The New York Timesmaps the increasing number of so-called landslide counties—counties where a candidate won by 20 or more percentage points. “The proportion of voters living in landslide counties has steadily increased since 1992, a trend that reflects the growing tendency of like-minded people to live near one another, according to Bill Bishop, a co-author of ‘The Big Sort,’ a 2008 book that identified this phenomenon.”
Bad Hombres, China and Trump Supporters
For all of Donald Trump’s rhetoric about illegal Mexican immigration and competition from China, his supporters don’t seem to be much affected by either. That’s the conclusion of a study by Raul Hinojosa Ojeda of UCLA’s Institute for Research on Labor and Employment. “[A]n examination of the geographical concentration of support for Donald Trump in the presidential primaries indicates a negative correlation between the number of Trump supporters and the population size of Mexican immigrants, as well as a negative correlation between Trump support and import competition from Mexico or China. […] In fact, only 2% of U.S. counties in the U.S. actually fit the Trump narrative of very high Trump support combined with very high levels of immigration or trade.” [CityLab]
The Mysterious Blue Curve
Geographical magazine explores what they call the “mysterious blue curve” —a narrow swath of Democratic support across the centre of the Deep South. I’ll save you a click: it’s where the African-American voters are concentrated. Geographical, though, goes a bit further back—to the fricking late Cretaceous—to explain why the soil in that area was so amenable to growing cotton, an activity that brought so many slaves to the area in the first place.
Felony Convictions and Voting Rights
Cards on the table: I live in a country where prisoners have the right to vote even while in prison, so the American practice—in 48 of 50 states—of not allowing ex-convicts to vote even after release is both alien and upsetting to me. The New York Times maps the impact of that practice, both in terms of how many people in each state can’t vote due to felony convictions, and in terms of how many African-American adults can’t vote—1 in 13!—because of same. When, as the Times says, “[a] black person is more likely to be convicted of a felony than a white person who committed the same crime,” this has the smell of systemic, targeted disenfranchisement to me.
The white underlying geographic map places states in their familiar size, shape and location, allowing them to be identified quickly. Using a cluster of dots rather than a solid fill to represent the outcome ensures that the amount of red and blue on the map accurately reflects states’ weight in the election outcome, rather than the (irrelevant) surface area.
Like the tiled grid cartogram, the number of electoral votes in each state is easy to compare visually without counting or interpreting numbers printed on the map. Because each electoral vote is a discrete mark, it is possible to accurately represent the split electoral votes that are possible in Maine and Nebraska, or the possibility of a faithless elector.
Before we’re inundated by the results from the 2016 U.S. presidential election, here are a couple of looks back at the 2012 election that explore the results from slightly different angles.
This map shows the county-by-county results but the intensity is by raw vote totals, not percentages: the darker the colour, the more actual votes there are. It’s an attempt to compensate for counties of different sizes, but you still end up with distortions if the county is both large and populous. [Maptitude]
Most Democratic strength is in the cities; most Republican strength is in rural areas. This map depicts the opposites: the urban counties won by Mitt Romney in 2012 and the rural counties where Obama won. [Maps on the Web]
Today, print subscribers to the New York Times were treated to a fold-out map showing a choropleth map of the 2012 election results at the ZIP code level (above). “The map is part of a special election section that aims to help explain the political geography of the United States — identifying where people who are conservative and liberal live and pointing out how physical boundaries, like the Rio Grande and the Cascade Mountains, often align with political ones,” writes the Times’s Alicia Parlapiano.
Parlapiano’s piece is in fact a lengthy tutorial on how to read election maps, along the lines of the pages I linked to in last week’s post on election map cartography—it outlines the problems of state-level election maps and choropleth maps that privilege area over population, for example, and shows some other ways of depicting the results.
The map may not look advanced today, but in 1883 it broke new ground by enabling Americans to visualize the spatial dynamics of political power. Readers responded enthusiastically. One reviewer pointed to the Republican counties in Arkansas—something left invisible on a map of the Electoral College returns—and wondered what other oddities of geography and history might be uncovered when election returns were more systematically measured. In other words, the map revealed spatial patterns and relationships that might otherwise remain hidden, or only known anecdotally. Perhaps its no coincidence that at the same time the two parties began to launch more coordinated, disciplined, nationwide campaigns, creating a system of two-party rule that we have lived with ever since.
(This map also inverts the modern colours for the two main U.S. political parties: here the Democrats are red and the Republicans are blue. Those colours were standardized only fairly recently.) [Geolounge]
For other ways of mapping election results, see this gallery of thematic maps, which includes things like 3D choropleth maps, dot density maps, and all kinds of variations on cartograms and choropleth maps. There’s more than one way to map an election. [Andy Woodruff]
Earlier this month FiveThirtyEight built a county-by-county model showing where both Hillary Clinton and Donald Trump’s “upside potential” — by which they meant where they would each benefit from the shifts in the electoral landscape. Compared to 2012, Clinton is underperforming with non-college-educated whites and Trump is underperforming with Asians, African-Americans, Latinos and college educated whites.
To get a handle on how these shifts could affect the electoral landscape, we modeled how many of Romney’s votes came from college-educated whites and minorities and how many of Obama’s votes came from non-college-educated whites in each state, county and congressional district. The difference between these two vote totals, shown in the map above, can tell us where Clinton and Trump have the most potential to build on 2012.
The authors went on to game out what that might look like in terms of the electoral vote if one in five voters in those shifting groups switched allegiances.
A pronounced gender split is emerging in the 2016 U.S. presidential election. Based on national polls in October, Nate Silver writes, “on average, Clinton leads Trump by 15 percentage points among women while trailing him by 5 points among men. How would that look on the electoral map?” Silver does a quick-and-dirty estimation by adding or subtracting 10 points to/from the FiveThirtyEight forecast. Moving 10 points to Clinton’s column approximates what the electoral map would look like if only women voted:
Moving those 10 points to Trump’s column approximates the results if only men voted:
You’ve almost certainly seen these maps make the rounds of social media. This is where they came from and how they were made.
Land does not vote and we can’t judge gerrymanders simply based on geometry. Districts aren’t just abstract shapes on a map, but collections of actual people and voters. Ultimately, the outcomes produced by a particular map matter far more than a map’s appearance. Comparing the actual congressional districts to plausible alternatives in Maryland and other states demonstrates both how gerrymandering is more complex than merely grotesque shapes, and that Maryland is far from the worst partisan gerrymander nationwide.
On Cartastrophe, Daniel Huffman points out the problems in Decision Desk HQ’s interactive cartograms for the U.S. presidential primaries, which maintain a state’s shape but resize the counties as the results come in. “Unfortunately, in so doing, they shuffle the counties around any old which way. The Lower Peninsula of Michigan has 68 counties in reality, the Upper Peninsula has 15. But Decision Desk HQ has shoved most of the counties into the Upper Peninsula, which now has 58, vs. 25 that remain in the Lower Peninsula,” Huffman writes. “This means that we can’t really see spatial patterns, which is sort of the point of having a map.” [via]
There was a time, not too long ago, when our Super Tuesday map would have been impossible to put together and display. Even earlier in the digital era, a complete vote-totals map wouldn’t have been available until every ballot was counted at the end of the night. (Not to mention that in the print-only era, no map would be available until two days after the vote, and then often only in black and white.)