing the maximum value) or somewhere
 in between on a linear scale from 0 to the maximum.

 </div>
 <div id="map" class="map"></div>
 <div id="map2" class="map"></div>
 <br>
 <div id="key" class="key"></div>
 <div id="key2" class="key"></div>
 <div class="text">

 The data are drawn from the results of the general election in 2010 (pulled from the
 Guardian <a href="http://perma.cc/9U8B-LX8L" target="_blank">
 website</a>) and the 2011 census (pulled from the 
 <a href="http://perma.cc/GTF2-GZEJ" target="_blank">
 Migration Observatory at the University of Oxford</a>). They do not seem to support
 the idea that UKIP gained higher vote shares in areas that have the highest concentration
 of immigrants. If they did, the darker purple patches on the left would be mirrored
 by darker purple patches on the right. In fact, some of constituencies which showed
 the greatest support for UKIP, such as Buckingham, Staffordshire Moorlands, Boston and
 Skegness and Christchurch, have relatively low levels of immigration and appear in a
 lightish purple on the right map. On the other hand, some of the constituencies with the
 highest concentrations of foreign-born residents have very low levels of support for
 UKIP: if high immigration puts pressure on local services, turning disaffected voters 
 towards UKIP, why would only 0.73% of voters in Brent North (where the concentration of
 foreign-born residents is highest at 59.27%) vote for UKIP?

 </div>
 <div id="corbox">
 </div>
 <div class="text">
 Plotting votes for UKIP against foreign-born population in each constituency (above) we
 actually observe a weak negative correlation between immigration and UKIP support. The 34
 constituencies where  UKIP did not field a candidate were excluded, though the average
 percentage of the population born in another country in these constituencies was
 18.51, compared to 12.84 in England as a whole. Assuming that the decision to field a 
 candidate was based on the perceived chance of success, this lends further support to 
 the idea that UKIP are more successful in areas with lower immigration.
 It is hardly the first time that it has been pointed out that the rise of UKIP is not
 just about immigration. Nor is it the first time that the claim that immigration will 
 ruin public services has been refuted. Services, after all, are paid for by taxes, and 
 immigrants pay taxes and actually make <a href="http://perma.cc/4K4Z-MMGS" target="_blank"> a positive net 
 contribution to the budget</a>. 
 But the fact that higher levels of immigration in a constituency
 actually make it less likely for those who live there to vote for UKIP shows centrist 
 parties' increasingly xenophobic rhetoric to be particularly disingenuous. 
 </div>
 </div>

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 d3.json("topo_wpc.json", function(error, uk) {
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 	d3.csv("2010_results.csv", function(res) {
 		for (i = 0; i < cons.length; i++) {
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 			cons[i].UKIP = 0
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 				if (cons[i].properties.PCON13NM == res[j].Seat && res[j].Party == "UKIP") {
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 		cons_miss = cons.filter(function(d) {
 			if (d.UKIP == 0) {
 				return false
 			} else {
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 			}
 		})

 		no_ukip = cons.filter(function(d) {
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 					.style("opacity", 0.8)
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 					.style("opacity", 1);
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 					.transition().duration(300)
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 					.style("opacity", 0);
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 		correlation()
 		lbf()
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 var totalheight = $("#main").height()
 d3.select(self.frameElement).style("height", totalheight + 50 + "px");

 function lbf() {
 	var m_x = d3.mean(cons_miss, function(d) { return d.fb })
 	var m_y = d3.mean(cons_miss, function(d) { return d.UKIP })
 	var x_y = d3.sum(cons_miss, function (d) { 
 		var x = d.fb - m_x
 		var y = d.UKIP - m_y
 		return x*y 
 	})

 	var x_x2 = d3.sum(cons_miss, function (d) { 
 		var x = d.fb - m_x
 		return x*x;
 	})
 	var m = (x_y)/(x_x2)

 	var b = m_y - m*(m_x)

 	var line = "UKIP vote share = " + b.toFixed(2) + m.toFixed(2) + "* Foreign-born population" 

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 		.attr("class", "fit")
 		.attr("stroke-width", 1)
 		.attr("stroke", "black")
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 			div.transition().duration(300)
 				.style("opacity", 0);
 		});

 }

 function correlation() {

 	for (i = 0; i < cons_miss.length; i++) {
 		cons_miss[i].xy = cons_miss[i].fb * cons_miss[i].UKIP
 		cons_miss[i].xx = cons_miss[i].fb * cons_miss[i].fb
 		cons_miss[i].yy = cons_miss[i].UKIP * cons_miss[i].UKIP
 	}
 	var n = cons_miss.length
 	var sum_x = d3.sum(cons_miss, function(d) { return d.fb })
 	var sum_y = d3.sum(cons_miss, function(d) { return d.UKIP })
 	var sum_xy = d3.sum(cons_miss, function(d) { return d.xy })
 	var sum_xx = d3.sum(cons_miss, function(d) { return d.xx })
 	var sum_yy = d3.sum(cons_miss, function(d) { return d.yy })

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 		.attr("y", h*0.25)
 		.text("Correlation = " + r.toFixed(2));
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 		.attr("stroke-width", 1)
 		.attr("stroke", "black");

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 		.attr("class", "axlabel")
 		.attr("text-anchor", "middle")
 		.attr("font-size", "18px")
 		.attr("fill", "black")
 		.attr("x", corw*0.55)
 		.attr("y", corh*0.98)
 		.text("Foreign-born Population (%)");

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 		x = i*10
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 			cor.append("text")
 				.attr("class", "axlabel")
 				.attr("text-anchor", "middle")
 				.attr("font-size", "12px")
 				.attr("fill", "black")
 				.attr("x", fbscale(x))
 				.attr("y", corh*0.93)
 				.text(x);
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 		.attr("x1", corw*0.1)
 		.attr("x2", corw* 0.1)
 		.attr("y1", corh*0.9)
 		.attr("y2", corh*0.1)
 		.attr("stroke-width", 1)
 		.attr("stroke", "black");

 	cor.append("text")
 		.attr("class", "axlabel")
 		.attr("text-anchor", "middle")
 		.attr("font-size", "18px")
 		.attr("fill", "black")
 		.attr("transform", "translate(" + corw*0.04 + ", " + corh*0.5 + ") rotate(270)")
 		.text("UKIP Vote Share (%)");

 	for (i = 0; i < 11; i++) {
 		x = i*5
 		if (x < max_fb) {
 			cor.append("text")
 				.attr("class", "axlabel")
 				.attr("text-anchor", "middle")
 				.attr("font-size", "12px")
 				.attr("fill", "black")
 				.attr("x", corw*0.07)
 				.attr("y", ukipscale(x))
 				.text(x);
 		}
 	} 
 }

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 }

 function download() {
    var array = [{s: "constituency", u: "ukip", fb: "fb"}]
 	for (i = 0; i < cons.length; i++) {
 		var name = cons[i].name.replace(",","")
 		array.push({s: name, u: cons[i].UKIP, fb: cons[i].fb})
 	}

 	console.log(array)

    var str = '';
     
    for (var i = 0; i < array.length; i++) {
        var line = '';
        for (var index in array[i]) {
            if(line != '') line += ','
         
            line += array[i][index];
        }
 
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    }
 
    if (navigator.appName != 'Microsoft Internet Explorer')
    {
        window.open('data:text/csv;charset=utf-8,' + escape(str));
    }
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    {
        var popup = window.open('','csv','');
        popup.document.body.innerHTML = '<pre>' + str + '</pre>';
    }          
 }

 </script>

 </body>
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diff --git a/theme.css b/theme.css
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 	text-align: center;
 }

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 	border: 1px solid black;
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 	padding: 2px;
 	font-size: 10px;
 	background: #FFFFE0;
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 	border-radius: 8px;
 	pointer-events: none;
 }

 circle {
 	fill-opacity: 0.6;
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 input[type='range'] {
 	width: 500px;
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 	display: inline;
 	margin-bottom: -20px;
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 	clear:both;
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 	display: inline;
 }

 .key_svg {
 	margin-top: -10px;
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 .key_title {
 	font-weight: bold;
 }

 .text {
 	text-align: left;
 	width: 850px;
 	margin: 5px auto;
 	padding: 25px;
 	
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 #scatter {
 	background-color: white;
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diff --git a/thumbnail.png b/thumbnail.png
diff --git a/topo_wpc.json b/topo_wpc.json
	Seat	Foreign_born
	Knowsley	1.969011645
	Houghton and Sunderland South	1.972368451
	Islwyn	2.032940802
	Rhondda	2.050994596
	Blaenau Gwent	2.134242416
	North Durham	2.145413947
	Easington	2.178351798
	Redcar	2.216391632
	Neath	2.26794609
	Staffordshire Moorlands	2.298672652
	Blyth Valley	2.319468445
	Ogmore	2.32545693
	North East Derbyshire	2.358283126
	Workington	2.360808034
	Wansbeck	2.377289377
	Bishop Auckland	2.389176411
	Jarrow	2.392505405
	Wentworth and Dearne	2.412910803
	Washington and Sunderland West	2.424987869
	St Helens North	2.428562548
	Makerfield	2.474491355
	Cannock Chase	2.475836736
	Blaydon	2.541883304
	Torfaen	2.562016077
	Halton	2.569608927
	Sedgefield	2.579072533
	Penistone and Stocksbridge	2.603730753
	Amber Valley	2.676285516
	Middlesbrough South and East Cleveland	2.680283541
	North West Durham	2.691084358
	Cynon Valley	2.697528716
	Caerphilly	2.710968039
	South Staffordshire	2.774010998
	Hartlepool	2.774155692
	Rother Valley	2.842254355
	Barnsley East	2.844063074
	Aberavon	2.844268368
	Dwyfor Meirionnydd	2.875972659
	Sefton Central	2.887241055
	Sherwood	2.907334678
	Bootle	2.931467054
	St Helens South and Whiston	2.9565753
	Barrow and Furness	2.972102763
	Bolsover	2.972277794
	Ashfield	3.020193496
	Doncaster North	3.056675865
	Beverley and Holderness	3.134899948
	Berwick-upon-Tweed	3.147204099
	Stone	3.150185759
	Copeland	3.153626485
	Carmarthen East and Dinefwr	3.169777327
	Penrith and The Border	3.196140694
	Eddisbury	3.198533276
	Derbyshire Dales	3.266686157
	Congleton	3.282949108
	Louth and Horncastle	3.283273985
	East Yorkshire	3.333432958
	Cleethorpes	3.376320879
	Ynys Mon	3.39923442
	Hexham	3.435384858
	Ludlow	3.475258376
	Gower	3.478584921
	Elmet and Rothwell	3.492165464
	High Peak	3.522862298
	Delyn	3.552806388
	Ribble Valley	3.558274613
	Castle Point	3.5597823
	Clwyd South	3.571179271
	Lichfield	3.571543797
	Wirral South	3.578935723
	South Ribble	3.653038379
	Don Valley	3.663178409
	Wallasey	3.678279147
	Normanton, Pontefract and Castleford	3.679276086
	Chorley	3.690009691
	Weaver Vale	3.704669971
	Waveney	3.755098854
	Torridge and West Devon	3.77123571
	Montgomeryshire	3.784944888
	Erewash	3.786283892
	Forest of Dean	3.796116843
	Merthyr Tydfil and Rhymney	3.832757245
	Kingston upon Hull East	3.841761206
	South Derbyshire	3.849446682
	Aldridge-Brownhills	3.862343129
	Haltemprice and Howden	3.86244761
	West Lancashire	3.862991445
	North West Leicestershire	3.867633843
	Wyre Forest	3.877519775
	Calder Valley	3.880109945
	North Tyneside	3.886634915
	Tamworth	3.888434347
	Leigh	3.890404575
	Stockton North	3.897515022
	Rayleigh and Wickford	3.9043882
	Chesterfield	3.92287234
	South East Cornwall	3.922993098
	Hazel Grove	3.935685145
	Wirral West	3.94746348
	Clwyd West	3.948863636
	Bromsgrove	3.956769226
	Bosworth	3.963085814
	North Norfolk	3.973063973
	Broadland	3.991049292
	Tynemouth	3.992547515
	Ellesmere Port and Neston	4.007455732
	Gainsborough	4.011164535
	Rossendale and Darwen	4.013891049
	Mid Derbyshire	4.028137551
	Wigan	4.057794617
	St Austell and Newquay	4.058530083
	South West Devon	4.064171123
	Camborne and Redruth	4.120043073
	Dudley South	4.149507834
	Vale of Clwyd	4.187001589
	South Shields	4.188640727
	Thirsk and Malton	4.203240879
	Maldon	4.233251123
	Clacton	4.270199979
	Hemsworth	4.281949231
	Morley and Outwood	4.284248598
	Barnsley Central	4.371514572
	Vale of Glamorgan	4.379278238
	Newton Abbot	4.382781596
	North Devon	4.40496653
	Preseli Pembrokeshire	4.442007129
	Pontypridd	4.45375331
	Kingswood	4.462667737
	North Warwickshire	4.469422663
	North Cornwall	4.471117608
	St Ives	4.482349207
	Brecon and Radnorshire	4.492969348
	Monmouth	4.515543454
	Aberconwy	4.520074448
	Selby and Ainsty	4.538787229
	Bridgend	4.559738585
	Blackpool North and Cleveleys	4.573635045
	Llanelli	4.615668657
	Plymouth, Moor View	4.61607377
	Birkenhead	4.619559098
	Thornbury and Yate	4.647517063
	North East Somerset	4.6628498
	Alyn and Deeside	4.680928429
	Carmarthen West and South Pembrokeshire	4.682045049
	Bassetlaw	4.722179408
	North Shropshire	4.750258948
	West Worcestershire	4.767723494
	Tiverton and Honiton	4.77052029
	Stourbridge	4.788723007
	South Norfolk	4.803804752
	Central Devon	4.829858534
	Fylde	4.836780038
	Brigg and Goole	4.839342145
	Liverpool, Walton	4.877225826
	Totnes	4.916726047
	Morecambe and Lunesdale	4.922276838
	South Suffolk	4.93068271
	Sleaford and North Hykeham	4.960560438
	Mid Dorset and North Poole	4.976916317
	Garston and Halewood	4.995035672
	North Somerset	4.996031665
	Great Grimsby	5.000963249
	Denton and Reddish	5.017942026
	Havant	5.050340136
	Wyre and Preston North	5.074380539
	Macclesfield	5.075695844
	Westmorland and Lonsdale	5.101347728
	Isle of Wight	5.119878494
	Scarborough and Whitby	5.133522931
	Bridgwater and West Somerset	5.138562705
	Bolton West	5.182865546
	Warrington North	5.21567433
	Stoke-on-Trent South	5.224539028
	Truro and Falmouth	5.224607734
	Stockton South	5.233136166
	East Devon	5.249265614
	Witham	5.252801683
	Carlisle	5.264076112
	Stroud	5.391921135
	Pudsey	5.391930674
	Central Suffolk and North Ipswich	5.422752312
	South Dorset	5.43049381
	Christchurch	5.43088186
	New Forest East	5.434994477
	Stalybridge and Hyde	5.505777196
	Darlington	5.506634433
	South Leicestershire	5.50922014
	West Dorset	5.544730777
	Shrewsbury and Atcham	5.54589674
	Mansfield	5.550131143
	Meon Valley	5.569589264
	Daventry	5.58124667
	Fareham	5.604898261
	Blackpool South	5.608741663
	Sittingbourne and Sheppey	5.620461588
	Skipton and Ripon	5.627304414
	Meriden	5.660272398
	Halesowen and Rowley Regis	5.672304997
	Wells	5.679497479
	North Herefordshire	5.683549456
	Mid Norfolk	5.684094551
	Newark	5.708683304
	Somerton and Frome	5.725882228
	Liverpool, West Derby	5.729149409
	Rutland and Melton	5.761647147
	Gosport	5.822190509
	Shipley	5.833403379
	Suffolk Coastal	5.833594469
	Torbay	5.935222172
	Mid Worcestershire	5.939399073
	Gedling	5.941664055
	Braintree	5.959730172
	Ceredigion	5.961381418
	Swansea East	5.971242674
	Newcastle-under-Lyme	5.978975772
	Yeovil	6.002828166
	Warrington South	6.013175723
	North Dorset	6.070060836
	North Thanet	6.077749853
	Richmond (Yorks)	6.141601663
	Tatton	6.142109697
	Bexhill and Battle	6.169150277
	Walsall North	6.21018769
	Newcastle upon Tyne North	6.233566203
	York Outer	6.299363873
	Faversham and Mid Kent	6.304685143
	Telford	6.361292179
	Worsley and Eccles South	6.391160042
	Harwich and North Essex	6.403422178
	South Basildon and East Thurrock	6.444687571
	New Forest West	6.448238147
	Heywood and Middleton	6.450805629
	Weston-Super-Mare	6.45136545
	Great Yarmouth	6.506162813
	Arundel and South Downs	6.577770467
	Nuneaton	6.638780932
	Stratford-on-Avon	6.651599051
	Tewkesbury	6.685756211
	Southport	6.696097631
	Arfon	6.724118006
	North Wiltshire	6.767834158
	The Cotswolds	6.777680397
	Kenilworth and Southam	6.825676909
	Chippenham	6.828184687
	Eastleigh	6.847334792
	Rushcliffe	6.857407622
	Stafford	6.862631883
	Crewe and Nantwich	6.890026195
	City of Durham	6.937218543
	Saffron Walden	6.992026207
	Taunton Deane	6.994473032
	Stoke-on-Trent North	6.998914336
	Lewes	7.036919448
	Dudley North	7.056317565
	Newport East	7.200996251
	Bury St Edmunds	7.230070902
	North East Bedfordshire	7.231590015
	Buckingham	7.248106684
	Sheffield, Heeley	7.264673785
	Norwich North	7.275162561
	East Worthing and Shoreham	7.289844206
	Hyndburn	7.306419876
	Wealden	7.324507754
	Sheffield, Hallam	7.38059
	Sutton Coldfield	7.395880429
	Dover	7.397049785
	Sunderland Central	7.406517495
	South Northamptonshire	7.410511966
	City of Chester	7.414377117
	Hereford and South Herefordshire	7.437533336
	Tonbridge and Malling	7.455418035
	Grantham and Stamford	7.475740246
	Basildon and Billericay	7.478229844
	Gateshead	7.508517978
	Brentwood and Ongar	7.541121164
	Portsmouth North	7.54631768
	Colne Valley	7.559454584
	Charnwood	7.631823363
	Redditch	7.653021399
	The Wrekin	7.67732993
	Burnley	7.701673578
	Mid Bedfordshire	7.82053715
	Stockport	7.845743117
	North West Hampshire	7.995167647
	Lancaster and Fleetwood	8.020773226
	Witney	8.05123164
	Chichester	8.053729856
	Southend West	8.113946267
	Worcester	8.1230763
	Hastings and Rye	8.136390576
	North East Hertfordshire	8.179585668
	Salisbury	8.184878358
	South West Wiltshire	8.189394483
	Bristol South	8.273645974
	North West Norfolk	8.306000589
	Bury North	8.348047421
	Broxtowe	8.39098251
	Cheadle	8.420948551
	Newport West	8.43666936
	Worthing West	8.445589291
	North East Cambridgeshire	8.457321848
	Kettering	8.460016047
	Birmingham, Northfield	8.465618899
	Cardiff North	8.53099394
	Leeds North West	8.550212248
	Sevenoaks	8.550695165
	Sheffield South East	8.604360834
	Wrexham	8.651277194
	Wakefield	8.716368303
	Poole	8.716742614
	Wantage	8.734484797
	Horsham	8.752844964
	Hertford and Stortford	8.781662621
	South Holland and The Deepings	8.857694125
	East Hampshire	8.868411662
	Devizes	8.92938121
	Bury South	8.953210278
	Hornchurch and Upminster	8.957081462
	South West Bedfordshire	8.969822897
	North East Hampshire	8.971890643
	South Thanet	8.992753623
	Folkestone and Hythe	9.003850069
	Chelmsford	9.066246775
	Henley	9.068416963
	Newbury	9.075178387
	Burton	9.191967371
	Lincoln	9.214362292
	Ashton-under-Lyne	9.242518014
	North Swindon	9.250305114
	Rochester and Strood	9.250410844
	East Surrey	9.325808478
	Solihull	9.335438234
	Scunthorpe	9.351524339
	Ashford	9.4528068
	Altrincham and Sale West	9.45947345
	Harrogate and Knaresborough	9.502240117
	Keighley	9.528564076
	Chatham and Aylesford	9.590773121
	Rotherham	9.611246753
	South West Norfolk	9.660324907
	Leeds West	9.732129388
	Bognor Regis and Littlehampton	9.748763118
	Batley and Spen	9.808246601
	Old Bexley and Sidcup	9.892303407
	Dewsbury	9.902600353
	Oldham East and Saddleworth	9.914272497
	Winchester	9.948305808
	Orpington	9.97099552
	Mole Valley	10.00389338
	Corby	10.06094515
	Tunbridge Wells	10.08946417
	Mid Sussex	10.15966951
	Gillingham and Rainham	10.18820196
	Filton and Bradley Stoke	10.19416952
	Cardiff West	10.19477737
	Kingston upon Hull West and Hessle	10.2449915
	Epping Forest	10.32140003
	Rochford and Southend East	10.3693934
	North West Cambridgeshire	10.55005158
	Wellingborough	10.56528415
	Middlesbrough	10.57689235
	Hitchin and Harpenden	10.59363298
	Plymouth, Sutton and Devonport	10.62078603
	Kingston upon Hull North	10.73903368
	South West Surrey	10.75061331
	Derby North	10.76124119
	Gloucester	10.80281037
	Pendle	10.81473863
	Dartford	10.90310078
	Maidstone and The Weald	10.92175756
	Harlow	10.9219535
	Chesham and Amersham	11.00987748
	Harborough	11.02998152
	Huntingdon	11.03724349
	Halifax	11.05735389
	Bolton North East	11.10947863
	Banbury	11.12543247
	South East Cambridgeshire	11.12747105
	Bradford South	11.21473239
	Nottingham North	11.21622317
	Stevenage	11.2440547
	Boston and Skegness	11.29282876
	Romford	11.29372015
	Cheltenham	11.36201093
	Hemel Hempstead	11.3953817
	Exeter	11.40304534
	Doncaster Central	11.40543116
	Eastbourne	11.43169992
	Stoke-on-Trent Central	11.56021371
	York Central	11.66070967
	Broxbourne	11.71474846
	Rugby	11.71736631
	South Cambridgeshire	11.85170344
	West Bromwich West	11.8969742
	Southampton, Itchen	11.95549542
	Swansea West	11.95641394
	Wythenshawe and Sale East	11.96437717
	Bexleyheath and Crayford	12.02645479
	Loughborough	12.0642891
	Newcastle upon Tyne East	12.14574899
	South West Hertfordshire	12.18034546
	Wolverhampton North East	12.30602793
	Surrey Heath	12.40059078
	Wokingham	12.40975533
	Reigate	12.48896691
	Bracknell	12.53707713
	Warwick and Leamington	12.58595841
	Bristol East	12.66881973
	Liverpool, Wavertree	12.79548857
	Romsey and Southampton North	12.81278332
	Bournemouth West	12.86173309
	Ipswich	12.88313166
	Basingstoke	12.91807104
	Aylesbury	12.99212234
	Stretford and Urmston	13.11709486
	Brighton, Kemptown	13.13246038
	Beckenham	13.19833125
	Cardiff South and Penarth	13.19994416
	Canterbury	13.22108346
	Colchester	13.26120983
	Bristol North West	13.34107074
	Beaconsfield	13.34580981
	Norwich South	13.46953553
	Bath	13.61595336
	Salford and Eccles	13.71123763
	Gravesham	14.0346048
	Spelthorne	14.06096362
	Birmingham, Selly Oak	14.2792624
	Leeds East	14.3772031
	Epsom and Ewell	14.426519
	Sheffield, Brightside and Hillsborough	14.68746208
	Thurrock	14.70990495
	St Albans	14.96882136
	Birmingham, Erdington	15.01360224
	Oldham West and Royton	15.15942933
	Bromley and Chislehurst	15.1974998
	Northampton North	15.19978652
	Maidenhead	15.33359536
	Wolverhampton South East	15.52559057
	Rochdale	15.61894161
	Brighton, Pavilion	15.71920883
	West Suffolk	15.73892799
	Bournemouth East	15.74124834
	Bolton South East	15.85697858
	Hove	15.94839253
	Preston	16.1437012
	Coventry North West	16.15017051
	Portsmouth South	16.22766675
	Huddersfield	16.53584621
	South Swindon	16.63245563
	Aldershot	16.84436404
	Guildford	16.96025443
	Hertsmere	16.98673411
	West Bromwich East	17.07599682
	Windsor	17.27207873
	Esher and Walton	17.4019473
	Welwyn Hatfield	17.49435237
	Liverpool, Riverside	17.51914375
	Milton Keynes South	17.62043095
	Manchester, Withington	17.68636858
	Carshalton and Wallington	17.71154613
	Reading West	17.81783064
	Birmingham, Yardley	17.87929322
	Oxford West and Abingdon	17.9761287
	Runnymede and Weybridge	18.03325156
	Walsall South	18.07537245
	Leeds North East	18.0881711
	Blackburn	18.6207411
	Cardiff Central	18.79519166
	Wycombe	18.97825081
	Northampton South	19.21593762
	Woking	19.27269293
	Milton Keynes North	19.43217458
	Wolverhampton South West	19.6071273
	Birmingham, Edgbaston	19.69596554
	Chingford and Woodford Green	19.74384281
	Croydon South	19.81816406
	Derby South	20.03828856
	Crawley	20.22008124
	Dagenham and Rainham	20.2213733
	Eltham	20.3834713
	Southampton, Test	20.850361
	Twickenham	20.99962568
	Leeds Central	21.27757249
	Newcastle upon Tyne Central	21.53949601
	Sutton and Cheam	21.9575213
	Watford	22.04674004
	Nottingham South	22.14349144
	Sheffield Central	22.40293536
	Bedford	22.654503
	Coventry South	22.65739697
	Bristol West	22.76168479
	Warley	22.94009826
	Bradford East	22.94060798
	Leicester West	23.02806963
	Uxbridge and South Ruislip	24.11551419
	Reading East	24.29729581
	Coventry North East	24.38490286
	Ruislip, Northwood and Pinner	24.54756925
	Peterborough	24.62092987
	Nottingham East	24.68026827
	Croydon Central	25.82363454
	Blackley and Broughton	26.31959117
	Luton North	27.05893054
	Kingston and Surbiton	27.10547279
	Enfield North	27.21609269
	Oxford East	27.57383704
	Lewisham West and Penge	27.6555999
	Birmingham, Hodge Hill	28.79896119
	Chipping Barnet	29.17489038
	Cambridge	29.49189472
	Richmond Park	29.77680023
	Birmingham, Perry Barr	29.79549911
	Lewisham East	29.95127488
	Manchester Central	30.22720843
	Erith and Thamesmead	30.62795617
	Ilford North	30.79082553
	Birmingham, Hall Green	31.77802319
	Dulwich and West Norwood	32.30446346
	Bradford West	32.37598139
	Manchester, Gorton	32.53835501
	Luton South	33.07133781
	Barking	33.59904507
	Leicester South	33.78825857
	Enfield, Southgate	34.26772398
	Battersea	34.4179029
	Islington North	34.55431095
	Tooting	34.58695856
	Wimbledon	34.99766585
	Greenwich and Woolwich	35.77529566
	Islington South and Finsbury	36.17129052
	Hornsey and Wood Green	36.68419671
	Putney	37.04976659
	Hackney North and Stoke Newington	37.98306726
	Streatham	38.86184657
	Lewisham, Deptford	38.91621686
	Slough	39.23967534
	Hackney South and Shoreditch	40.16695705
	Holborn and St Pancras	40.23163917
	Mitcham and Morden	40.25731379
	Hayes and Harlington	40.27040033
	Birmingham, Ladywood	40.28951876
	Bethnal Green and Bow	40.60757393
	Croydon North	40.76401752
	Camberwell and Peckham	40.79025123
	Vauxhall	40.945165
	Bermondsey and Old Southwark	41.78403756
	Finchley and Golders Green	42.37612762
	Brentford and Isleworth	42.87314478
	Edmonton	42.96040479
	Walthamstow	42.98823508
	Leyton and Wanstead	43.06748702
	Chelsea and Fulham	43.25950595
	Leicester East	43.26483598
	Feltham and Heston	43.6368131
	Hendon	44.13068939
	Hammersmith	44.58878853
	Poplar and Limehouse	45.34545031
	Hampstead and Kilburn	45.89234474
	Ealing North	46.49471173
	Ealing Central and Acton	46.50599988
	Ilford South	46.62571069
	Harrow West	46.63370614
	Harrow East	46.91550775
	Cities of London and Westminster	51.87636364
	West Ham	51.93749921
	Tottenham	52.2002213
	Kensington	52.26049194
	Ealing, Southall	52.38221687
	Westminster North	53.51928133
	Brent Central	54.2237227
	East Ham	55.54050266
	Brent North	59.26652346
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	<p>
	<h1>Support for UKIP and Immigration Levels</h1>
	</p>
	<div class="text">

	We no longer widely dismiss UKIP or their supporters as bigots. Instead, politicians
	and the media have started to treat the phenomenon of UKIP as a manifestation
	of the real concerns of people about "the pressure immigration puts on public
	services", among other things. The leader of the Labour Party went so far as to
	say that UKIP supporters' migration concerns are <a href="http://perma.cc/GTF2-GZEJ" target="_blank">
	'based on reality, not prejudice'</a>. If this were the case, we would
	expect support for UKIP to be higher in areas where there were higher levels
	of immigration, as these would be the areas where immigrants were putting pressure
	on local services.
	With the 2015 general election approaching, and UKIP claiming a lot of attention,
	results from the last general election were tested against this hypothesis. Two maps
	of English parliamentary constituencies were created, one (on the left)
	showing support for UKIP, and the other (on the right) showing the percentage
	of the population that was born outside the UK. Each constituency was coloured
	either white (representing 0) or purple (representing the maximum value) or somewhere
	in between on a linear scale from 0 to the maximum.

	</div>
	<div id="map" class="map"></div>
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	<br>
	<div id="key" class="key"></div>
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	<div class="text">

	The data are drawn from the results of the general election in 2010 (pulled from the
	Guardian <a href="http://perma.cc/9U8B-LX8L" target="_blank">
	website</a>) and the 2011 census (pulled from the
	<a href="http://perma.cc/GTF2-GZEJ" target="_blank">
	Migration Observatory at the University of Oxford</a>). They do not seem to support
	the idea that UKIP gained higher vote shares in areas that have the highest concentration
	of immigrants. If they did, the darker purple patches on the left would be mirrored
	by darker purple patches on the right. In fact, some of constituencies which showed
	the greatest support for UKIP, such as Buckingham, Staffordshire Moorlands, Boston and
	Skegness and Christchurch, have relatively low levels of immigration and appear in a
	lightish purple on the right map. On the other hand, some of the constituencies with the
	highest concentrations of foreign-born residents have very low levels of support for
	UKIP: if high immigration puts pressure on local services, turning disaffected voters
	towards UKIP, why would only 0.73% of voters in Brent North (where the concentration of
	foreign-born residents is highest at 59.27%) vote for UKIP?

	</div>
	<div id="corbox">
	</div>
	<div class="text">
	Plotting votes for UKIP against foreign-born population in each constituency (above) we
	actually observe a weak negative correlation between immigration and UKIP support. The 34
	constituencies where UKIP did not field a candidate were excluded, though the average
	percentage of the population born in another country in these constituencies was
	18.51, compared to 12.84 in England as a whole. Assuming that the decision to field a
	candidate was based on the perceived chance of success, this lends further support to
	the idea that UKIP are more successful in areas with lower immigration.
	It is hardly the first time that it has been pointed out that the rise of UKIP is not
	just about immigration. Nor is it the first time that the claim that immigration will
	ruin public services has been refuted. Services, after all, are paid for by taxes, and
	immigrants pay taxes and actually make <a href="http://perma.cc/4K4Z-MMGS" target="_blank"> a positive net
	contribution to the budget</a>.
	But the fact that higher levels of immigration in a constituency
	actually make it less likely for those who live there to vote for UKIP shows centrist
	parties' increasingly xenophobic rhetoric to be particularly disingenuous.
	</div>
	</div>

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