Safe and Sound: a Carolinian Salamander!

The last few weeks I’ve devoted my time to a new geographic and cartographic project.

The project’s objective is to identify characteristics of “safe” districts for the Democratic and Republican parties in the United States. There are two sub-questions: where are these safe districts located (if they exist at all) and; what are their significant characteristics? In terms of parameters for the study. I shall only be using results from the 2010 Congressional election (for the 112th Congress, 2010-2012), though I’d prefer a longitudinal approach – digitizing the necessary data from the one election took some time. Within that election, I will be examining results for the House of Representatives, since this body (theoretically) rolls over every two years and the seats are proportional representations of population. My hope is that the results are more applicable to district characteristics than a similar study of the Senate, since that chamber’s seats are tied to perspectives and politics at a state-level rather than a more local level. To be explicit this is the previous Congress, which sat from 2010 to 2012.

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Results for the 2010 election to the House of Representatives (via ME!)

The map above is one depiction of the House results from the 2010 election. It shows potentially “safe” districts (which I defined as over 70% of the available votes going to either the Republican or Democratic party) in the darkest colors, green for Republican, purple for Democratic. It also shows “strong” districts (defined as over 60% of the vote) in a lighter tone of the same colors. By the numbers: 51 districts were “safe” Democratic and 51 were “strong” Democratic. 56 were “safe” Republican and 94 were “strong” Republican. Before you get too excited, keep in mind that the House of Representatives is a proportional body based on population. Though the Republican safe districts are geographically larger, the districts more (or less) contain the same numbers of people. Thus giving rise to the common observation that urban areas vote Democratic and more rural locales (with their more diffuse across geographic space populations) vote Republican. That is common knowledge… right?

No? Well, a cursory map analysis elicits a few observations. First, the Democratic Party is hardly a “coastal” phenomenon and Republican strongholds are hardly limited to the American South and Midwest. While this isn’t news to anyone who 1) lives in these areas, 2) has a brain, 3) is a Geographer, one would be surprised by the number generalities made by U.S. media outlets, so-called pundits, and others. Second, some of us thought (myself included) that gerrymandering was dead. I’m happy (because it gives me something to write about) and sad (for the same reason) that its not.

Political Geography in North Carolina (via ME!)

Political Geography in North Carolina (via ME!)

Meet North Carolina’s 12th Congressional district or the Carolinian Salamander (Caroliander?). Over 60% of the voters in this Congressional district voted for the Democratic Party candidate in the 2010 election. Without a map this statistics does not mean much. We see that four strongly Republican districts on the border (two of which voted over 70% for Republican candidates) and the, rather odd, shape of the district itself is… telling.

Initially I was going to report some demographic characteristics of these districts but since I’ve only done a very limited, cursory analysis (commonly referred to as “eye-balling”) I shall spare you my musings. Suffice to say though, with the appropriate caveats, that there is likely to be some interaction between race/ethnicity and income with the House of Representative electoral outcomes (in North Carolina) in 2010. More explicitly, I think that these districts are shaped to promote these electoral outcomes. Of course, much more research needs to be done on the method and manner in which electoral districts are demarcated in North Carolina.

The above should serve to dispel some misconceptions about U.S. politics. First, there’s really no red-state/blue-state binary. Most states include areas considered strong or safe Democratic or Republican holds, with the notable exceptions of the states with only one representative (Vermont, Montana, and so on). Second, gerrymandering! Taken together, these observations give credence to the idea that the potential spatial concentration of safe districts, say the safe and sound Republican Congressional districts of North Carolina, or Texas, deserve closer scrutiny.

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Geopolitical Cartoons: Depictions of the Spanish-American War (1898)

This weeks geopolitical cartoons is brought to you by William Randolph Hearst! Well not quite, I’m pretty sure Hearst would balk at my political tendencies. However, the cartoons do stem from the conflict that he assisted in creating, the Spanish-American War. In this post we’ll explore some of the not-very-subtle propaganda messages in various geopolitical cartoons. Know your sources!

The first image below comes from a satirical German newspaper first published in 1848 (according to wikipedia) and printed the day before hostilities ensued, or were declared, or when scholars agreed the war started (published April 24, started April 25). Coming from a German perspective, its primary focus is on the effects of the impending conflict on “poor Cuba.” The caption reads “this encounter does not seem, at present, exactly a happy one for poor Cuba.” Indeed, as the picture shows Cuba is being ground underfoot by Uncle Sam (the United States who is strolling over to the Caribbean island via Florida) and Don Quixote (Spain who is stretching across the Atlantic from Spain). Quite clearly, the Germans are making a call on who is going to win the conflict. Who would you bet on? A modern Uncle Sam walking over? Or an insane Spanish minor noble, armored and armed with lance in the late-1800s, with a penchant for charging windmills, accosting monks, and generally not following up on his deeds?

“Poor Cuba”, 24 April 1898 (via Ohio State University)

The Spanish, of course, saw things rather differently. The cartoon is apparently from a Catalan source and depicts a greedy Uncle Sam hungrily eyeing Cuba from the United States. His groping hands are hovering over the island. Though I have no idea what “fatlera” means, wikipedia tells me that the caption reads “Protect the island so won’t be lost.” Righteous nationalistic fury indeed! But I have to agree with a comment made in a Blue Sky GIS post, “Spain complaining about anybody else’s imperial ambitions is very much the pot calling the kettle black.” Couldn’t have said it better myself!

Greedy Uncle Sam, 1896 (via wikipedia)

The next two images are from the U.S. The first, from the Minneapolis Tribune, depicts President McKinley holding onto a savage-looking child, the Philippines. He is contemplating whether to “keep” the archipelago, “return” it to Spain, or setting it on his own path. The editors at the Minneapolis Tribune clearly believe that President McKinley should keep the islands. After all, handing them back to Spain is akin to throwing the child off of a cliff. Moreover, it is just a savage child after all, hardly ready for independence. As the world looks on, history is made. McKinley holds on to the Philippines. The aftermath is for another post.

McKinley and the Philippines, 1898 (via wikipilipinas)

The final poster is from the 1900 election campaign season, which McKinley/Roosevelt subsequently won for the Republicans. The poster compares the effects of four years of party rule in 1896 (after four years of Democratic rule under Grover Cleveland) and in 1900 (after four years under McKinley and the Republicans). Two things worth drawing attention to from the geopolitical standpoint. First, is how the United States justified (and continues to justify) its foreign intervention “the American flag has not been planted in foreign soil to acquire more territory but for humanity’s sake.” I wouldn’t be the first person to suggest that Americans are uncomfortable with the sort of power they wield. As a society we take pains to justify our adventures abroad, yellow journalism and yellow cake. When the conflict is said and done, and righteous American power is in place, the shining city upon the hill bring the light of liberty, we have the the last two pictures in the campaign poster. Cuba is compared under Spanish rule and under America’s rule. I think these two messages are one of the most interesting omnipresent debates in American foreign policy. The isolationist trend, content to guard its power and prosperity while the world goes to shit, and the righteous, liberty-exporting revolutionary trend.

Liberty under McKinley, 1900 (via wikipedia)

Book Review: No Dig, No Fly, No Go (Mark Monmonier)

Feeling under the weather (aren’t we always?) so I offer you a book review written in 2012 for an assigned reading:

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Monmonier, Mark. No Dig, No Fly, No Go: How maps restrict and control. 2010. Chicago, U.S.: University of Chicago Press.

In No Dig, No Fly, No Go, Mark Monmonier builds on his earlier 1996 work, How to Lie with Maps, by providing an in-depth look at one aspect of cartography the realm of so-called “prohibitive cartography.” In the book, Monmonier critically examines maps from the perspective of how they restrict and control, but provides his analysis in a language that is accessible to the layperson (in this case the non-academic Geographer). While I find Monmonier’s book refreshing and occasionally insightful, I remain wanting.

At the most basic level, Mark Monmonier explores how maps influence human behavior. More specifically, he seeks to answer how maps restrict access, mobility, and the use of spaces and places. From this standpoint alone, Monmonier’s work should be required reading for cartographers and political geographers from the undergraduate level. If we (partially) define Geography as the study of human interaction with the environment than Monmonier’s book becomes immediately important, for its subject is how maps, or rather authorities, attempt to regulate humans’ interactions with their environment. Primarily, Monmonier’s sources include news articles, legal cases, and maps (naturally). The first two provide historical and contemporary context for the various aspects of prohibitive cartography. For the most part, these sources work well for his overall purpose, which is to weave a narrative of how maps influence, and influenced, our lives at various times and at a variety of scales.

Monmonier loosely organizes the book around the concepts of theme, scale, and time. Each chapter examines a different theme of “prohibitive cartography.” Monmonier, after an introduction as to why boundaries “matter,” begins with a historical look at how maps played a role in delineating plots of land in the United States. He then takes a smaller scale look at this same theme with a look at how international states maintain their territorial integrity through maps and how maps affect governments’ view of their integrity. The following chapter takes this point to the colonial period, examining how maps justified the creation of colonies or partitions during peace. Likewise, Monmonier than examines the affects maps had on delineating maritime boundaries and exclusive economic zones. Moving back to the intra-state scale, Monmonier first examines how boundaries are set at the local and provincial (state) levels in the United States. In “Divide and Govern,” Monmonier also introduces political gerrymandering, which then forms the basis of the next chapter. An interesting discussion in this chapter is Monmonier’s suggestion of improvements to U.S. congressional districting. Following this deeper look at how politicians can utilizes maps to influence voting outcomes, Monmonier then examines how map-makers can utilize maps to influence where we do business, through the processes of redlining and greenlining. The next two chapters follow the theme of economics at the local level through discussions of zoning and rezoning plans and how maps influence changes (or not) in the built landscape, whether by rezoning industrial areas as commercial or by banishing red light districts to the far corners of a county. The first of the last two chapters focuses on the title and offers observations on how maps impact these aspects, digging, flying, going, of human activity. The last chapter examines relatively new developments in technology and how it integrates with “prohibitive cartography.” As we can see from this cursory summary of Monmonier’s book, the impact that maps have had on spatial restrictions span time from colonialism to the 2000s, scale form the parcel to international level, and in a variety of subtle and overt ways. In essence, Monmonier seems to suggest that states and governments crush us on all sides with maps attempting to regulate our existence. Offered not as a value judgment but as an objective observation, Monmonier’s book provides a valuable discussion on the impacts that maps have had but there are limitations.

The first, and most significant limitation, is the book’s scope. The limitation is immediately apparent to a critical eye examining the book’s sub-title; Monmonier purports to show us “how maps restrict and control.” However, this isn’t the case. Maps do not restrict or control access, they influence human actions. In this context, maps attempt to restrict and control. This nuance is more than a semantic argument or request for clarification; it strikes at the heart of the book. I contend that maps do not restrict at all, how could they? Maps are on paper, on a screen, or on a disk, it is impossible for it to prohibit anything. Maps are only prohibitive if individuals and communities accept them as such. Monmonier takes this basic assumption as an underlying fact throughout his book. For the most part, his examples support his thesis that maps restrict and control; however, he may be guilty of either cherry-picking his data, at worst, or unknowingly misleading his readers. Perhaps a more apt sub-title would be “how Western maps restrict and control.” For it is in the “West,” a gross and undefined generalization admittedly, that communities almost ubiquitously accept the power of the map. Monmonier provides ample evidence of this, particularly for the United States, throughout his book. Most of the evidence relates to court cases settled, in part, through the use of the map. Notable examples include a boundary dispute stemming from hydrological changes in Kansas’s Peuker v. Canter (27-29) or Florida’s right-of-way case in Enos v. Casey Mountain, Inc. (24-25). At the international level, comprised of states following the nation-state concept derived in Westphalia, Monmonier again shows how maps (or geographic phenomena) played an integral role throughout history from the 1494 Treaty of Tordesillas that split the world between Spain and Portugal to the competing claims on Antarctica in the second half of the 20th century. At the local level in the U.S. context and the international context, Monmonier’s assumptions seems to hold, but does it at the local level elsewhere?

I contend that it does not. To take an extreme example, I would cite the Durrand Line that splits the Pashtun linguistic nation between Afghanistan and Pakistan. While the British certainly attempted to police this border during the height of European imperialism, at best their activities were a nuisance. In the 2000s, we find that the line is all but nonexistent as various groups, including violent ones, routinely violate it. Monmonier acknowledges that newly independent states from European imperialists “could not unify dissimilar peoples lumped together by artificial boundaries” (58). However, I find that he does not go far enough. Not only do these states not unify dissimilar communities, they could not enforce the state’s view of its territoriality, i.e. that Pakistan ends at the Durrand line. For their part, the Pashtuns, who the British had split across the border, probably perceived the world in much the same way as they had prior to the split; the Durrand Line was merely a line on a piece of paper. Referring back to the title of the introductory chapter, the boundary doesn’t matter. In addition to this significant lapse in analysis, Monmonier would also benefit from additional technical information to contextualize his comments.

Monmonier’s view on GPS devices should include additional nuance from a technical aspect. As Monmonier is attempting to steer a middle course between providing a jargon-free work accessible to cartographic newcomers and professionals, he may have inadvertently cut some useful detail. For instance, the lay person (particularly homeowner) would want to know that the “highly precise handheld GPS” that Monmonier is referring to still has quite a bit of room for error (something between 10 and 15 feet). While that circle of error may be small enough for most applications, I would hesitate on relying on a GPS to “quickly determine whether a fencepost or rosebush is on [my] property or a neighbor’s” (22). Monmonier should also have considered additional details on non-technical items in order to balance the message of the book. One possibility is how cartography played a role in the decision taken by the military commander responsible for Hawaii to not to implement the order for the relocation of Japanese Americans located in the state to the mainland (as discussed in 174-175).

A final discussion point that I believe Monmonier missed was with the issue of “greenlining” found in chapter 8. While Monmonier provides an in-depth discussion at the beginning of the chapter on “redlining,” or the process of cartographically demarcating “dangerous” areas to preclude them from various services, he provides only one half of the available discussion on “greenlining.” While Monmonier acknowledges that this process involves “mapping out areas within which firms that create jobs receive tax breaks or outright grants” in areas that he describes as “a city’s green, A-list neighborhoods,” he doesn’t discuss some of the other implications of this practice (124-125). One worth discussing at length, is the implication that this practice concentrates additional financial resources in sections of a place that already enjoy substantial financial clout. It seems puzzling, and Monmonier doesn’t discuss this apparent contradiction, that governments are utilizing public resources to combat “unemployment, underemployment, or out-migration” in areas that don’t traditionally experience these phenomena (124). This contradiction might be the source of the lukewarm outcome where these programs result in neither success nor failure.

As I noted at the beginning of this review, we should consider Monmonier’s book an important part of the political geographic and cartographic literature. However, as this review has pointed out, there is at least one glaring omission, which is a discussion of how people decide, or choose to, follow a map’s suggestions. This omission notwithstanding, Monmonier’s examination of the role maps play in delineating ownership at a variety or scales and the overt and subtle messages transmitted by maps to suggest where to go and what to do are important discussion and research points. Any work that causes us to pause and reexamine what we take for granted at a most basic level, in Mark Monmonier’s case the veracity and objectivity of a map, will always have a timeless quality to them.

In conclusion, Mark Monmonier’s exploration of how maps influence human behavior fills a gap in cartographic and political geographic literature. Drawing on historical and contemporary events and court cases, Monmonier discusses the various ways in which maps can restrict our movement, our ownership, and how they impact our worldview at a variety of scales. Despite the wide scope of the book it is incomplete. In the future, I hope to read Monmonier’s thoughts on how people prescribe importance and validity to maps and how maps can be simultaneously important or not in delineating the same area.

The Geography of Rich, White Kids

I don’t like it when tools purport to explain anything, like when someone suggests GIS “IS” Geography. Its not Geography, GIS is a tool of Geography, like Excel, Word, PowerPoint, and various other ways to present, organize, and analyze data are tools. GIS is an incredibly smart tool, but it can give you some really dumb outputs if you let it. Heck, I’m waiting for some of my maps to make it on the “bad maps” Google Image search. Maps, unlike prose and verbal communication, are similar to charts and graphs, there is an inherent authority to them that written and spoken words lack. I can tell you that the United States lies above the equator, you might even believe, but if I showed you a map. I’m still “telling you” but you’ll question me a lot less.

And these are just facts. Think about something more subjective, like New York City is more expensive than London, England. I can make that statement but you may or may not believe, some folks might even go the extra step and call it a hypothesis and test it. But what if I showed you a map of say, average rent per month per square foot, in 10 cities around the world. And New York City’s circle is larger than London’s. You’d probably believe it. But I just lied to you, or simply led you to the answer I wanted to give you. Who defines “expensive”? I chose the measurement, in this example: rent. Perhaps the average rent was $500 dollars per square foot in New York City and $499 dollars per square foot in London. But, to make my point, I broke the two symbols at $500 dollars. Now New York City “looks” bigger on the map, but its a $1 difference. Maps can lie and there are a few great books out there on the topic (I may even post a book review of one!).

While this post isn’t about lying maps and statistics, it is about managing expectations and challenging studies (somehow I have a reputation for being “contrarian [sic]”). Anytime I see a post entitled “The Geography of [fill in the blank]”, my hairs stand on end. Thus far in my own blog I’ve tried to avoid such arrogance. The Atlantic recently ran an article entitled “The Geography of Happiness According to 10 Million Tweets”. Naturally, I had a heart attack (not really). The article was published a while ago but I’ve felt I’ve been rather negative in the past so I wanted to take a break from critiquing others’ work.

THE Geography of Happiness, where’s D.C. and why is Alaska and Hawaii south of the continental U.S.?, 2013 (via the Atlantic)

There are some positive aspects to this work, first is the promise of a new analytic tool. Researchers in Vermont have developed a bot (presumably) to sift through rather large datasets (10 million tweets) to score “happiness” by “geography”. The article (which deserves praise for its even-handedness) provides an example of how happiness scores were calculated. Essentially, the bot measures the words in the tweet for “happiness” and “sadness” and scores the tweet. I’m guessing that all the tweets in a given locality are then tallied and a final score assigned (one imagines that its normalized across the dataset to make relative comparisons meaningful). With a properly scoped (translation: caveat-ed) study, this could have some useful applications.

However, there are serious limitations. The article points out some of them, for one, the context of the words aren’t taken into account. With Geography, its all about local context. I’m fairly sure I’ve heard people in Texas (I grew up there) say, “Hot damn, you’re hot shit”. Depending on the inflection this could be mean a) you’re pretty/handsome or b) you’re rather conceited. According to the methodology, however, this would be an overwhelmingly negative sentiment. Comparing Napa, California and Beaumont, Texas, I would absolutely expect to hear people saying “shit” and “ass” all over Texas. Doesn’t necessarily indicate that folks are sad. As the article points out, perhaps “people might just talk about happiness differently in other parts of the country or within demographic groups.”

For evidence of this latter point (demographic groups), the Vermont study found that people of Norwegian ancestry are happier than African Americans. Firstly, I have no idea how they would figure this out based on tweets. If what I think happened is correct, then we may have stumbled onto a Modifiable Areal Unit Problem (MAUP alert!). I’m guessing that when these tweets were geolocated, they were associated with Census Blocks (I HOPE!), or some larger administrative units (zip codes, counties, and so on). With the available Census data (2011), the researchers could probably guess the population group of the tweeter. This is a guess, perhaps they really did contact a few thousand users, track their tweets for a while, and asked standard demographic questions in survey format. Of course the problem with this approach is that people are affected by their environments and we aren’t rooted in the same place. So a Norwegian in St. Paul a daily commuter to Minneapolis tweets, “this whole place is going to hell”. So is the sadder city St. Paul, or Minneapolis? Considering my previous post of millions of Americans commuting, many of whom are stuck in traffic for any length of time (plenty of time to tweet about it!), one wonders how reflective happy/sad is of the place or the environment.

And that’s just in English! As the article points out Spanish wasn’t covered. So that leaves out an entire demographic group heavily represented in that part of the country that’s apparently the “saddest” the South (though California is high on the list).

All of this taken together, lack of context, unclear geographies, missing populations, one wonders what we’re left with. Its impossible to say what’s making people happy or sad, and its not like knowing that Beaumont, Texas is the “unhappiest” place (for English-speaking tweeters with access to the internet and who like to curse a lot) offers any clues. Did the study account for seasonality: “damn its cold”,”i LUV the SPRING”,”SUMMER IS AWESOME HAPPY HAPPY HAPPY”,”autumn makes me want to shoot myself because i know summer is ending”?

If it didn’t account for seasonality, I think a strong case could be made for a future study of environmental influence on happiness/sadness (environmental determinism alert!). However, were I to create this study I would limit the returned tweets based on landmarks and common sights such as “these broken windows make me want to rob somebody” or “clean facades in Potemkin villages make me happy!”. But in all seriousness, the scale of the study should be larger (that is, more local). With 10 million tweets, statistical significance can be maintained in a single urban area. Why not examine happiness and sadness in a single city, broken up by neighborhoods? Get the researchers out there to figure out if the neighborhood is commercial, industrial, or residential. Do the residents live and work there or do they commute? This sort of integrated study emphasizing both the quick fix fancy new tool of social media analysis with “old school” on the ground research might actually produce a worthwhile paper.

I volunteer!