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MAPPING THE 2012 PRESIDENTIAL ELECTION
(Lilia) Iman Salehian ID: 604-001-502 Shin | Ward, D. Geog 7, Lab 1G Assignment 4 / Week 4
In an ideal world, a United States election map would read as little more than a homogenous canvas of purple—red and blue united into a common front, void of political quibbles. A few seconds worth of any Fox or CNN news channel, however, pierce this utopian fantasy and reveal a stark truth: the United States is a nation of deep political divide. The choropleth maps below serve to illustrate the Republican/Democrat voting binary using the state and county results of the 2012 Election between Democrat Barack Obama and Republican Mitt Romney. Though a cursory glance at the map reveals it to be swathed in red—with Romney dominating in terms of area— understanding the US’ system of electoral voting accounts for Obama’s ultimate triumph. Using an electoral college, rather than impersonal or reductive factors such as area, the United States election process hinges on acquiring 270 votes (Spillius). Thus, Obama, by winning key states such as California was able to secure his second term. * * * A) At a state level, the results illustrate a strongly polarized country. The entirety of the West Coast and North East regions voted Democrat, while nearly every state (with the exceptions of Colorado and New Mexico) voted Republican. These general trends rely upon a bevy of demographic issues, ranging from socio-economic status, to race (McNown), but from a distanced, state-level perspective, the results seem to encourage generalizations. While those states in the mid-west and south that are home to larger populations of white, conservative Americans tend to vote Republican, the liberal coasts expectedly voted Democrat. At a county level, however, the maps become far more nuanced. While the Central US is still decidedly red, and the coastal regions generally blue, the neat binaries established at the state level are completely destabilized. Running population queries indicates once more that population size—as opposed to geographic distribution—is what matters. For instance, looking at Nevada’s county voting trends at the county level, one finds a generally ‘pink’ state. With two key counties voting ‘sky blue,’ however, the entire state’s average was tipped in Obama’s direction (see: Query Quiz, question 1a,b,c for specific population results). Instances such as these inform us that US voting, in direct contrast to Figure 2, is not a black and white issue, but rather one dependent on a multitude of factors—including population concentrations and electoral voting. Explaining the two most obvious outliers (CO and NM), however, introduces a factor specific to population trends: the effects of immigration. Analyst Ruy Teixeira, describes of Colorado: The share of minority eligible voters has grown by over three points—almost entirely from Hispanics—and there has been a roughly equal decline in the share of white working class eligibles, by far Obama’s worst group.
The rapid growth of this population within US will undoubtedly effect greater changes at the county level, as minorities increasingly emigrate to suburban communities (Frey, 2012), and may continue to effect change within states as a whole. B) As was suggested in the above comparison of state and county maps, unit of analysis makes a monumental difference in both research and visualization. It is mostly an issue of granularity. Working with data that use states as their units of analysis, one is forced to acknowledge the ‘bigger picture,’ driving straight to trends that span the nation as a whole. Visualizing this data, the state level maps, with their binary color schemes, allow for quick-
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and-easy readings of state elections across commonly recognized state borders. Analyzing data at the county level, however, beneficially disrupts the fiction of state homogeneity, allowing for more micro-level analysis of voting both within the states themselves, and more accurately across the United States. C) Though the “Red State vs. Blue State” battle is given significant media attention during election times, genuinely reflecting upon the efficacy of that labeling system and comparing it to detailed county maps, it is difficult not to question whether the abstraction is detrimentally reductive. While Fig. 1 and Fig. 2 paint divisive images of America, research argues “the literature indicates that the American public as a whole is no more polarized today than it was a generation ago, whether we focus on general ideological orientations or positions on specific issues” (Fiorina). I fear that offering Americans this reflection of their nation risks cementing further polarity, when basic comparisons between state maps and county maps (Fig. 3,4) seem to argue that the political divide is, in fact, not as grave as one may imagine. Recognizing the ease with which our eye makes the distinction between the colors Red and Blue, I chose to apply a single color gradient to the same data (Fig. 4), an exercise that proved especially telling. While Fig. 3 makes an obvious political argument, Fig. 2 presents pure data. Without state lines or popularly politicized colors, viewers are unable to make on-the-fly assumptions about the information at hand. As Harrower and Brewer emphasize in their report on Colorbrewer, color plays an enormous role in the manner in which we perceive geographic visualizations, and is a tool that must be wielded with caution. While cogent visualizations are helpful addendums to thorough reporting, it is essential for their consumers to recognize what information is being left out. This process that demands cartographic education and conscientiousness, something many simply neither have the time nor interest to pursue. While recognizing the utility of choropleth maps and their centrality to geographically visualizing presidential election data, I would go so far as to suggest that, given how voting processes work within the US, a reconceptualized visualization linking graphic area and color to population and electoral vote amounts would be a great means of simultaneously educating visualization consumers on both the election process and its results.
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Fig. 1
Fig. 2
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Fig. 3
Fig. 4
QUERY QUIZ: Exploring State and County 2012 Election Data 1a. What is (to the nearest tenth) the average total population of Nevada’s counties? (158,856.0) 1b. Of the counties in Nevada that supported Romney? (21,858.3) 1c. Of those that supported Obama? (1,186,338.0) 2. What is the average amount (to the nearest tenth) of electoral votes states that have BOTH the letters in the greeting “Hi”? (12.3) 3. What is the difference between the most populated county in the United states and the least? Provide their respective names. (9,818,523; Smallest total population: Loving, Texas; Largest total population: Los Angeles, California) 4. How many county names begin with the prefix “Mc”? (32) And which, of these counties, is the furthest west? (McKinley) 5. How many states are located in the “Mtn” sub-region of the United States? (8)
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BIBLIOGRAPHY Fiorina, Morris P., and Samuel J. Abrams. "Political polarization in the American public." Annu. Rev. Polit. Sci. 11 (2008): 563-588. Frey, William. “The 2010 Census: America on the Cusp.” The Milken Insitute Review, (2012): 47-58. Dorling, Daniel. "Map design for census mapping." Cartographic Journal 30.2 (1993): 167-83. Harrower, Mark, and Brewer, Cynthia. "ColorBrewer. org: an online tool for selecting colour schemes for maps." Cartographic Journal, The 40.1 (2003): 27-37. McNown, Robert. “Economic and Demographic Determinants of the Electoral Vote for President.” Institute of Behavioral Science. 2008. "President Map." The New York Times. N.p., 2012. Web. 24 Oct. 2013. Spillius, Alex. "US Election 2012: The Electoral College Explained." The Telegraph. N.p., 6 Nov. 2012. Web. 24 Oct. 2013. Teixeira, Ruy. “New Data on Obama’s Massive Demographic Advantage.” New Republic. 9 July 2012.
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