In my previous post, I noted the low median income in the census tract surrounding the Sedgwick stop on the Brown and Purple Lines. That the median income in that part of the city would be less than $20k went against my own experience of Chicago—as well as my prejudices about the North Side. How could a census tract a (light) stone’s throw (by a strong arm) from Lincoln Park, a few blocks away from the Container Store(s) and sundry other gateways to yuppie distinction in Wicker Park and Bucktown have such a low median income? Was there a mistake?
In the post, I suggested that the culprit was the ghost of Cabrini-Green. After all, as Whet reminds us, the ACS is a rolling survey, meaning that the 2011 version still has data from 2007, when Cabrini-Green still existed. But I bristled a bit at that explanation: Cabrini-Green, at least the Green high-rises, weren’t in that tract. Nor are the original Frances Cabrini Homes. The high-rises are in the tract just to the west, and the row houses are a bit to the south.And even so, look at the coloring in the tracts: where the high rises once were is relatively better off than the Sedgwick tract, and the Cabrini Homes are even better off, in terms of median income, being in the same discussion as the handsome tract just east of Sedgwick, where I’ve had a devil of a time finding parking on the way to Oak St. Beach because of all the fancy cars already gobbling up all the street parking.
So unless I’m making some kind of mistake, this answer is insufficient. Another idea is that the massive depopulation of the Green high-rises has spilled into the Sedgwick tract. There might be something to this. After all, in 2000, what is now the tract that includes the high-rises was three separate tracts, suggesting serious depopulation (NB: the blues are still for the 2010 tracts):
But that only provides some of the answer: the high-rises area is economically well off now since there are no longer 10,000 people involved in the CHA living there. It still tells us nothing about the Sedgwick tract.
Yet maybe there’s an answer in what I’ve already mentioned above: Oak St. beach, parking, Container Store, Lincoln Park… that is, a certain amount of upper middle-class white privilege. Let’s break down these tracts by median income (with margins of error) and then by estimated median incomes of white and African-American households:
Keeping in mind the sometimes outlandish margins of error, this area begins to tell a rather different story depending on who’s telling it. These tracts are all comfortably upper middle-class for their white inhabitants, while the story for the African-American inhabitants is rather more all over the map (further indicated by the margins of error), but decidedly distant from the lofty heights of six-digit annual incomes. So as a non-expert on this neighborhood like me, it’s the white income that tells the story I expect given the retail, entertainment, and housing options nearby.
Is the white story the majority story here, though? Here’s the last picture of the area that puts my assumptions into check:
It’s tempting to say that these numbers speak for themselves and leave it at that, but two quick caveats: the margins of error tip past ±10% for the two tracts just south of the Sedgwick tract. Elsewhere they’re all within 10%.
In geography school, we quickly learn Tobler’s First Law of Geography, where everything influences everything, but near things influence things more than far things. And in that case, we do see the effect of the Cabrini-Green public housing efforts on the racial and income makeup of the tracts surrounding it. So the answer to “what’s the matter with Sedgwick?” is simply “nothing at all.” It’s not an aberration. It and its nearby tracts reflect the brutal racial and economic segregation of Chicago that continues to this day. And my surprise at that is just a function of my own time spent living within that segregation.
Pete sent out this New Yorker interactive web thingy that handsomely redraws each MTA line as, instead, a graph of median income rising and falling as the trains move between poorer and richer neighborhoods. I figured it would take only a few hours to throw something similar for Chicago, and I was right.
Below are each CTA line’s stations plotted against the median income of the census tract that contains the station.1
So we can see that there are similarities with the MTA. As trains move into the Loop (Manhattan), the median income rises, and then it falls as trains move back out of the Loop (Manhattan). As with the New York data, we can see some pretty distinct variance in median incomes. The Green Line moves from nice (but not as nice as nearby) Oak Park to some of the poorest parts of Chicago before emerging in the Loop, only to bend south through some more of the poorest parts of Chicago. The Purple Line starts at the super tony Linden stop in Wilmette before moving through less fancy Evanston on its way to the Loop.
In short, the graphs affirm most of what we already knew. Though I also was not expecting the Blue Line to be so much nicer between Western and Grand than it is in the Loop.
There’s also at least one startling hiccup: the huge dive in median income at the Sedgwick stop on the Brown and Purple Lines. I double checked everything, and that’s the correct tract number. I can only guess that there’s a residual effect of Cabrini-Green’s ghost that’s pulling that number down. Even so, however, the Sedgwick census tract is bordered by North, Sedgwick, Division, and Larrabee, meaning that it’s one tract to the east of Cabrini-Green (which was west of Larrabee) and one tract to the north of the Frances Cabrini Homes, which are south of Division. [UPDATE: I tackle the Sedgwick question in a separate post]
But part of putting this data together was to test another, unrelated hypothesis. I’ve long suspected that the CTA ignores poorer neighborhoods of Chicago, considering how the lines don’t even make it out to the southwest side, and it feels like it’s merely the lowly Green Line fighting its way valiantly to serve the mass of lower-income areas of the West Side. These graphs speak to neither. Also, they don’t tell us whether truly rich areas are served by the CTA, since we have no idea how high that median income number can go. As a result, as is often the case, it’s now more useful to make a map (interactive version available on GeoCommons):
What I was not expecting to see was that the primary poorer part of the city abandoned by the CTA isn’t the area around Marquette Park on the southwest side (which uniformly sits comfortably in the second of seven bins), but, rather, the southeast side, made up of the South Shore, East Side, and South Chicago community areas. I always assumed this area to be more prosperous, but the median income tale suggests otherwise. The wealth of the southeast side is still along Stony Island and Jeffrey, in from the lake.
Furthermore, it’s not the Green Line coursing through the lower-income West Side by itself; it’s joined by both Blue and Pink Lines.
But this then prompts yet another question. Does money follow the CTA or is it the other way around?2 The median income is higher in tracts near the Red and Brown Lines on the North Side than it is for latitudinally parallel patches of land closer to the lake, where one might expect to find more money. I also doubt anyone would be surprised if it turned out that a large part of Bucktown, Wicker Park, and Ukrainian Village’s appeal to higher-income types are their sitting right on the Blue Line, making travel into the Loop for work trivial.
But the CTA doesn’t guarantee a (relative) level of prosperity. The two final stops on the Ashland side of the Green Line look like they’re doing the opposite, as they’re surrounded by low-income neighborhoods, with the better off tracts farther, rather than closer to the El. Englewood has a low median income but sits right on the Green Line. Beverly and Ashburn, on the other hand, are better off but serviced only by Metra. I recall back in the mid-90s, when the Green Line was being renovated, that people wanted it torn down along 63rd St. precisely because it was a blight. No one wanted to live by the El, and no one wanted to have shops underneath it. I strongly doubt that opinion is uniform throughout the city.
Anyway, in closing, one truly sad thing about living in Vilnius is that I couldn’t toss together this kind of a bit of data visualization about it without leaving my chair and in only a few hours.
- In greater detail: I used the 2011 5-yr ACS data on Cook County as provided by FactFinder and joined that with a shapefile of all of the census tracts in Cook County provided by TIGER. Then I pulled in the CTA shapefiles from the City of Chicago (I had actually already done this, but whatever). There were a couple spatial joins and blah blah, and I ended up with a census tract for each station. Many stations straddle census tracts, but I let the spatial join be the arbiter. Then I filtered down the median income dataset to include just the tracts with stations, exercised some patience while dealing with Tableau, and there you go. [↩]
- Obviously I could piece together some sort of answer using historical data, but for now I’ll leave it to speculation. [↩]
Every map nerd in the world is probably fascinated by exclaves, and, as a map nerd, I count myself in that number.
So today I found out this morning that there’s a new set of shapefiles of country boundaries provided by the Humanitarian Information Unit, purported to be the most high-resolution available. As a result, I had to download them and check them out. I immediately tossed them into qGIS and started looking at how high-res these things actually are. And they are. While scrolling around the Lithuania-Belarus border, however, I found a Lithuanian exclave near the peculiar “Dieveniškes appendix,” a small chunk of Lithuania thrust into Belarus that’s about 3km wide at its narrowest point, nearest the “rest” of Lithuania. Of course, this area is a strong mix of ethnic Polish, Lithuanians, as well as Belarusians, so the borders here are naturally very murky. In fact, in Lithuanian school, I was taught that “Lithuania’s” border in this area was the Nemunas (Неман) river, a good 30km to the south.
But wait, Lithuania has an exclave? How come it’s not on OpenStreetMap (above)? Or Google Maps? Or Maps.lt? And why is it so hilariously tiny? Looking at the satellite imagery, it looks like a single farm!
The reason it’s not on any contemporary maps is pretty straightforward. The exclave in the shapefile is the Pagiriai exclave, one of the shortest-lived exclaves in history, lasting only since Lithuanian independence until a treaty in 1996, which gave the land to Belarus in exchange for an equivalent amount of land contiguous with the Lithuanian border. Luckily, an even bigger map nerd than I, Jan S. Krogh, did the research for me:
Mr Josif Rybak, a former mayor of Salcininkai municipality told methat Pagiriai before 1990 belonged to a collective farm under various organisations (kolukiai, tarybinis ukis, valstybes zemes ukio imone Salcininkai) before it in 1994 became a private company (bendrove). During the Soviet period republic borders had no real significance and it happened that regional exclaves appeared. The actual name of this company is not known, but it certainly does not exist anymore. According to the information it was only one house there in a rather bad shape about 1995. One family lived there, the Zanegina family living there which consisted from the mother (about 75 years) and at least two sons (about 50 years of age) thereof one was officially registered at the house. The son not registered had been imprisoned. The family was not of Lithuanian or Polish origin, but most likely Russian. They accepted that their farm, where the house was not their own property, could be Byelorussian territory on condition they would be granted Lithuanian citizenships and pensions. After 1995 the brothers moved to Zavisonys village north of Salcininkai town. According to what is known the sons who both are said to be social cases are now both living from odd jobs they are getting in Salcininkai area. The mother is not alive anymore.
So there you have it. Krogh even visited the exclave with two Lithuanians and provides photos of the ruins of the farmhouse and surrounding land.
Of course, Lithuania still has one fun geographic curiosity. While not an exclave, the town of Neringa shares a land border with Russia but a water border with the rest of Lithuania, making it much like the Eastern Shore of Virginia.
It was an issue more appropriate to a different blog, but I have done a bit of writing about the situation regarding dual citizenship in Lithuania. But assuming you’ve not had need for my Guide to a Passport, you’ve probably not followed the story carefully. In which case, here’s the short version:
- The Lithuanian constitution limits dual citizenship.
- The Constitutional Court (KT) has interpreted that limitation to mean that dual citizenship is given in extremely rare cases.
- All the same, people like me (descendants of Lithuanian citizens who fled Lithuania between 1940 and 1990) are eligible to have dual citizenship, as they’re understood as de facto citizens from birth. I did not, then, apply to become a citizen, I applied to exercise my right to that citizenship.
- People who receive another country’s citizenship automatically (by birth or marriage) can also be dual citizens, though born Lithuanians have three years to choose a citizenship once they reach majority.
- The other way in which dual citizenship is granted is by the President, who can bestow citizenship in honor of a person’s efforts done on behalf of Lithuania.
The situation has not moved much since the KT stopped rampant dual citizenship in 2006 by introducing the rareness limitation. Organizations and the Seimas (legislature) have tried to get around this limitation by legislative means, but they’ve not been successful. I’ve argued since the beginnings of this debate that if one doesn’t like the KT’s rulings, they need to change the constitution, not pass laws that are a priori unconstitutional.
But earlier this week, the KT responded to a specific petition from the President regarding dual citizenship. President Grybauskaitė wanted to know if there could be a law passed that granted dual citizenship to Lithuanians who left Lithuania after 1990 and received some other citizenship. She also wanted to know about yet another situation where an American ice dancer wants to represent Lithuania with her (Lithuanian) partner in the Olympics. “Um, no, lol.” is the short version of the answer to both questions.
In the meantime, the KT explained that it’s not a political organ, therefore its makeup (and when that changes) should not influence its decisions. Nor would political or sociological findings or surveys or anything like that. These external influences would threaten the court’s impartiality. This is, of course, a very weird and archly conservative position to take, but it has a kind of sweetness to it. The KT finds answers in the constitution. That’s its brief, the end.
So this is news in that, as far as I can tell, it reaffirms something we (or at least many of us) already knew. Only a referendum that amends the constitution will open up Lithuanian dual citizenship. And athletes can’t get citizenship for honor and glory they will bring to Lithuania in the future, only for honor and glory they have already brought.1
But I was reminded of one other thing: should I run for Seimas, I would have to renounce my US citizenship, which, of course, has a precedent: Valdas Adamkus renounced his US citizenship when he took the office of President of Lithuania.
- This situation has come up again recently, as Isabelle Tobias, an ice dancer, has had her recommendation for citizenship denied. However, interestingly, the caption on lrytas.lt is a bit misleading. It reads, “American I. Tobias, despite learning Lithuanian, cannot become a citizen of Lithuania.” As far as I can tell, this is only half true. It’s missing a clause at the end that reads, “without giving up her US citizenship.” She’s perfectly able to naturalize, if she should so choose. [↩]
[I was going to save this post until the new year, but the recent appearance of @10print_ebooks, the Markov chain bot for the fascinating (freely-available) book 10 PRINT CHR$(205.5+RND(1)); : GOTO 10 made me eager to unveil this a bit earlier.]
you are literally deconstructing century+ old text and still finding meaning
(a response to @KarlMarxovChain)
A friend of mine was using an online Markov chain text generator (provided by the band Dr. Nerve) over a decade ago to scramble up text. I remember reading the description back then, and despite the fact that I was an adult who was taking the highest level calculus course at my university, I couldn’t properly understand what a Markov chain was.
A Markov chain is a more controlled version of the random walk, in that the probabilities regarding which next step will be taken are weighted. Say, for example, that my food court at work has three restaurants: Snail, Rajun Cajun, and Maravilla’s. If I lunch at Snail, there is a 40% chance that I’ll want to eat at Rajun Cajun the next day, a 40% chance that I’ll want a burrito at Maravilla’s, and a 20% chance that I’ll return to Snail’s panang curry. If I eat at Rajun, there’s a 50% chance that I’ll be back the next day, a 30% chance that I’ll go for a burrito, and a 20% chance that I’ll be eager for Snail the next day. And, finally, if I eat at Maravilla’s, there’s a 10% chance I’ll be back the next day, but even odds (45%) that I’ll go to Rajun or Snail.
So there are three events (eating at one of the three restaurants) that have probabilities that lead to the next event, which then loops back. And, as you can imagine, the rules above, though rather simple (about 20 lines of Ruby without trying to be economical), can create a very wide variety of weeks of dining. For example, if we pick Monday’s restaurant location out of a hat, the last three times I ran the script, I got:
- M: Rajun Cajun, Tu: Rajun Cajun, W: Snail, Th: Rajun Cajun, F: Rajun Cajun
- M: Maravilla’s, Tu: Rajun Cajun, W: Snail, Th: Rajun Cajun, F: Rajun Cajun
- M: Maravilla’s, Tu: Maravilla’s, W: Rajun Cajun, Th: Maravilla’s, F: Snail
Markov chains are especially useful for running simulations to determine statistical outcomes of complicated probabilities. For example, given the situation above, if I have lunch at Maravilla’s on a Monday, where am I likely to have lunch on Friday? It’s far easier to tell the computer to run the Markov chain a bunch of times than to sit and calculate the probabilities. And the answer is, that over a million weeks, if every Monday I would eat at Maravilla’s, I’d spend Friday afternoon at Snail about 27% of the time, at Rajun Cajun 46% of the time, and at Maravilla’s 27% of the time.1
With only three possible states, the chain is not terribly interesting, but this exercise does show the limitations of the process. First, it needs a “seed”: some state to kick things off. Above, I picked a restaurant out of a hat and ran the process five times. Then I took Maravilla’s as the initial state and ran the process five times. Second, the Markov chain only knows where it is right now and decides what the next step to take will be. So I can’t have a rule like, “And I always eat at Maravilla’s at least twice a week.” I could program in such a rule into the script, so that if by Thursday there are no trips to Maravilla’s, I program two in a row, but it breaks the spirit of the chain.
So what if we took a massive amount of possible states and calculated the probabilities of each and built chains out of them? Here is where text scrambling comes into play. A Markov text generator takes a source text, calculates all the probabilities of one word following another, and builds a new string of text based on the probabilities. Let’s say the source text is “A man, a plan, a canal, Panama.” So there is a 3/7 chance that the seed word will be “a.” And if the seed word is “a”, there’s a 1/3 chance that the next word is “man,” a 1/3 chance that the next word is “plan,” and a 1/3 chance that the next word is “canal.” But it’s impossible for the next word to be “Panama.” Only when the previous word is “canal” will the next word be “Panama.” So you can imagine the computer spitting out a text string like “A man A man a plan A man a plan a plan A man a plan,” but the string will always end up, if it goes on long enough, at “a canal Panama.”
But as the source text gets bigger and richer, the probabilities get more interesting, and so do the results. Enter @MarkovChainMe, a twitter bot.
@MarkovChainMe is very simple. If you @ it (with basically any text), it will ask Twitter for your most recent tweets (up to 100). It then mashes all the tweets into one long string of words, strips out the “@”s and any urls (but keeps hashtags), picks a word at random, builds a tweet out of a random walk through the words in your most recent tweets, and tweets it back at you. If you tweet a lot, then Twitter will return a lot of tweets and the resulting chain will be more interesting. If you @ it “do @user,” then instead of going through your tweets, it will go through @user’s tweets (when testing the bot, I used @France24 as my source of tweets, since I hadn’t been tweeting enough recently to get interesting results). It’s a trifle, but the results can often be rather amusing.
The other Markov chain bot I wrote, however, @KarlMarxovChain, is a bit more surreal. For this bot, the source text is either a compendium of early Marx or volume I of Capital. The bot chooses one of the two sources at random. Then it basically does the same as @MarkovChainMe. Five times a day, it picks a word at random and builds a Markov chain out of it and tweets it. If you @ it a word, it’ll look for that word (cutting off the final letter until it matches something in the text) and build a chain around it, and tweet it back at you.
But the text is prepared a bit differently, which means that the results are often a bit more uncanny than those of @MarkovChainMe. When it gets the seed word, it finds it in the text and takes not the next word, but the next two words. The first two words of this 3-gram are first two words of the tweet. It then takes not the last of these words, but the last two and searches the text for that pair of words. Then, of all of the times that those words appear together, it picks one at random, adds the last word to the chain, and then moves up a word. The result is that the probabilities are a bit more constricted, meaning that the tweet conforms a bit more closely to the original text, meaning it ends up sounding a bit more like normal English.
The bot also cheats a bit and tries to make “complete” sentences (start with a word that has an initial capital in the source text and end with a period), but it’s not always successful. The source texts are also not the cleanest in the world, so it sometimes hiccups and tosses out typographical gibberish. But every five or so tweets, it comes up with something rather bizarre. I’ve now also gone through after a few weeks of letting the bot tweet away to clean up some of the assumptions it makes, so it should be even more surreal.
So there we are. Two more Markov chain robots have infiltrated Twitter.
- Or maybe they’re not so useful. I got the same results no matter on Friday no matter where I ate on Monday. More restaurants would probably add more volatility. [↩]
Shaviro ends Without Criteria by discussing the consequences of the Whiteheadian affect-based ontology he has described throughout the book. The metaphysics, he writes,
cannot be applied to particular social and political circumstances. It does not command us, and it does not make ethical demands upon us. It does not make judgments of legitimacy. It certainly does not give us warrant to congratulate ourselves over the crucial role that creativity plays in postmodern marketing, much less to celebrate capitalism for unleashing its continual waves of “creative destruction” (Schumpeter 1962, 81ff.). Whitehead’s metaphysics does not give us any grounds to condemn capitalism—as I would want to do—for purveying a denatured beauty, or for promoting an inauthentic and sadly limited version of creativity. I can only make such a condemnation on my own account, and from my own perspective. (156)
Ultimately, the reasoning is that the realm of affect precedes cognition. If Whitehead is right, then metaphysics is simply no place for politics, which is a feature of cognition. “It is only after the subject has constructed or synthesized itself out of its feelings,” Shaviro writes earlier in the book, “out of its encounters with the world, that it can then go on to understand that world—or to change it”(15). Whereas another (anti-)metaphysics might ground itself in, say, the Other, culture, or language, thereby giving the political (and ideological) access to the very kernel of being, in the description Shaviro gives, it doesn’t work that way. Ethics only goes so far. Morality only goes so far. Language, culture, and even a critique of capitalism, which Shaviro would like, can only go so far.
This decoupling of politics from ontology is one of the most provocative parts of Without Criteria, and it’s part of why I like it so much. And it also is a bridge between Shaviro and Object-Oriented Ontologists (Harman, Bryant, Morton, Bogost, in the context of what I’m looking at here) with whom he has shared a useful tête-à-tête for years. Part of the appeal of OOO lies in its efforts to break out of the prison-house of language by arguing for a radical and weird realism in which the human subject is no longer the centerpiece of reality. An ontology based on language or on a critique of capitalism tells us very little (if not nothing at all) about the relationship between an orchid and a wasp. If we put aside those fences built by humans to keep humans in the human world, however, and consider the affective relationship between the orchid and the wasp, suddenly we can say something philosophical about it.
This decoupling also forms the spine of Galloway’s critique of “the new realism” in the newest issue of Critical Inquiry. I’m not familiar with Galloway’s other work, but I’ve been eager to read an engaged criticism of the OOO decoupling of politics and ontology that attempted to read the OOOers with the same kind of care that someone like, say, Shaviro does. Unfortunately, this article is not such a critique. Instead, in its eagerness to dismiss “the new realism” tout court—a realism which includes such varied philosophers as DeLanda, Meillassoux, and Harman, it creates a conspiratorial parody of realism only too easy to topple under a series of gratuitous references to mathematics and computer programming that I imagine might be unfamiliar to many readers of CI. The obfuscation gins up a cloudy mess that makes it difficult to follow the path of Galloway’s argument, leaving me with the impression that it is mostly a series of asserted observations, not terribly well-connected, that end up with everyone cheering for Marx at the end, a kind of cheering that, again, many realists—myself included—would like to join in on.
The battle for Galloway is between materialism and realism. On the side of the materialists are Marx and himself, as well as the anti-essentialists that make up and are the progeny of our “Marxist, feminist, and postcolonial forebears”(356). In short, “the Left.” On the other side are the realists, including those named above and other similarly aligned thinkers like Badiou (whose radical leftism, for Galloway, makes his dalliances with universalism a bit more palatable) and Latour. These two warring parties align themselves on the battlefield as well of two forms of politics: aligned and unaligned. Aligned politics is “tethered to a moral yardstick and equipped with an ethical mechanic able to pursue it.” There’s a morality, a plan, a canal, etc. The unaligned, on the other hand, is a politics “unencumbered by the moral law,” featuring projects that “exist as mercenaries, often jumping the gap between friend and enemy”(365). Any good leftist has already intuited which of materialism and realism features an aligned politics and which features an unaligned.
By being an ontology that does not have a politics stapled to it, realism is “dangerous”; it “abdicates the political decision”(365). And we end up with Galloway’s closing warnings that “the true poverty of the new realism is not so much its naïve trust in mathematical reasoning and object-oriented architectures but its inability to recognize that the highest order of the absolute, the totality itself, is found in the material history of mankind”(366).
There’s a lot in that assertion that demands immediate discussion. What Galloway calls an “inability to recognize,” a thinker like Bogost or Harman (and probably DeLanda) would consider the point. The speculative realists, in aligning themselves against correlationism, are explicitly building a philosophy in which humanity is not central. They recognize perfectly well Galloway’s position of putting the material history of mankind at the “highest order of the absolute,” and they are actively trying to move beyond it. Were Galloway to say “inability to successfully demonstrate why it is not that,” then we would be able to argue something. As it is, the discourse sounds like something along the lines of “It’s 2011.” “No, it’s actually now 2012.” “Right, why can’t you understand that it’s 2011?” The realists have binned the centerpiece of Galloway’s ontology, and instead of engaging with their critique, he, sounding like a direct-mail scare monger, sniffs that the realists are espousing a “dangerous” ontology, one which could, I would imagine, be used to keep capitalism in power…
…more or less exactly as Shaviro notes in the opening quote to this post. Capitalists aren’t using realism when they use the aesthetic relationship to creativity to engage in Schumpeter’s “creative desctruction.” Similarly, anti-capitalists aren’t using realism when they organize themselves into political groups. Cleopatra’s Needle isn’t a capitalist. The orchid isn’t a capitalist. The wasp isn’t, either. Yet they have a right to be a part of the real world, no?
What realism does—its “danger”—is precisely what attracts me to it, at least the version of it Galloway is trying to topple in this article. Realism launches infinite competing political forms, political ideologies, including many in which the autonomous, liberal human subject is not the center of the ideology. Of course some political ideologies that aren’t based on liberal human subjects would lead to a world worse than the one which we have now. But it is simply not the case that all of them must. Or that the only way to reach a just world is by riding that tired old nag of liberalism until it buckles at the gates of socialism.
But I’ll stop here, since I don’t want to put words into Galloway’s mouth. Instead, I’ll remark on another part of the final paragraph of the essay, in which Galloway contrasts materialism to realism in how materialism does not believe that “everything should be rooted in… abstraction, logical necessity, universality, essence, pure form, spirit, or idea”(366). Now it may be that Meillassoux, who serves as Galloway’s primary interlocutor, believes this. But no one who has read DeLanda or Harman (much less the other OOOers quoted by Galloway) with anything resembling care can believe that either believes in universality or essence in the way the realists of medieval Europe, whom Galloway channels here, did. If Galloway is willing to call the contemporary thinkers part of “the new realism,” he should strive to understand what the fundamental breaks are that they make from “old realism.”
Yes, it’s true that in Intensive Science and Virtual Philosophy, DeLanda announces his attachment to realism, as reported by Galloway. But the realism is a Deleuzean realism, radically anti-essentialist and anti-transcendence. DeLanda has no room in his ontology for universality in his reading of Deleuze. As he himself writes in the book from which Galloway quotes:
Deleuze is not a realist about essences, or any other transcendent entity, so in his philosophy something else is needed to explain what gives objects their identity and what preserves this identity through time. Briefly, this something else is dynamical processes. (3)
As for Harman, the outrageously radical autonomy of objects that are always withdrawing ruin any kind of appeal to universality or pure form. As Bryant argues in Democracy of Objects (a book also appearing in Galloway’s bibliography), we cannot even grant Badiou the luxury of saying that a single world exists to collect all the objects, so how, it strikes me, would we be able to talk about universality? Again, it may be that Meillassoux is more aligned with Galloway’s critique of seeing the new realism as a simple rehash of the old battles which demand him (and others) to “trot out the old antiessentialist arguments”(356). But those arguments don’t seem to work against DeLanda or OOO, since these thinkers are responding (in part) to historical materialists.
Harman, for example, has written frequent (and overlapping) attacks on materialism. Galloway differentiates himself from Harman’s critique by insisting that his own materialism “is taken to mean historical materialism” and not “the definition of materialism used in certain scientific and philosophical circles,” like Harman’s, where materialism is “a form of atomism through which small elements of matter are the foundations and ultimate arbiters of everything that exists”(359). Actually, no. What Galloway describes is what Harman calls “undermining” materialism, where materialism reduces objects “downward to their material underpinnings.” But Harman also describes a materialism called “overmining” materialism, in which objects are reduced “upward to their appearance for human beings”(“Realism without Materialism,” 52). He, Bryant (in chapter 2 of Democracy of Objects), and Morton have made repeated references to these two branches of materialism, and Galloway’s missing this only further suggests that he is arguing with thinkers other than those quoted in his article.
And yet those quotes he does provide are dismissed as readily apparent in their ghastliness to us good leftists. Again he takes a swipe at Harman while concern trolling: “Left unchecked, there is little to differentiate the new philosophical realism from the most austere forms of capitalist realism. What kind of world is it in which humans are on equal footing with garbage?”(364) The “equal footing” comes from one of Harman’s “Latour litanies,” streams of objects used precisely to disorient and remind us that we are discussing a world that is larger than merely the human corner of it. These Latour litanies are the a genre calling card of much OOO writing and are described in great detail by Bogost in Alien Phenomenology (Galloway does not quote Bogost anywhere, but he does make a passing reference to “Bogost” in one footnote, making him the only person in the article who never gets his first name in print), but to read a Latour litany as “equal footing” in the way Galloway does is to mistake an ontological argument for a political argument. Again, Bryant, from a book referenced by Galloway:
This, in short, is what the democracy of objects means. The democracy of objects is not a political thesis to the effect that all objects ought to be treated equally or that all objects ought to participate in human affairs. The democracy of objects is the ontological thesis that all objects, as Ian Bogost has so nicely put it, equally exist while they do not exist equally. (19)
Harman’s comparison of humans to garbage (the actual quote is “plastic in a garbage dump is no less an actant than a nuclear warhead,” but whatever… Harman could have easily written “a person” there) is ontological, not political. And though it may be impossible for ontology to not have a politics, again, that’s not Galloway’s argument.
The comparison between humans and garbage leads Galloway to further fret, “What kind of world is it in which the only absolute law remaining is the absolute law of a barren, totalizing nihilism?”(365) This rhetorical question is especially rich because, in my more postmodern/Derridean days, I was often accused of nihilism. “If all is a text,” I’d be asked, “then even the Holocaust is just a text, no?” The only possible response at that time was, “Well, it’s rather a bit more complicated than that.” The case is the same now. Bryant explicitly says that “The aim of diminishing the primacy of the human is not nihilistic nor designed to exclude the human”(248). As for Harman, he sees the undermining materialists as the real nihilists. They “view individual objects in a spirit of nihilism, destroying them with bulldozers to make way for something more fundamental”(The Quadruple Object, 10). Morton sees OOO as the “genuine way out of the recent philosophical impasse of essentialism versus nihilism”(“Here Comes Everything,” 164). For him the nihilists are those (like Whitehead, I imagine) who insist that entities are no more than their relations. “OOO can’t be a form of nihilism,” he explains. “It’s the opposite view (relationism) that tends towards nihilism. Relationism holds that objects are nothing more than the sum of their relations with other objects… At least OOO takes a shot at saying what objects are: they withdraw”(184)
So despite these realists’ efforts to engage with nihilism, Galloway merely asserts that they are nihilists following some kind of “absolute law” and moves on to his next point.
I’ve suggested how Galloway sounds like someone writing a conspiratorial scare pamphlet, the sort of direct-mail that promises me that it would be possible to have an electric car that runs on $10 a year if only those asshole realists in the government/Detroit/whatever weren’t holding back the truth. Part of the genre of that scare pamphlet is merely asserting things without context and bending the context to elicit a reaction, like Harman’s homo sacerish comparison of humans to garbage. Another aspect of the genre is collapsing a whole gallery of people (“realists”) under the actions of one of them, in this case Meillassoux. Meillassoux may be the Teddy Kennedy of the realists (though I doubt it), but that doesn’t mean that a Southern Blue Dog Realist is a Meillassoux clone. A further trope is never precisely spelling out the consequences of or arguing the opposite point. At the risk of sounding especially uncharitable, it feels like Galloway’s article can be reduced to “We beat the realists once, dear leftists. If we don’t again, things might get ‘dangerous.’” He can’t say that the realists would make things worse per se, because humans are already being ruined by capitalism. The worst the realists could do is play in their ivory towers and sit by while capitalism continues its scorched-earth policy, despite the heroic effort of historical materialist chest-thumping in the pages of CI.
But the most obnoxious trope of the scare pamphlet that Galloway adopts is the use of a flurry of specialist language to give an appeal of expertise that really does not serve much argumentative purpose other than to establish the interlocutor’s bonafides. Here I have in mind what absolutely blew my mind in the opening pages of the essay, namely the invocation of object-oriented programming.
OOP, Galloway explains, is based on math and on set theory (the realm of the old realists). And it has certain affinities with Badiou. OK. But then Galloway begins a scare campaign about OOP to convince us good leftists that we should be against OOP (I think?). To wit:
object-oriented computer languages inhabit an important niche in today’s global industrial infrastructure: as software they control the new robotic automobile plants, fluidly synchronize corporate headquarters with call centers in other countries, and allow companies like Google and Facebook to process millions of requests efficiently. (349)
object-oriented computer languages are themselves the heart and soul of the information economy, which if it is not synonymous with today’s mode of production is certainly intimately intertwined with it. Many of the most highly capitalized companies on the planet are software companies reliant on object-oriented infrastructures (Google, Cisco Systems, IBM, Facebook); many of the richest individuals are moguls from the information technology sector (Michael Bloomberg’s estimated worth is $22 billion, Bill Gates, $56 billion); almost every aspect of industry has today been restructured to accommodate the affordances and vicissitudes of software (algorithmic trading in finance, bioinformatics); and the vast majority of this software is written in object-oriented languages, be they C++, Ruby, or Java. Furthermore, object-oriented computer languages not only structure business but also influence the logic of identifying, capturing, and mediating bodies and objects more generally… Thus it is not too much of a stretch to say that the contemporary mode of production has a very special relationship with object-oriented computer languages… In short, Java and other languages are the tools par excellence of the contemporary postindustrial infrastructure. One should have no illusions about it. (351–352)
OOP, you see, is used by capitalists! In order to make money! So it must be bad? And since it’s based on set theory and realism, they’re all intertwined, and Google’s post-Fordist sins are tossed at Meillassoux’s doorstep. I have to be flippant here because this absolutely boggles my mind. Which is also why I quote at such length. Galloway throws completely useless facts at us, like that Google relies on C++ (which may not even be true, seeing as Google uses commodity-class servers running Linux), to establish some kind of sinister relationship between OOP and capitalism.
Now it is certainly the case that OOP emerged under capitalism. It’s also the case that OOP relies on certain assumptions from set theory in order to organize itself, which Galloway explains well in the essay. I have no disagreement with either of those assertions. But they are not proof that OOP is necessarily a coercive capitalist tool that we should view with strict suspicion, as hinted in the quotes above. After all, historical materialism also emerged under capitalism, but it has managed a good trade in anti-capitalism. Surely the same could be true for OOP?
Galloway’s description of object-oriented programming languages make them sound like some kind of cabalistic cant that the 1% use to keep themselves in power. I can imagine someone who doesn’t know anything about programming, who, after reading this article and learning that I can write Ruby, reacts with wariness—or at least with hilariously unrealistic ideas about my net worth. By only focussing on the bad, Galloway demonstrates how OOP (like realism) can be “dangerous,” but by ignoring the good, Galloway does not give the realist relationship to politics its due. Whitehead’s ontology actually can neither praise nor condemn capitalism. On the other extreme, OOP can either build up or demolish capitalism. That the latter has not yet happened isn’t OOP’s fault, and it’s outrageous to hint that it is.
We return to my own desire, a desire for a considered critique of the relationship between politics and the new realism. Some OOO thinkers have tried to sketch this relationship out for themselves. Bryant critiques Occupy from an OOO perspective while considering himself a committed Marxist. Morton, on the other hand, sees a kind of anarchism emerging out of OOO, which amusingly puts it somewhere right back on the side of Occupy. And what do you know, it’s interesting what emerges when the author isn’t trying to scare me into being a materialist.
I’m on the road until next week, so any sort of map-based reflection on the second round of Seimas elections will have to wait. Which is fine, since the results are both not shocking and still in a bit of a holding pattern themselves.
Before the second round of run-off voting, I was reading that the President, Dalia Grybauskaitė, who has veto power over the Seimas’s choice of Prime Minister, said that she would never accept a government in which the Labor Party’s chairman, Viktor Uspaskich, held that role. The man remains under a stormcloud of charges relating to fraud, and it would not be proper for him to head the government. For what it’s worth, Andrius Kubilius, the outgoing PM and head of the conservatives, said that he’d never go into a coalition with the Labor Party, trumping the President’s ultimatum.
Of course, now that the second round is complete, it seems as though neither warning needs to be heeded. The Social Democrats passed the Laborites in terms of total seats in the Seimas, and they’re now solidly in the driver’s seat regarding coalition haggling between, as everyone predicted, themselves, Labor, and Paksas’s Order and Justice Party. Between them they have 79 out of 140 seats in Seimas (one seat will be contested in a special election in six months because of Laborite vote-buying shenanigans).
So though the results are more or less done, the government is still in the process of being formed, with latest news hinting that not only will Uspaskich be frozen out of the new coalition (not surprising, as he’d only leave his post as MEP for something more prestigious, like PM), but so too will be his second in command, Vytautas Gapšys, who is under the same stormcloud as his mentor. Gapšys had been touted as a possible Parliament Speaker, but Algirdas Butkevičius, the head of the SocDems and likely next PM, categorically insisted that his moral code would force him to deny, with 100% confidence, a minister or Speaker role to either man. Butkevičius is confident that he’ll reach a compromise with his coalition as well as with Grybauskaitė, but Uspaskich is waiting to see what the future will bring.
So I, too, will wait. In the meantime, I can give one nugget of election analysis: Drąsos kelias (Path of Courage), the anti-pedophile protest party, failed to win a single election in the second round, where each of their candidates was dismissed by a conservative candidate. They will, however, because of the logic of the proportional voting system in the Seimas, still have seven seats in the upcoming term. This seems fair; they showed that they have a certain amount of support (even if it’s largely limited to Kaunas and its environs) to earn some representation, but it was not enough to topple the conservative party structure. On the flip side, the Peasants and Greens Union, which did not break the 5% threshold in proportional voting will get one voice in Seimas, as they managed to win the constituency around Šiauliai.
Last night, I finally saw The Other Dream Team, the documentary that proposes to tell the story of the 1992 Lithuanian Men’s Basketball Team that beat the Unified Team to win bronze at the Olympics in Barcelona.
Of course, the story makes no sense without the necessary context of how this team, playing for the first time as Lithuania (and not as part of the Soviet Union), emerged out of the twin forces of basketball’s six decades of popularity in the country and the Soviet sports machine. The result is that the movie is less about the specific team in 1992 and more about the four Lithuanians who were stars of the 1988 gold medal–winning USSR team: Šarūnas Marčiulionis, Arvydas Sabonis, Rimas Kurtinaitis, and Valdemaras Chomičius. The changes in the USSR in the 1980s we see through their eyes, as it becomes easier and easier for them to go abroad, up until finally Marčiulionis, in perhaps the defining moment of the film, turns his back on his surrounding infrastructure and lights out for the Terrritory (in this case, the Golden State Warriors), completely alone, a radically individual autonomous subject.
Even within this description we already see, despite how fun and enjoyable most of the movie is, problems that will emerge to overwhelm the film.
Watching the movie, directed and co-written by diaspora Lithuanian Marius Markevičius, I had a sense of something that was not quite nostalgia but more like déjà vu. Markevičius gives a lot of nuggets (especially during Sabonis’s often hilarious interviews) to an expert audience, but the primary thrust of the movie is for neophytes: for people like perhaps Jonas Valančiūnas—the tenuous link the film uses to bring its story to 2012—who did not experience the Cold War. These people don’t know the story of the Lithuanian SSR. They don’t know about the deportations to Siberia, about the bread lines, about the political battles that were waged on the basketball court whenever Žalgiris (from Kaunas) would play CKSA Moscow.
And hence the déjà vu. Telling the story of Soviet occupation of Lithuania was a preoccupation of mine in the late 80s and early 90s. But at some point I stopped wanting to tell the story. Perhaps the problem was that the story I knew was merely that: a story. Not history—or, at least, not adequate history—but also not fiction. The story I learned had a specific political purpose built into it that encouraged my own desire to tell it to the world; it was a story designed to completely delegitimatize the Soviet Union, to bring about its annihilation, and to let the self-determined utopia of an independent Lithuania, building upon the interwar paradise republic, to take its place. Less a story, then, and more basic capitalist propaganda.
Smartly, Markevičius feels this impulse and attacks it early in the movie. We’re treated to a brief description of US attitudes to the Soviets during the Cold War, filtered through shots of Dr. Strangelove, Red Dawn, Rocky IV, and other Cold War classics (the former being a peculiar and even subversive choice). To Americans, the Soviets were always presented as radical others. Everything about their society was backward from ours. They cheated to win, while we believed in sportsmanship. They crushed individuality, whereas we had a culture that prized the rights of the individual. In this way, they were rendered inhuman. They were an enemy for whom we should have no pity when it would become time to wage war. Soviets were nameless and faceless, the men in black flying MiGs in Top Gun. This complete caricature is made extra-obvious by Markevičius’s montage.
But the problem is that Markevičius never then abandons this caricature; in fact, the caricature informs the politics of the entire movie. It’s not that the Lithuanians somehow transcend this alterity, humanizing the USSR. After all, we’re told that our view of the Soviet Union as told in these movies is fundamentally sound. We consistently hear story after story about commodity shortages and rationing, including even a completely gratuitous joke from Ronald Reagan. What The Other Dream Team suggests, then, is not that our view of the Soviet Union is wrong. They actually were as bad as portrayed in the various movies. The West’s mistake, and what the politics of the film seek to rectify, is the idea that these Lithuanians were Soviets.
Even though the movie gives ample screen time to radical nationalists like Vytautas Landsbergis, tellingly, the only “Soviet” voice in the movie comes in the form of the sympathetic interviews with Sasha Volkov, the Ukrainian who was part of both the CSKA Moscow teams that terrorized Žalgiris in the 1980s and the Unified Team that lost in Barcelona. It falls on him—who had been playing capitalist as a professional ballplayer in the NBA for three years already before meeting the Lithuanians in Spain—to inhabit that inhuman bad guy persona against which the Lithuanians (and the West) fought. If that doesn’t make sense, it’s because it can’t. No giant Soviet bogeyman sits for an interview in the film because this giant Soviet bogeyman doesn’t exist. The simplistic anti-communist politics of the Lithuanian Diaspora, which could have been discarded after independence (Landsbergis’s continued political career shows how it wasn’t) are rearticulated in this film over and over.
As an example, there is a five minute (or so) interlude in which the players are asked to talk about the Stalin-era deportations to Siberia. We’re provided children’s drawings of the cattle cars taking away innocent Lithuanians to work camps, and in the meantime each player struggles to describe how profoundly his family was affected, how many uncles were deported, etc. What on earth that has to do with basketball or with the players’ desire to strive on the court is a complete mystery. Kurtinaitis even explains that it’s a history he’d rather not talk too much about (if I recall correctly). But the film urges that you draw the conclusion that his reticense is a function of his eagerness to avoid pain. Probably it is. But another conclusion is that the reticence uncovers talk of 1940s–1950s Siberia as a non sequitur, immaterial to the basketball being played in the 1980s as well as to Lithuanian struggles for independence, which would have existed with or without the deportations.
But the discussion of the deportations does provide yet another opportunity for the film’s politics to reemphasize that the caricature of the screaming officer from Red Dawn is not actually a caricature. After all, only an unthinkable evil force would rob children of their childhoods.
Towards the end of the film’s historical arc, as Landsbergis begins to get more and more screen time, he explains how, once, in a group of people in Vilnius, he understood that he was not a part of a mass. He found himself, rather, among individuals. Masses, he implies, are for (unruly) communists. Instead, he was at a spontaneous gathering of radically autonomous subjects. But he shows the folly of his own liberal fantasy by then reflecting on the words of a journalist: this wasn’t a mass gathered here, but, rather, a nation. Nationalists can move in numbers, as a unified, unchallengeable forces forcing others to its will. But a mass is a coercive actor of Soviet oppression deserving disdain.
I mentioned earlier that I thought the links to Valančiūnas were rather tenuous. After all, several players from Lithuania have played in the NBA over the past two decades. Why do we care specifically about this one? The movie offers that the reason is since he was born in 1992, in line with the climax of the film. But if that were the case, it’s a really ridiculous reason to include him. Thousands of people in Lithuania were born in 1992. Instead, a friend suggested, he’s a bridge, showing how different (or similar) life is for a twenty year old now compared to how it was for Sabonis and Marčiulionis.
Though I’m not quite sure what Markevičius wants to say about the similarities or differences, it seems like there are enough of both to reveal the incoherence of the politics of the movie. On the one hand, Valančiūnas’s being drafted by the Raptors is in stark contrast to Sabonis’s being drafted by the Trailblazers. As Sabonis says, what difference did it make that he was drafted? The Soviets would never let him out of the country to actually play for Portland. Valančiūnas, on the other hand, is part of that free market and is able to plot his future against the draft. We’re even told the old saw about how “millions of dollars” separate a high first round pick from a low first round pick. Score one for independence and freedom.
Yet at the same time, we see the modest Valančiūnas home. Jonas talks about how his father built the backboard with his son’s help, and he even reminisces about what a daunting task it was, using nearly the exact same words as Marčiulionis, who earlier describes building his own backboard outside of his dilapidated apartment building in Kaunas. The material goods available in the west to the likes of Marčiulionis and Sabonis—instant access to cars, computers, bananas—are all missing from the Valančiūnas home, where we see that Jonas sleeps on a bed unlikely to contain his massive frame in a simply decorated bedroom. Score one for whom, then?
Valančiūnas’s story is about Valančiūnas, not about Lithuania. He’ll enjoy the benefits of class mobility, as will his mother. He’ll be a millionaire. But Lithuania won’t become a nation of millionaires. Similarly, Marčiulionis’s risky move to go to the US was a function of his own individual ambition. Going to Golden State was about him (and his family), not about Lithuania, despite the fact that his moving had the ancillary result of raising the profile of Lithuania. At the time of independence, in fact, all four main Lithuanian ex-USSR players were pros in the West, a fact mentioned in the film, at best, only in passing, as Kurtinaitis describes how he was playing in West Germany during the independence struggle. These four men had already realized class mobility (and had become good capitalists) outside of (and without) an independent Lithuania. Glasnost’, not nationalism, made these men rich.
But the film aligns the individual mobility of these players with the independence of a nation of 3 million who will never experience similar success. Marčiulionis remarks at how shocked he is that one can walk into a dealership in the US and walk out with a car right then and there. “What a country!” he might as well add in a Yakov Smirnoff accent. Yet how many people in current independent Lithuania have that same “freedom”? I’m by no means poor, but if I wanted to walk into a dealership and pay cash for a car, it’d be the culmination of many, many years of scrounging and saving for such a thing. Yet the film aligns democratic freedom with material prosperity.
So I’ve got rather fundamental problems with the movie. It purports to move past the image of the Soviet as the evil villain only to require his continued presence as a foil for the Lithuanians struggling to emerge out from under the Soviet thumb. It sutures together a massive democratic process with the class mobility of a handful of edge-case Lithuanians.
Most profoundly, though, it begs the question of the invariable goodness of nationalism. Nationalism is never questioned, never checked. Anything that is “pro-Lithuania” is ipso facto good. Everything that is pro-Soviet is necessarily bad. The Soviet era is presented merely as one of persistent conflict, as though it’s impossible to consider that, perhaps, these four Lithuanian basketball players were ever even friendly, say, with the likes of Sasha Volkov. Within the logic of the film, Volkov is forever a villain: non-Lithuanian, playing for CSKA Moscow against Žalgiris, and suffering the final ignominy of losing out on a bronze medal to the Lithuanians. But Volkov, we can’t forget, also celebrated with the four Lithuanians in Seoul in 1988. And he also played in the NBA. And he also played for his own nationalist (Ukrainian) team. The zero-sum conflict of nationalism, which is the ostinato of Markevičius’s direction, doesn’t make sense in the context of sport, where players can be teammates under certain circumstances and rivals under others.
I started asking myself how I might have made the film differently. Ultimately, I think it’s impossible because of these unexamined political preconditions.
But there are a few ways out. It’s interesting that the film chooses in part to focus, for example, on the rivalry between Žalgiris and CSKA Moscow instead of, say, on the rivalry between Sabonis and Marčiulionis themselves, a rivalry that existed in the USSR as well as in Lithuania. Marčiulionis, after all, never played for Žalgiris, despite its being a de facto Lithuanian national team. Instead, he played for their Vilnius rivals, Statyba. And since independence, both men have tried to assert themselves as the keystone of Lithuania’s basketballing legacy. As Volkov says:
Сабонис и Марчюлёнис с детства очень дружили, но постоянно спорили, кто из них в Литве главнее. Иногда могли зайти в туалет и подраться.
A movie that foregrounded their rivalry would have softened the over-the-top nationalism, turning the men instead into mere entrepreneurs exploiting patriotism. Focusing on their interpersonal rivalry would have brought in players like Volkov from the cold. No longer is the movie about these poor four Lithuanians being denied every bare necessity while toiling almost against their will for the red Soviet jersey. Now it’s about how a unit—that very same 1988 team—over the course of four years turned into something radically different, namely two teams competing against each other for bronze in Barcelona.
I doubt anyone would have made that movie, though, and I doubt that anyone would have wanted to see it. But it at least wouldn’t have been antiquated anti-communist propaganda rehashing extinct modernist Wilsonian politics of nationalism.
Tags: anti-communism, Arvydas Sabonis, basketball, Communists, CSKA Moscow, Jonas Valančiūnas, Marius Markevičius, Rimas Kurtinaitis, Šarūnas Marčiulionis, Sasha Volkov, Statyba, The Other Dream Team, Valdemaras Chomičius, Vytautas Landsbergis, Žalgiris
A friend looked over my recent posts and said, basically, that this analysis of things that had already happened was all find and dandy, but might it be possible to predict the results of the second round? On Tuesday, I speculated that a coalition of the Labor Party (Darbo partija), Social Democrats, and Order and Justice (Tvarka ir teisingumas) would be at most 11 seats away from a majority, meaning that the three parties have 11 second round elections against other parties that they have to win. But what are the chances of getting those 11 seats? Similarly, considering that the conservatives (TS-LKD) are the most represented party in the second round, how likely is it that the Prime Minister Andrius Kubilius’s words—that his party will be the largest faction in the new Seimas—will come true?
I’m not an elections prognosticator—there’s already one alum of my university who does that rather well—but, I am a bit of a hobbyist. So I decided to take the results of the first round and develop a predicting methodology for the second round. For the TL;DR crowd, here are the results:
- The conservatives will pick up 11 seats.
- The Social Democrats will pick up 11 seats.
- The Labor Party will pick up nine seats.
- Order and Justice will pick up four seats.
- The Polish Action (Lenkų akcija) will pick up two seats.
- The liberals (LRLS) will pick up one seat.
- The Path of Courage (Drąsos kelias) will pick up one seat.
That’s 37 of 68 seats. The rest my methodology considers too close to call. But it does indicate that the Social Democrats, Labor, and Order and Justice still have some work to do to get to a majority. What was the methodology? Both of the parties in each run-off were awarded bonus points based on certain criteria. If a party scored more than three bonus points, it was solid for that party. If a party scored more than one point, it was a slight favorite. If both parties picked up less than one point, it was considered a toss-up.
Here’s the rather arbitrary way the points were distributed:
- +1 for an incumbent (or if the candidate is a member of the incumbent party). +.5 if the incumbent party is not represented at all. (This second part was a bit tricky, since parties are so volatile in Lithuania)
- +1 if the candidate won the first round by more than 20 points. +.5 for a win of more than ten points. +.25 for a win of more than five points. The inverse was true for the first round runner-up.
- +1 if the candidate’s party also was the party that received the most votes in the constituency in proportional voting.
- +1 if the candidate’s party received votes at a percentage two standard deviations (or more) above the party’s national mean in the constituency. +.25 if it was more than one standard deviation above the mean. The inverse was applied if the party underperformed its national average within the constituency.
- +1 if the candidate’s party was the leading proportional party and received 28% or more of the vote in proportional voting (one standard deviation above the mean of all top parties in all constituencies of ~24%).
The rationale was:
- Incumbency would be rewarded, even in an election about change. There would even be a trace effect if a new candidate represented the incumbent party. But both sides benefited a bit if it was a clean slate.
- Beating up on the second place candidate in the first round bodes well for the second round.
- Representing a popular party in the constituency helps.
- If your party is especially locally popular, it helps.
- If your party demolished the others in proportional voting, it helps.
Interestingly, only two candidates received 4.5 bonus points (against .25 for their opponents), and both represent the Polish Action. Somehow I’m a little skeptical that these are locks, since I suspect the non-Polish population in both constituencies will rally and vote for the Lithuanian candidate. The question is if there will be enough Lithuanians voting to offset the Polish vote. In the other constituencies, the matrices get too complicated for me to consider.
So how does it play out spatially? Glad you asked (as always, click to enlarge):
It’s no surprise that there’s some correlation with the maps from the previous post; that correlation is built into the means by which I hand out bonus points. The toss-ups (mostly) have the showdown indicated on the map. The party that got more votes in the first round is the first mentioned. I’ll also include a few explanations of abbreviations: TT = Order and Justice. LCS = other liberals. Indep = Independent candidate. VZ = Peasants & Greens. Also, the three “decided” constituencies feature candidates who broke the 50% threshold in the first round and face no run-off.
In the Vilnius inset, the northwestern toss-up is Fabijoniškių constituency. It’s TS-LKD vs. Darbo p. The eastern constituency, Naujosios Vilnios, is Lenkų a. vs. Darbo p. The large one in the southwest, Lazdynų constituency, is TS-LKD vs. LRLS.
All three Kaunas toss-ups are TS-LKD vs. Drąsos k. In Klaipėda, the northern toss-up, Danės constituency, is TS-LKD vs. LCS. The southern constituency is actually Pajūrio constituency, which makes up much of the coast. It’s TS-LKD vs. Darbo p.
A few small consituencies are obscured in the main map. Alytaus constituency is a Darbo p. vs. SocDemai toss-up. The northern constituency of Panevėžys, Nevėžio, is TS-LKD vs. Darbo p., and the southern constituency, Vakarinės, is Indep. vs. Darbo p. Marijampolės tiny constituency is mostly blocked by the label for the surrounding Suvalkijos constituency. It’s a slight SocDemai favorite.
So there are some predictions. We’ll see in just over a week how ridiculous they were.
In my previous post, I provided links to fancy interactive maps from the Lithuanian Election Commission. They map turnout, how people voted on the referendum, and other fun things.
But they also map something completely useless, namely the party that “won” each constituency in the vote to decide how many proportional seats the party will get in Seimas. This is a completely stupid way to represent a map, since the point of the proportional seats is that they are distributed based on the percentage of the national vote a party gets. The Labor Party (Darbo partija) did not get 17 proportional seats in Seimas since they “won” 17 constituencies—that part still has to be determined. Rather, across the nation, they received enough votes to earn 17 of the 70 proportional seats. After all, according to the interactive map, Labor “won” 26 of the constituencies (if I count correctly). As such, their performance is hard to interpret across the nation as a whole, because we have no idea what the actual percentages were in each constituency. All we know is that they did well.
Consider this situation: in constituency A, Labor gets 15%, the conservatives (TS-LKD) 14%, and the rest of the parties split the rest of the vote among themselves. In the map, it’s colored for Labor. Now, in constituency B, Labor got 30% of the vote, the conservatives got 35%, and the rest of the parties split the remaining votes. B is colored for the conservatives (green in the interactive map), but I think it would be rather interesting to know that Labor performed so strongly in that constituency.
I’d like to know how each party did independently among all the constituencies. That way we can see where their strongholds might be. To do this, I collected all the vote results and then compared each constituency’s performance against the national total for each party.
For example, the Labor Party received 19.84% of the vote of Lithuania as a whole. In the Pajūrio constituency along the coast, however, Labor received 16.61%. In the interactive map, the constituency is colored blue, despite the fact that the party received a smaller proportion of votes of the national result! Labor didn’t “win” anything here! They underperformed. They are colored blue only since the vote was generally extremely fractured, and 16.61% was the most a party could collect (the liberals were a percentage point behind them).
So I decided to create a map for each party that managed the 5% threshold. Each map shows how that party performed in every constituency against the national total. In my map, the Pajūrio constituency is colored light red, because Labor performed between -2.5% and -.5% worse than the national result. The darker red, the more a party underperformed. The darker blue, the more a party overperformed. White means they performed more or less in line with the national result. Click on each map to see the larger version of it.
As in that map, we see that Labor did very well throughout Aukštaitija. But we also see that they did reasonably well throughout the entire nation. They got killed in the three largest cities (Vilnius, Kaunas, and Klaipėda, as noted in the insets), and their support faded as they went toward the coast. As we’ll see, that’s the stronghold of the other main populist party, Order and Justice (Tvarka ir teisingumas).
Labor might likely enter into a coalition with the Social Democrats. Again, in the interactive map, it looks like they have strong support in Suvalkija, in the southwest. My map shows the same, but it also shows strong support nationwide, which explains why both they and Labor are atop the seat count, with 15 and 17 respectively. They also got killed in the major cities, but they dominated Šiauliai and did reasonably in Panevėžys. Most notably, they also got killed in Polish Lithuania (see below).
The third party in terms of seats were the conservatives, who collected 13 seats. In an election about change featuring the historically/hysterically unpopular Prime Minister Andrius Kubilius, it would make sense that his party gets slammed. And that’s what we see on the national scale. But where the countryside went for Labor and the Social Democrats, now we see that the two largest cities went hard for the conservatives. The city of Vilnius is a blue marble in a sea of resentful red.
Next up are the liberals (there are many liberals, but only the Liberal Movement received seats), who picked up seven seats. In the interactive map, the only hint we get that the liberals showed up was in Klaipėda. In my map, we see the truth of my comment in my previous post: everyone I know (and I only know city-dwellers) voted conservative or liberal. Just as with the conservatives, Vilnius and Kaunas are blue marbles surrounded by opposition. But now we also see how much support the Liberals have on the seaside, as well. Klaipėda is entirely dark blue, and the surrounding Gargždų constituency is also for the liberals.
Here I’ll pause for a moment for my American readers to wrap their heads around the idea that, in Lithuania, center-right parties do well in cities, while center-left parties do well in the countryside.
Well, that’s not entirely true, since the anti-government Drąsos kelias (Path of Courage), which emerged out of outrage at the government for not weeding out the pedophiles in their midst (I’m not kidding) received its strongest support in the outskirts of Kaunas. Of course, those very outskirts include the suburb of Garliava, which is where the incidents that led to the forming of the party occurred. They’re riding their outrage to seven seats as well.
Further complicating the idea of the center-left countryside, we see that the right-wing populist Order and Justice party, led by impeached president Rolandas Paksas, have their stronghold in Žemaitija, the area around Klaipėda. In the interactive map, they seem to only hold sway in the southern part of the region, but in this map, we see that their support is more widespread, which is why they managed six seats. Though they don’t have much support nationwide, we see the beginnings of a problem with this means of analysis: the party only received 7,31% of the national vote. As such, one might think it nearly impossible for a party getting only slightly more than 5% of the national vote to have sections that get colored dark red.
Well, one would think that as long as they don’t know about the one inviolate radical schism in Lithuanian politics: between Lithuanians and Poles. If one doesn’t know the history of the Vilnius region, especially during the interwar period, the map of the performance of the Polish Action should explain all. With 5.83% of the vote (good for five seats), the Polish Action is absolutely a non-entity in nearly the entire country. Yet they’re so strong in the Vilnius area that, despite receiving effectively no votes in the rest of the country, they still manage to do what 11 parties could not: seat members in Seimas based on proportional voting.
There remain problems with my analysis here: I rather arbitrarily chose the break points of -5%, -2.5%, -.5%, .5%, 2.5%, and 5% knowing ahead of time what the data would more or less look like. But it leads to less useful results especially in extreme cases, like the Polish Action. Using Jenks natural breaks, we get a better sense of how the Polish Action support is distributed around the area in Vilnius, for example. Furthermore, if a party gets, say, 50% of the vote, what does it matter if one constituency got them 56%? That difference is not as great as a party that got 2% of the vote nationwide but got 4% in one constituency. Though the total number of percentage points is smaller, it represents a doubling of the vote in comparison to the national total.
I figured it would be interesting to see, then, which parties over- and underperformed the national results. And might there be some parties whose fervid support is masked by the consensus seen in the maps above?
To answer this, I took each party’s percentage result in each constituency and averaged them for each party. This number is a bit different than the national result, but only by about a half a percentage point (and the difference decreases as the average approaches zero). I then compared each constituency’s performance as a factor of standard deviations above (or below) the mean. Two more maps were the result (and one really must click on these maps to see the large versions).
In the first map like this, which shows radical overperformers, we see that Labor’s stronghold is truly in the area just north of Kaunas. The Social Democrats are strong in Suvalkija, which makes sense, as their party leader, Algirdas Butkevičius, is from there. We see, furthermore, that the conservatives aren’t fervently supported anywhere in the country, outside of a region in Kaunas. Though they performed well in the national result, they never had the most excited support base. The lesser parties that received seats match more or less the results above: Order and Justice around Klaipėda, while the liberals are strongest on the coast, the Path of Courage as a strictly Kaunas affair, and the Polish Action surrounding Vilnius.
The results in Vilnius, though, deserve a bit of explication. First, we see the bright turquoise sliver in the middle. That’s the first constituency, Naujamiesčio. All voters registered abroad are bunched into that constituency, and that color corresponds to the Emigrant’s Party. We can see their support in other cities, as well: they are the most fervently supported party in both constituencies in Panevėžys and Alytus. Surrounding Naujamiesčio constituency are the desaturated greens of the Yes Association (Sąjunga Taip), the liberal breakaway party founded by Artūras Zuokas, the mayor of Vilnius. Abutting Vilnius to the east is the Naujosios Vilnios constituency, the home constituency of Algirdas Paleckis and, hence, a logical stronghold of his far-left Socialist People’s Front (Socialistinis liaudės Frontas). The rest of the map is interesting mostly if one can keep track of all the smaller parties in Lithuania, and I certainly can’t. As a final note, though, I’ll indicate the support the Peasants and Greens received around Šiauliai.
The second map, as the title suggests, shows where parties performed astonishingly weakly. Mostly, it shows two things we already knew: conservative and liberal support is exceptionally urban (noted by how frequently we see their colors in the countryside), and that Labor and the Social Democrats were wildly unpopular in the largest cities.
In closing, I have to add something about the efforts to make these maps. Unlike in the US, whose government hands out GIS datasets left and right, as far as I can tell, in Lithuania, the shapefile used in the interactive map is proprietary and belongs to the consultancy firm that makes the government’s maps for it. This is, in my opinion, profoundly fucked up. Not only did it delay the production of this post (as I spent all of yesterday hand-digitizing the inexact shapefile I used to make these maps—the inexactness of the shapes is why I’ve not made them interactive), but it’s just bad policy. Among the biggest problems I see in Lithuania is its knee-jerk pro-privatization (a relic of anti-communism, I’m certain), and the fact that I need to talk to a business in order to get data that the government should be collecting/providing (for free, even) is a catastrophe.