The maps above—and throughout this article—show their estimates of partisanship down to the individual voter, colored by the researchers’ best guess based on public data like demographic information, voter registration and whether voters participated in party primaries.
We can’t know how any individual actually voted. But these maps show how Democrats and Republicans can live in very different places, even within the same city, in ways that go beyond the urban-suburban-rural patterns visible in aggregated election results.
It goes beyond racial, urban vs. suburban vs. rural and house vs. apartment splits, to the point where researchers are wondering whether Americans are “paying attention to the politics of their neighbors” when they decide where to live. This has implications not only in terms of electoral targeting (e.g. gerrymandering, voter suppression), but in terms of basic social cohesion.
The maps are based on research by Jacob R. Brown and Ryan D. Enos published earlier this month in Nature Human Behavior.
Kenneth Field has released a dasymetric dot density map of the 2020 U.S. presidential election results. One dot equals one vote. “Data at a county level has been reapportioned to urban areas. Dots are positioned randomly.” It’s in the same vein as his 2016 map, which went all kinds of viral when he posted it in early 2018. A high-resolution downloadable poster is here; an interactive version is here.
It tries to address something that I find frustrating about election maps: Very few of them do a good job of showing where voters are. […] There are more Trump voters in California than Texas, more Biden voters in Texas than New York, more Trump voters in New York than Ohio, more Biden voters in Ohio than Massachusetts, more Trump voters in Massachusetts than Mississippi, and more Biden voters in Mississippi than Vermont.
Mapbox is holding an election mapping challenge. Entrants are asked to create, using the Mapbox basemap and compatible tools and platforms, “an original, publicly viewable interactive map, map-based data visualization, or application that uses location tools and focuses on an elections-related theme.” Entries are due November 8, and must be accompanied by a public blog post explaining the project.
Kenneth Field’s virtual talk on the cartography of elections, given to University of South Carolina students on 25 September 2020, is now available on YouTube. “It explores the way in which map types and their design mediate the message, and using examples from elections shows different versions of the truth.” Also includes material from Ken’s forthcoming book.
The pattern we observe here is consistent with the urban-rural divide we’re accustomed to seeing on traditional maps of election results. What spans the divide—the suburbs represented by transition colors—can be crucial to winning elections. […] At each extreme of the political spectrum, the most Democratic areas tend to be heavily developed, while the most Republican areas are a more varied mix: not only suburbs, but farms and forests, as well as lands dominated by rock, sand or clay.
This is a generalization, to be sure, but so are most political maps, and the notion that urban areas tend to vote Democratic while rural areas tend to vote Republican isn’t what I’d call a revelation. Still.
Researchers have released an interactive map showing Canadians’ opinions about climate change—whether it’s happening, and what we should do about it—and, more significantly, the regional variations in that opinion, down to the riding level. Not surprisingly, the oil- and coal-producing regions are much more likely to be climate skeptics.
The map is based on surveys of more than 9,000 Canadians taken between 2011 and 2018, which raised my eyebrows a bit: public opinion can change a lot over seven or eight years, after all. But the researchers did so to get a more accurate sense of regional opinion: opinion polls are usually based on a small national sample; regional breakdowns of that sample have large margins of error, and getting accurate regional samples would be a lot more expensive. More at Global News.
Bothered by the widespread use of Web Mercator by Canadian news outlets to show last week’s election results, Kenneth Field has posted an article that aims to address the problem. Static maps of Canada tend to use a conic projection like the Albers or the Lambert, and that’s the case for print election maps as well. Online interactive maps, on the other hand, use off-the-shelf tools that use Web Mercator, which results in the sparsely populated territories looking even more enormous. But that doesn’t have to be the case, says Ken, who shows us, with a few examples, how use ArcGIS Pro to create interactive maps using a conical projection.
Meanwhile, Mark Gargul writes in response to Ken’s critique of his cartogram of the election results. Mark describes himself as an amateur and readily admits that other cartograms are “clearly more aesthetically pleasing. On the other hand, I was going for something different with my cartogram—specifically, to try to preserve riding-adjacency as much as possible.”
@kennethfield … On the other hand, what I was going for was preserving, to the extent possible, riding adjacency. If Markham-Stouffville shared a border with Markham-Unionville on a real map, I wanted that border on the cartogram. Hence, the ugliness.
The other thing Mark was going for in his cartogram was to indicate the urban-rural split: metropolitan areas are given a black border: it’s easy to see which ridings are in Montreal or Toronto; seats that are partially urban and partially rural straddle those borders.
I'll summarize for you guys what I let Ken know in more detail: I wasn't going for pretty, but I was going for illustrating the rural-urban split, which doesn't come across well in the other cartograms or maps I have seen
Speaking of the Mercator. Maps Mania’s roundup of Canadian election results maps notes that the Canadian media’s interactive maps (e.g. CBC, Global, Globe and Mail) invariably resorted to Web Mercator, largely because of the mapping platform used. (In-house infographics team? Don’t be ridiculous.) Web Mercator is singularly bad for Canadian election maps, because Nunavut: it’s the largest electoral district by area (1.9 million km2) and the smallest by population (31,906). It’s enough of a distortion on the Lambert: Mercator makes it worse.
As for cartograms, Ken hated the one I posted last night; Keir points to Luke Andrews’s Electoral Cartogram of Canada, which is a bit nicer, and uses only one hexagon per riding instead of seven. Keir also points to this animation that shifts between a geographical map and a cartogram. It’s hard to recognize Canada in cartograms, because it’s difficult for us to grasp just how many people live in southern Ontario.
This cartogram shows the seat-by-seat results of the federal election held last Monday in Canada. It was uploaded to Wikipedia by user Mark Gargul to illustrate the 2019 Canadian federal election article, and it’s a welcome departure from the usual election results maps in this country.
Canadian election results maps generally use geographic maps, usually the Lambert conformal conic projection that most maps of Canada use (though sometimes it’s the Mercator!) rather than cartograms. Which means that Canadian maps suffer from the same “empty land doesn’t vote” problem that U.S. maps have, though it’s mitigated by the fact that vast rural and northern seats are often won by different parties: you don’t have the same sea of one colour that you get in the States.
That said, Canada is overwhelmingly urban, and so are its electoral districts. Most election results maps resort to using multiple inset maps to show the urban results. (Elections Canada’s map has 29 of them.) Gargul’s cartogram sidesteps both problems neatly; on the other hand, it’s next to impossible to find your own damn constituency (it’s hidden in the mouseover text). If the disadvantage of empty-land election results maps is that the colours aren’t representative, their advantage is that you can tell what regions voted for whom, at least if you know your geography.
So Trump is a serial map-abuser. These three examples clearly show how he uses the map for dominance and to assert his apparent power and possession. This is Trump’s America. He’s simply the latest in a very long line of leaders, politicians, dictators and many others to use maps to try and illustrate a version of the truth that has been cartographically mediated to suit a partisan purpose. Like I said, it’s not wrong to use maps to tell a certain story (apart from when the facts are clearly manipulated which is stretching truth to the realms of plain lies) but it is a case of “reader, beware.”