How Social Science Is Like Microbiology

I’m almost finished reading Michael Pollan’s latest, Cooked. It’s a terrific book about food, but it’s also steeped in science, and I wanted to share a passage from the part of the book on fermentation that really resonated with me. Pollan is writing about microbiology, but the developments he identifies in that field could (or should) apply just as well to the social sciences. The passage starts like this:

In the decades since Louis Pasteur founded microbiology, medical research has focused mainly on bacteria’s role in causing disease. The bacteria that reside in and on our bodies were generally regarded as either harmless “commensals”—freeloaders, basically—or pathogens to be defended against. Scientists tended to study these bugs one at a time, rather than as communities. This was partly a deeply ingrained habit of reductive science, and partly a function of the available tools. Scientists naturally focused their attention on the bacteria they see, which meant the handful of individual bugs that could be cultivated in a petri dish. There, they found some good guys and some bad guys. But the general stance toward bacteria we had discovered all around us was shaped by metaphors of war, and in that war, antibiotics became the weapon of choice.

Cholera_bacteria_SEMThe “habit of reductive science” Pollan describes should be familiar to social scientists, too. We often sort the objects of our analysis into binary categories of helpful and hurtful, assume the objects we see are all there really is, and then design interventions to try to kill the bad without harming the good. Where microbiology has traditionally drawn a sharp line between pathogens and cells that belong, social science has neatly distinguished rebel groups and criminal gangs and patronage networks from bureaucracies and political parties and civil society. Where medicine has antibiotics, development practitioners have aid.

What we’re now learning, though, is that these lines are really much blurrier than we’ve assumed. Pollan goes on:

But it turns out that the overwhelming majority of bacteria residing in the gut simply refuse to grow on a petri dish—a phenomenon known among researchers as “the great plate anomaly.” Without realizing it, they were practicing what is sometimes called parking-lot science—named for the human tendency to search for lost keys under the streetlights not because that’s where we lost them but because that is where we can best see. The petri dish was a streetlight. But when, in the early 2000s, researchers developed genetic “batch” sequencing techniques allowing them to catalog all the DNA in a sample of soil, say, or seawater or feces, science suddenly acquired a broad and powerful beam light that could illuminate the entire parking lot. When it did, we discovered hundreds of new species in the human gut doing all sorts of unexpected things.

This, to me, is the promise of what Gary King calls the “social science data revolution.” Exponential growth in the production and distribution of information to and from all parts of the world, and in our collective capacity to store and process and analyze that information, are to the social sciences what genetic batch sequencing is to microbiology. Our libraries and limited professional networks were our petri dishes, and now they’ve been shattered—in a good way.

Pollan then describes where microbiology’s version of the data revolution has led:

To their surprise, microbiologists discovered that nine of every ten cells in our bodies do not belong to us, but to these microbial species (most of them residents of our gut), and that 99 percent of the DNA we’re carrying around belongs to those microbes. Some scientists, trained in evolutionary biology, began looking at the human individual in a humbling new light: as a kind of superorganism, a community of several hundred coevolved and interdependent species. War metaphors no longer made sense. So the microbiologists began borrowing new metaphors from the ecologists.

I’d say a comparable gestalt shift is occurring in some corners of social science, with similarly dramatic implications. For decades, we’ve cranked out snapshots and diagrams and typologies of objects—states, parties, militaries, ethnic groups—that we’ve assumed to be more or less static and distinct and told just-so stories about how one thing changes into another. Now, we’re shedding those functionalist assumptions and getting better at seeing those objects as permeable superorganisms embedded in ecosystems, all of them continually coevolving in ways that may elude our capacity to narrate, or even to understand at all. The implications are simultaneously thrilling and overwhelming.

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.

Complexity Politics: Some Preliminary Ideas

As regular readers of this blog will know, I have become interested of late in applying ideas from complexity theory to politics. I’m hardly the first person to have this thought, but I’ve been surprised by how little published political science I’ve been able to find that goes beyond loose metaphors and really digs into the study of complex adaptive systems to try to explain specific macro-political phenomena.

To start thinking about how that might be done, I’ve been reading: Miller & Page on complex adaptive systems; Gould and Mayr on evolution; Kahneman on human cognition; Beinhocker on the economy; Ostrom on institutions; BatesFukuyama, and North, Wallis, & Weingast on the long course of political development; and Taleb on the predictability of unpredictability.

The single most-stimulating thing I’ve read so far is Eric Beinhocker’s The Origin of Wealth, which provides a thorough but accessible introduction to the principles of complex adaptive systems and then attempts to re-imagine the entirety of economics through that prism. Beinhocker dubs his reworked discipline Complexity Economics, so I thought I would borrow that phraseology and talk about Complexity Politics. Where Beinhocker asks, “Where does wealth come from, and why did it grow explosively in the past few hundred years?” I want to know: Where does government come from? Why does it take so many different forms, and why do those forms change over time? More specifically, why is democracy so prevalent nowadays? How long is that pattern going to last, and what comes next?

In the spirit of web logging circa 2003, I thought I would use this platform to sketch out a rough map of the terrain I’m trying to explore in hopes of stimulating conversation with other social scientists, modelers, and anyone else interested in the subject. Some of these probably won’t make sense to people who aren’t already familiar with complexity theory, but, hey, you can’t blame a guy for trying.

Anyway,  here in very loose order are some of the thoughts I’ve had so far.

1. Political systems aren’t “like” complex adaptive systems. They are complex adaptive systems, and those systems are embedded in a much larger system that “exists in the real physical world,” to borrow Beinhocker’s phrase. The human part of this larger system also encompasses the economy and non-economic forms of social interaction (like friendship), and the political part is not prior to, outside, or above the others, even if it sometimes aspires or claims to be. These various streams of human activity don’t just affect each other; they are all part of a single system in which human activity is embedded and is just one small part.

2. Political development doesn’t just resemble an evolutionary process. These systems are evolutionary systems, and political organization co-evolves with the economy and culture and the physical and biological environments in which all this behavior occurs. As a result, changes in physical and social technologies and the wider ecology of any of these other systems will affect politics, and vice versa.

3. In light of humans’ evolutionary trajectory, some form of hierarchical organization of our social activity is virtually inevitable, but that does not mean that the specific forms we see today were inevitable. The basic theme of organization for cooperation, and the never-ending tension between cooperation and conflict, may be “natural,” but the specific organizational expressions of these themes are not. There is no utopia or other optimal form, just an unending process of variation, replication, and selection.

4. In the human portion of this system, governments are the political equivalent of firms in the economy—organizations that bring together multiple “businesses” in pursuit of some wider goal(s). There is a great deal of isomorphism in which “businesses” governments pursue, but, as the unending arguments in American politics over the proper purpose and size of government show, this debate is not settled. In other words, there is no natural or obvious answer to the question, “What do governments do?”

5. So what is government, anyway? The defining feature of government as a social technology is the claim to the authority to make rules affecting people who are not parties to the rule-making process. Economic exchange is based on trade or contracts, both of which involve all parties choosing “freely” to make the exchange. Governments, by contrast, are defined by their assertion of the authority to compel behavior by all individuals of a certain class. In the system of government that has developed so far, the relevant classes are defined primarily by territory, but this is not the only structure possible.

6. The defining features of government are: a) procedures for selecting rule-makers, b) procedures for making rules, c) some capacity to implement those rules, and d) some capacity to enforce those rules. Variation in the form (and therefore fitness) of governments occurs along these four dimensions, each of which has many components and sub-components that also vary widely (e.g., electoral systems in democracies).

7. Because they must enforce the rules they make, all governments depend to some extent on coercion. In this sense, all governments depend on people skilled in violence, and on physical technologies—including weapons—that enable monitoring and enforcement. As relevant physical technologies emerge and evolve, governments will often evolve with them.

8. States are a particular form of government connected to the contemporary organization of politics at the global level. (I wrote more about that here.) As Edward Carr wrote in a recent blog post, however, “Many of the global poor live beyond the reach of the state.” In other words, states are just one part of the global political landscape, and all social behavior within their borders does not necessarily fall under their hierarchical structures. It’s really a matter of degree, and for a non-trivial proportion of the human population, the degree is approximately zero. On this point, see also Steve Inskeep’s work on cities in “developing” countries.

9. The economy, by contrast, is effectively ubiquitous in human society. This means that efforts to understand the emergence and evolution of government should presume that governments emerged to serve economic ends and not vice versa. Once government emerged as a social technology, path dependence kicked in, and the two began co-evolving. But the economic roots of government should not be ignored. You can’t explain or understand politics without reference to the economy.

10. Governments operate on many different geographic scales. The presumption (or assertion) by many actors at the national and international scale is that governments at these different levels are nested in a clear hierarchy: local, regional, national. In practice, though, these organizations often don’t operate that way, and the array of governments around the world is really interconnected through a mixture of hierarchical and dense networks that often overlap.

11. Once the social technology of government had emerged, it began to evolve, too. Evolution involves variation, selection, and replication. Adaptation occurs as selection and replication amplify fitter variations. In political space, rules are the building blocks, governments are the “readers” that give form to different arrangements of rules, and institutions are the results on which selection pressures act. As with other social technologies, change primarily occurs through human agency, some of it with clear intention and some of it more experimental. Mutations may also occur as a result of ambiguities inherent in language.

12. Regime types are like species. They aren’t crisp categories so much as recognizable peaks in multidimensional space defined by possible combinations of political DNA. One implication of this observation is that we may get better insights from inductive scans of this multidimensional space than we do from efforts to match real-world cases to deductively defined ideal types. After all, those deductively defined forms are just ideas, and those ideas are just another stream in the same co-evolving system.

13. Like anything else, forms of government vary in their fitness, and fitness is always situational. The evolution of forms of government should follow the usual patterns of s-curves and punctuated equilibria. There will be periods of relative stability in the system when specific combinations with a fitness edge will come to dominate, and there will be periods of rapid change when lots of experimentation and churn will occur. During the more stable phases, hedgehog-like forms that do the “fit” things well will predominate. During periods of phase shift, fox-like organizations that internalize experimentation will survive more readily.

14. Re (13), it’s unclear if democracy is the former or the latter, but I’m inclined to see it as the latter. The last 200 years have been a period of rapid change in human society, and democracy is proliferating because it is fitter than authoritarian rule in this highly uncertain environment. If that’s right, then we would expect to see something other than democracy come to dominate the political landscape whenever this period of phase shift comes to an end. I have no idea when that might be or what the world will look like when that happens, and therefore I have no idea what organizational forms might be fitter in that new era.

15. Ditto for territoriality as the basis for defining the boundaries of governments as political organizations. To imagine what a non-territorial form of political organization might look like, we can consider possibilities for political organization in cyberspace. As more and more exchange migrates to cyberspace, pressures to organize in that domain will increase. States are currently trying to maintain control of that process, and their efforts to do so are facilitated by the dependency of cyberspace on a physical infrastructure. If and when that infrastructure becomes sufficiently non-hierarchical and resilient, I expect we’ll see the center of gravity for governance shift to that (non-territorial) domain. The physical element of coercion will keep territoriality relevant, but there are ways other than direct violence to coerce (e.g., delete bank accounts, revoke accesses or permissions, block signals), and developments in physical technologies (e.g., remotely operated weapons) may also make territoriality less relevant.

16. One of the few “laws” of political behavior is Michel’s Iron Law of Oligarchy, which implies that political organizations invariably become more bureaucratic and self-protective as they grow and gain power. Any attempt to trace political development through the lens of complex adaptive systems needs to show how this pattern emerges from the process. It’s easy to imagine a connection between this pattern and things like loss aversion and the biological drive to dominate reproduction, but it would be useful to see if we can induce the emergence of this pattern from agent-based models with realistic simplifying assumptions.

So that’s where I’m starting from. I hope to dig deeper into some of these ideas in future blog posts. Meanwhile, if you have any reactions or you can point me toward relevant books or articles, please leave a comment or send me an email.

An Evolutionary Theory of Political Development

The overall framework for understanding political development presented here bears many resemblances to biological evolution. Darwinian evolution is built around the two principles of variance and selection: organisms experience random genetic mutations, and those best adapted to their environments survive and multiply. So too in political development: there is variation in political institutions, and those best suited to the physical and social environment survive and proliferate. But there are also many important differences between biological and political evolution: human institutions are subject to deliberate design and choice, unlike genes; they are transmitted across time culturally rather than genetically; and they are invested with intrinsic value through a variety of psychological and social mechanisms, which makes them hard to change. The inherent conservatism of human institutions then explains why political development is frequently reversed by political decay, since there is often a substantial lag between changes in the external environment that should trigger institutional change, and the actual willingness of societies to make those changes.

In the end, however, this general framework amounts to something less than a predictive theory of political development. A parsimonious theory of political change, comparable to the theories of economic growth posited by economists, is in my view simply not possible. The factors driving the development of any given political institution are multiple, complex, and often dependent on accidental or contingent events. Any causal factors one adduces for a given development are themselves caused by prior conditions that extend backward in time in an endless regression.

That’s Francis Fukuyama on pages 22-23 in Part I of his magnum opus in progress, The Origins of Political Order. As a framework for thinking about the process of political development over the long haul, I think this passage gets a lot of things right. It contrasts sharply with teleological approaches, including modernization theory and Marxism, which assume political development has a specific destination. Modernization theory in particular seems to help explain a broad trend toward representative government over the past half-century, but it does a poor job of explaining divergences or digressions from that trend, and it tells us nothing about previous and future epochs in political development. Fukuyama’s framework also contrasts with simple functionalist theories, which imply that institutions are tidy solutions to specific political or economic problems. As Fukuyama notes (p. 9), “There is no automatic mechanism by which political systems adjust themselves to changing circumstances.”

Last but not least, I think Fukuyama is on to something fundamental when he talks about the ways that specific aspects of human nature and culture combine with accidents of history to produce distinct trajectories in the process of institutional change. As he says in the book’s Preface (p. x),

Countries are not trapped by their pasts. But in many cases, things that happened hundreds or even thousands of years ago continue to exert a major influence on the nature of politics. If we are seeking to understand the functioning of contemporary institutions, it is necessary to look at their origins and the often accidental and contingent factors that brought them into being.

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