A Rumble of State Collapses

The past couple of years have produced an unusually large number of collapsed states around the world, and I think it’s worth pondering why.

As noted in a previous post, when I say “state collapse,” I mean this:

A state collapse occurs when a sovereign state fails to provide public order in at least one-half of its territory or in its capital city for at least 30 consecutive days. A sovereign state is regarded as failing to provide public order in a particular area when a) an organized challenger, usually a rebel group or regional government, effectively controls that area; b) lawlessness pervades in that area; or c) both. A state is considered sovereign when it is granted membership in the U.N. General Assembly.

The concepts used in this definition are very hard to observe, so I prefer to make probabilistic instead of categorical judgments about which states have crossed this imaginary threshold. In other words, I think state collapse is more usefully treated as a fuzzy set instead of a crisp one, so that’s what I’ll do here.

At the start of 2011, there was only state I would have confidently identified as collapsed: Somalia. Several more were plausibly collapsed or close to it—Afghanistan, Central African Republic (CAR), and Democratic Republic of Congo (DRC) come to mind—but only Somalia was plainly over the line.

By my reckoning, four states almost certainly collapsed in 2011-2012—Libya, Mali, Syria, and Yemen—and Central African Republic probably did. That’s a four- or five-fold increase in the prevalence of state collapse in just two years. In all five cases, collapse was precipitated by the territorial gains of armed challengers. So far, only three of the five states’ governments have fallen, but Assad and Bozize have both seen the reach of their authority greatly circumscribed, and my guess is that neither will survive politically through the end of 2013.

I don’t have historical data to which I can directly compare these observations, but Polity’s “interregnum” (-77) indicator offers a useful (if imperfect) proxy. The column chart below plots annual counts of Polity interregnums (interregna? interregni? what language is this, anyway?) since 1945. A quick glance at the chart indicates that both the incidence and prevalence of state collapse seen in the past two years—which aren’t shown in the plot because Polity hasn’t yet been updated to the present—are historically rare. The only comparable period in the past half-century came in the early 1990s, on the heels of the USSR’s disintegration. (For those of you wondering, the uptick in 2010 comes from Haiti and Ivory Coast. I hadn’t thought of those as collapsed states, and their addition to the tally would only make the past few years look that much more exceptional.)

Annual Counts of Polity Interregnums, 1946-2010

Annual Counts of Polity Interregnums, 1946-2010

I still don’t understand this phenomenon well enough to say anything with assurance about why this “rumble” of state collapses is occurring right now, but I have some hunches. At the systemic level, I suspect that shifts in the relative power of big states are partly responsible for this pattern. Political authority is, in many ways, a confidence game, and growing uncertainty about major powers’ will and ability to support the status quo may be increasing the risk of state collapse in countries and regions where that support has been especially instrumental.

Second and related is the problem of contagion. The set of collapses that have occurred in the past two years are clearly interconnected. Successful revolutions in Tunisia and Egypt spurred popular uprisings in many Arab countries, including Libya, Syria, and Yemen . Libya’s disintegration fanned the rebellion that precipitated a coup and then collapse in Mali. Only CAR seems disconnected from the Arab Spring, and I wonder if the rebels there didn’t time their offensive, in part, to take advantage of the region’s   current distraction with its regional neighbor to the northwest.

Surely there are many other forces at work, too, most of them local and none of them deterministic. Still, I think these two make a pretty good starting point, and they suggest that the current rumble probably isn’t over yet.

What Darwin Teaches Us about Political Regime Types

Here’s a paragraph, from a 2011 paper by Ian Lustick, that I really wish I’d written. It’s long, yes, but it rewards careful reading.

One might naively imagine that Darwin’s theory of the “origin of species” to be “only” about animals and plants, not human affairs, and therefore presume its irrelevance for politics. But what are species? The reason Darwin’s classic is entitled Origin of Species and not Origin of the Species is because his argument contradicted the essentialist belief that a specific, finite, and unchanging set of categories of kinds had been primordially established. Instead, the theory contends, “species” are analytic categories invented by observers to correspond with stabilized patterns of exhibited characteristics. They are no different in ontological status than “varieties” within them, which are always candidates for being reclassified as species. These categories are, in essence, institutionalized ways of imagining the world. They are institutionalizations of difference that, although neither primordial nor permanent, exert influence on the futures the world can take—both the world of science and the world science seeks to understand. In other words, “species” are “institutions”: crystallized boundaries among “kinds”, constructed as boundaries that interrupt fields of vast and complex patterns of variation. These institutionalized distinctions then operate with consequences beyond the arbitrariness of their location and history to shape, via rules (constraints on interactions), prospects for future kinds of change.

This is one of the big ideas to which I was trying to allude in a post I wrote a couple of months ago on “complexity politics”, and in an ensuing post that used animated heat maps to trace gross variations in forms of government over the past 211 years. Political regime types are the species of comparative politics. They are “analytic categories invented by observers to correspond with stabilized patterns of exhibited characteristics.” In short, they are institutionalized ways of thinking about political institutions. The patterns they describe may be real, but they are not essential. They’re not the natural contours of the moon’s surface; they’re the faces we sometimes see in them.

video game taxonomy

Mary Goodden’s Taxonomy of Video Games

If we could just twist our mental kaleidoscopes a bit, we might find different things in the same landscape. One way to do that would be to use a different set of measures. For the past 20 years or so, political scientists have relied almost exclusively on the same two data sets—Polity and Freedom House’s Freedom in the World—to describe and compare national political regimes in anything other than prose. These data sets are very useful, but they are also profoundly conventional. Polity offers a bit more detail than Freedom House on specific features of national politics, but the two are essentially operationalizing the same assumptions about the underlying taxonomy of forms of government.

Given that fact, it’s hard to see how further distillations of those data sets might surprise us in any deep way. A new project called Varieties of Democracy (V-Dem) promises to bring fresh grist to the mill by greatly expanding the number of institutional elements we can track, but it is still inherently orthodox. Its creators aren’t trying to reinvent the taxonomy; they’re looking to do a better job locating individuals in the prevailing one. That’s a worthy and important endeavor, but it’s not going to produce the kind of gestalt shift I’m talking about here.

New methods of automated text analysis just might. My knowledge of this field is quite limited, but I’m intrigued by the possibilities of applying unsupervised learning techniques, such as latent Dirichlet allocation (LDA), to the problem of identifying political forms and associating specific cases with them. In contrast to conventional measurement strategies, LDA doesn’t oblige us to specify a taxonomy ahead of time and then look for instances of the things in it. Instead, LDA assumes there is an infinite mixture of overlapping but latent categories out there, and these latent categories are partially revealed by characteristic patterns in the ways we talk and write about the world.

Unsupervised learning is still constrained by the documents we choose to include and the language we use in them, but it should still help us find patterns in the practice of politics that our conventional taxonomies overlook. I hope to be getting some funding to try this approach in the near future, and if that happens, I’m genuinely excited to see what we find.

211 Years of Political Evolution in 60 Seconds — New and Improved!!

The heat maps used in the animation I posted yesterday plotted change over time in counts of countries in each cell of a two-dimensional space representing different kinds of politcal institutions. Over the 211 years in question, however, the number of countries in the world has grown dramatically, from about 50 in 1800 to well over 150 in 2011. For that reason, a couple of commenters wondered whether we would see something different if we plotted proportions instead of counts, using the size of the total population as a denominator in each cell. Proportions better fit the ideas behind a fitness landscape, so I added a line to my code and gave it a whirl. Here’s what I got:

To my eye, there aren’t any big differences in the patterns we see here compared with the ones based on counts. Re-watching the animation today, though, here are a few other things that caught my attention:

  • The predominance in the mid-1800s of intermediate forms combining authoritarian selection with highly polarized political participation—what Polity calls “factionalism.” This peak in the middle left of the heat maps shows how popular mobilization generally led to competitive elections, and not the other way around. As historian Sean Wilenz wrote, “Democracy is never a gift bestowed…It must always be fought for.” It also reminds us that popular mobilization was initially quite polarized in the “developed” world (ha!), just as it often is poorer countries today.
  • The wide variety of intermediate forms present in the early 1900s. Here we see a bunch of cases in the upper left-hand quadrant, combining authoritarian selection procedures with open and well-regulated participation. This is a combination we almost never see nowadays. It looks like there were some interesting experiments occurring in the wake of the industrial explosion that occurred in richer countries in the latter half of the nineteenth century.
  • The sharp bifurcation of the fitness landscape after World War II. Before the war, the peak in the lower left-hand corner representing closed dictatorships had shrunken, and there seemed to be more action in the upper left and lower right quadrants. After the war, the peak in the lower left rose again and remained there until around 1990. This pattern makes clearer that the evolution of the past two centuries has not been a steady march toward democracy. It’s interesting—and potentially chilling—to contemplate how much the fitness landscape of the past 70 years might have differed had World War II taken different turns.

211 Years of Political Evolution in 60 Seconds

The GIF below—click on it to make it play—animates a series of 211 heat maps summarizing annual data on national political regimes around the world from 1800 to 2010. The space in the heat maps represents two of the “concept” variables from the Polity IV data set—executive recruitment and political competition—that roughly correspond to the dimensions of contestation and participation Robert Dahl uses to define modern regime types. In the animated maps, the lower left is least democratic, and the upper right is most democratic. The darker the grey, the higher the number of cases in that cell. [NB. For a version that uses proportions instead of raw counts and some additional thoughts on patterns over time, see this short follow-up post.]

[Fellow propeller-heads: I built this in R with helpful suggestions from Trey Causey and Tom Parris along the way. The heat maps were made with a function appropriately called 'heatmap', and I used the 'animation' package to compile those images into a .gif. Ping me if you'd like to see the script.]

I made this animation because I think it supports the idea, discussed briefly in my last post, that political development is an evolutionary process. Evolutionary processes feed on diversity and mutation, but the results of evolution are not randomly distributed. Borrowing from Daniel Dennett, we can imagine evolution occurring in a multidimensional design space that contains all possible combinations of a particular set of building blocks. In biology, those building blocks are genes; in politics, they might be simple rules.

For present purposes, let’s imagine that there are only two dimensions in this design space. Those two dimensions suggest a map of the design space that evolutionary biologists call a fitness landscape. The topography of this landscape is determined by the fitness of specific combinations, as indicated by sizes of the relevant populations. That’s what the heat maps in the animation above are showing.

The existence of the system is a matter of chance, but once an evolutionary system emerges, we can expect to see certain patterns. The selection pressures present in any particular environment mean that some combinations will be fitter than others, producing visible and often durable peaks in that fitness landscape. Mutation—and, in the case, of social technologies like government, deliberate tinkering—will keep producing new varieties, but most won’t be fit enough for the environment of the day to survive and spread. As a result, most of the variation will cluster around the existing peaks, because small differences in design will often (but not always!) produce small differences in fitness.

When selection pressures change, however, the designs embodied in the previous peaks will often become less fit, and new designs will emerge as stronger competitors. Importantly, though, that transition from the old peaks to new ones usually won’t be smooth and direct. Instead, as Niles Eldredge and Stephen Jay Gould describe in their model of punctuated equlibrium, we can expect to see bursts of diversity as the evolutionary engine “searches” for new forms that better fit the changing environment. As the selection pressures settle into a new normal, the fitness landscape should also settle back into the familiar pattern of clearer peaks and valleys.

The two Polity variables used here are, of course, gross and conceptually biased simplifications of complex phenomena. Underlying each of these dimensions are a few component variables that are themselves simplifications of complex sets of written and unwritten rules. Still, the Polity data are the best we’ve got right now for observing change in over a long period of time, and it’s pretty hard for us humans to visualize four- or seven- or thirty-dimensional space. So, for now, I’m using these two summary indices to get a very rough map of the design space for modern political institutions.

Maybe it’s confirmation bias at work, but when I watch the animation above, I see the patterns evolutionary theorists tell me I should see. In 1800, the fitness landscape is dominated by a single peak representing highly undemocratic regimes—mostly monarchies with virtually no popular participation. If we could extend the movie back several more centuries, we would see the same pattern holding through the entirety of human civilization since our hunter-gatherer days.

Pretty soon after we drop in to watch, however, things start to move. In the early 1800s, a couple of new lumps rise as popular participation expands in some regimes. Most countries still select their rulers by hereditary lineage or other closed means (the peak in the middle left), but some start using competitive elections to pick their governments. By the late nineteenth century, a second peak has clearly emerged in the upper right-hand corner, where rulers are chosen through competitive elections with broad participation. [NB: I think Polity rushes things a bit here by ignoring the disenfranchisement of women, but we go to publish with the data we've got, not the data we'd like.]

Through most of the twentieth century, the same general pattern holds. There’s a fair amount of variation, but most regimes are concentrated in the same few patches of the design space. At the end of the twentieth and start of the twenty-first centuries, however, we see a burst of diversity. The authoritarian peak shrinks, the democratic peak holds, and large swathes of the design space that have rarely been occupied bubble with activity.

To my eye, this very recent phase looks like one of Eldredge and Gould’s punctuation marks, that is, an episode of heightened diversity caused by a significant shift in selection pressures. Most observers of international politics won’t be surprised to see this pattern, and many of them would probably attribute it to the end of the Cold War. I’m not so sure. I’m more inclined to see the collapse of the Soviet Union and the expansion in the diversity of political forms as twin consequences of deeper changes in the global system that seem to be favoring democratic forms over authoritarian ones. What new peaks we’ll see when the system settles down again—and on what heretofore hidden dimensions of political design space they might draw—is impossible to know, but it sure is fascinating to watch.

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