More on what can be explained

A previous posting argued that most social facts don't admit of social explanation because they are too fundamentally conjunctural or too boringly ordinary. Let's extend this thought by considering what sorts of social facts do admit of explanation.

One obvious category is the example of a perplexing mid-range social regularity. Why do used cars usually sell for less than their "real" value? Because of the asymmetry of information between buyer and seller (the market for lemons). Why does ethnic conflict turn violent more commonly in circumstances where the institutions of civil society are weak? Because weak civil institutions undermine trust between distinct intermixed groups. (Here is a posting summarizing some recent thinking on this connection between civil society and ethnic violence.) Why do collectivized farms usually witness lower labor productivity than privately owned farms? Because of some common features of labor management and supervision that are usually a part of collective farm practices but not of private farm practices, that are likely to result in individual effort that is of lower quality or intensity than the private alternative. (This is sometimes referred to as the "easy-rider" problem.)

This category encompasses cases of non-trivial regularity. These are all examples of what I call "phenomenal" social regularities. They are not manifestations of some underlying set of social laws, but rather the common results of a set of mechanisms or processes in a range of cases (article). In each case the explanation proceeds by identfying a common but non-obvious mechanism or structural feature that produces the observed outcome.

Another important category of social phenomena demanding explanation is the large, complex social occurrence. (William Sewell calls these "events" -- historical occurrences that are "irreversible, contingent, uneven, discontinuous and transformational" (link). ) Here I have in mind things such as the great Pullman strike of 1894, the defeat of France in the Franco-Prussian War in 1870, the civil war in Lebanon in the 1980s, the Rwandan genocide, or the selection of alternating over direct current electricity transmission systems. In each case we want to know why the event occurred -- the event is important and obscure -- and it is credible that there may be a small number of social mechanisms and circumstances that can be discovered and that brought about the event.

So explanation of these singular but extended events takes the form of a causal narrative that turns on a small number of important causal factors or mechanisms. The burden of explanation is to discover the mid-level social processes and mechanisms that caused the outcome to occur. And a feature of generalization comes into this account as well, but at a different point in the story: to say that P caused O in the circumstances is also to imply that P would have similar effects in similar circumstances in other settings.

So the idea of a social regularity comes into this discussion twice. First, we are often led to ask for an explanation when we observe a curious regularity -- instances of similar behaviors or outcomes in separate cases. "Why does this weak regularity obtain across independent cases?" And second, the type of explanation highlighted here is a causal explanation, which implies assertions about counterfactual regularities. "The outcome occurs because of the regular causal powers of such-and-so a causal mechanism." A factor that possesses the causal power to help bring about a certain kind of effect plainly plays a role in statements like this: "whenever P occurs in circumstances substantially similar to C, O is likely to occur." And this is a statement of an idealized regularity. This in turn lends some support for the idea that explanation and the discovery of a level of social generalization are linked -- but not in the way that the nomological-deductive model of explanation would imply.

(See Varieties of Social Explanation for other perspectives on these questions.)

How much of social life can be explained?

How much of social life can be explained?

It may sound like a strange question -- surely everything can be explained! And it's true that nothing that occurs is "inexplicable". But consider this homely example: if I spill my coffee on the desk, is there a scientific explanation of the particular shape that the splash of liquid takes? The final configuration of liquid on the desk is fully governed by physical laws and existing conditions; but chance and contingency play a critical role in the flow and splash of liquid as it moves into equilibrium. Some facts about the final equilibrium can be explained and predicted -- the flat surface and shallow depth, for example. But the particular configuration of the radiating arms of the spill is highly contingent. So we might say that the depth of the pool has a scientific explanation but the shape does not.

Now bring the focus back to the social. The social universe contains a great deal of stuff that is random, chaotic, and conjunctural. Social outcomes are path-dependent: later events often depend critically on circumstances that occurred earlier in time. And this means that outcomes may be decisively shaped by accidental and ideographic events that occurred in the past.

Take collective behavior. In analogy to the coffee spill, we might be in a position to explain the behavior of each person in a crowd -- and it may still be true that there is no explanation of the behavior of the group as a whole. (Maybe that is suggested by the beach crowd scene above.) Sometimes there is a salient explanation of group behavior, and sometimes there is not. And we might want to say that any social outcome that is random or depends primarily on a random concatenation of causes, cannot be explained but merely retraced. We can provide a narrative but not an explanation.

In fact, for a wide range of social phenomena, the outcome is simply the resultant of many small influences, and there is no salient reason for this particular outcome. There had to be some result, and the observed result is no more distinguished than any of the other possible outcomes. If the best causal story we can provide depends on unvarnished coincidence, then it seems reasonable to say that there is no explanation of this particular fact.

The most interesting social explanations arise when:

There is a large social trend or event that surprises us (change or unexpected persistence) and there is a previously unobserved factor that can be demonstrated to have caused the trend. Crudely, we might say that an outcome or pattern has an explanation just in case we have reason to believe there is a major causal factor that produces the pattern or outcome.

There appear to be a couple of pragmatic features to this question about whether something is amenable to scientific explanation. (This raises the question of the pragmatics of explanation in contrast to the logic of explanation.) First, it appears that there an implicature, in asking for an explanation of X, that X is unexpected. If so, there is an implication of contrast: contrary to the usual situations where X does not occur, X occurred on this instance. What caused X to occur? What factor in the situation led to the surprising outcome now? And second, there is the pragmatic preference for large and general factors rather than local and particular factors to serve as explanations.

So we might test out this idea: the proportion of social events that permit substantive scientific explanations is very low. Most social events are routine and expected, and they are the resultant of a large number of unimportant influences. And if either condition is present, then we might say that the event lacks an explanation.

Chaos and coordination in social life

Much social behavior is chaotic, in that it simply emerges from the independent choices of numerous agents during a period of time. It is analogous to Brownian motion -- particles in a liquid moving in random motions as a result of innumerable bumps and pushes at the molecular level.

However, there are also many patterns that become visible in social behavior -- examples of what I would like to call "coordinated social action": stock market panic selling, holiday travel, rumors, style, riots, pickpockets in train stations. And we can identify many causes of coordination of individual behavior into larger patterns: commands, regulations, institutions, customs, conventions, collective plans, shared beliefs about social behavior, common sources of information, and common changes in the environment of choice, for example.

What I mean by "coordination" here is the opposite of chaos -- something analogous to the coherence of photons associated with the laser effect. In a laser a set of photons are stimulated to fire coherently with each other, resulting in a beam of light that possesses focus and parallel propagation that is different in kind from the scattered diffusion of photons from an incandescent bulb. "Coordinated" social action is a set of actions that possess synchronicity or regularity in their occurrence, resulting in an observable regularity of behavior over time and space. A crucial problem for social inquiry is to provide an explanation of the mechanisms that underlie the instances of coordinated social action that we can identify.

Examples of coordinated social action can easily be offered, and specific mechanisms can be identified that produce these forms of social coordination. An army moves in concert across a landscape (command). People drive on the right in North America (regulation). People send their children to school (institution). People greet each other with a polite "good morning" (custom). Villagers come together to fish as a group in the morning (convention). People discuss a spontaneous demonstration in front of the mayor's office on Wednesday, and many appear (collective plans). Drivers choose Route 3 rather than Route 1 because they expect a lot of traffic on Route 1 (shared beliefs). People buy a large number of batteries and chocolate, anticipating an approaching hurricane (common environmental change).

These are all mechanisms that create a degree of coordination or synchronization of behavior among independent agents. There seem to be several large categories of mechanisms here: hierarchical coordination (command, regulation); common response coordination (each individually responds to the same signal); communications and network coordination (individuals exchange messages to secure coordination); and strategic coordination (each intends to behave in a way that will be desirable given his/her expectation of actions by others). Might we try out the thought that all forms of regularities of social behavior derive from one or another of these forms of coordination? This thought is probably somewhat too strong a claim. For example, there are probably social regularities that derive from our biology and evolutionary histories -- limitations of memory, bonds of intra-group loyalty, kin altruism. But the impulse is a sound one: when we are able to observe patterns of social behavior, there must be a cause of those regularities that works its way through influence on the individual actors who constitute the domain of action. And there are only so many mechanisms that might serve.

These sorts of regularities and mechanisms constitute part of the regularity of social life, but perhaps only part. It may be that they don't capture other kinds of more "structural" regularities -- for example, "racial discrimination increases health disparities," "feudal political systems are slow to respond to external aggression", "capitalist market systems are more innovaative than planned economies". But there is an important aspect of social explanation that centers exactly on this question: what are the social mechanisms that bring a degree of coherence and coordination among the actions of a population of independent actors?

Agent-based modeling as social explanation

Logical positivism favored a theory of scientific explanation that focused on subsumption under general laws. We explain an outcome by identifying one or more general laws, a set of boundary conditions, and a derivation of the outcome from these statements. A second and competing theory of scientific explanation can be called "causal realism." On this approach, we explain an outcome by identifying the causal processes and mechanisms that give rise to it. And we explain a pattern of outcomes by identifying common causal mechanisms that tend to produce outcomes of this sort in circumstances like these. (If we observe that patterns of reciprocity tend to break down as villages become towns, we may identify the causal mechanism at work as the erosion of the face-to-face relationships that are a necessary condition for reciprocity.)

But there are other approaches we might take to social explanation and prediction. And one particularly promising avenue of approach is "agent-based simulation." Here the basic idea is that we want to explain how a certain kind of social process unfolds. We can take our lead from the general insight that social processes depend on microfoundations at the level of socially situated individuals. Social outcomes are the aggregate result of intentional, strategic interactions among large numbers of agents. And we can attempt to implement a computer simulation that represents the decision-making processes and the structural constraints that characterize a large number of interacting agents.

Thomas Schelling's writings give the clearest exposition to the logic of this approach Micromotives and Macrobehavior. Schelling demonstrates in a large number of convincing cases, how we can explain large and complex social outcomes, as the aggregate consequence of behavior by purposive agents pursuing their goals within constraints. He offers a simple model of residential segregation, for example, by modeling the consequences of assuming that blue residents prefer neighborhoods that are at least 50% blue, and red residents prefer neighborhoods at least 25% red. The consequence -- a randomly distributed residential patterns becomes highly segregated in an extended series of iterations of individual moves.

It is possible to model various kinds of social situations by attributing a range of sets of preferences and beliefs across a hypothetical set of agents -- and then run their interactions forward over a period of time. SimCity is a "toy" version of this idea -- what happens when a region is developed by a set of players with a given range of goals and resources? By running the simulation multiple times it is possible to investigate whether there are patterned outcomes that recur across numerous timelines -- or, sometimes, whether there are multiple equilibria that can result, depending on more or less random events early in the simulation.

Robert Axelrod's repeated prisoners' dilemma tournaments represent another such example of agent-based simulations. (Axelrod demonstrates that reciprocity, or tit-for-tat, is the winning strategy for a population of agents who are engaged in a continuing series of prisoners' dilemma games with each other.) The most ambitious examples of this kind of modeling (and predicting and explaining) are to be found in the Santa Fe Institute's research paradigm involving agent-based modeling and the modeling of complex systems. Interdisciplinary researchers at the University of Michigan pursue this approach to explanation at the Center for the Study of Complex Systems. (Mathematician John Casti describes a number of these sorts of experiments and simulations in Would-Be Worlds: How Simulation is Changing the Frontiers of Science and other books.)

This approach to social analysis is profoundly different from the "subsumption under theoretical principles" approach, the covering-law model of explanation. It doesn't work on the assumption that there are laws or governing regularities pertaining to the social outcomes or complex systems at all. Instead, it attempts to derive descriptions of the outcomes as the aggregate result of the purposive and interactive actions of the many individuals who make up the social interaction over time. It is analogous to the simulation of swarms of insects, birds, or fish, in which we attribute very basic "navigational" rules to the individual organisms, and then run forward the behavior of the group as the compound of the interactive decisions made by the individuals. (Here is a brief account of studies of swarming behavior.)

How would this model of the explanation of group behavior be applied to real problems of social explanation? Consider one example: an effort to tease out the relationships between transportation networks and habitation patterns. We might begin with a compact urban population of a certain size. We might then postulate several things:

• The preferences that each individual has concerning housing costs, transportation time and expense, and social and environmental environmental amenities.
• The postulation of a new light rail system extending through the urban center into lightly populated farm land northeast and southwest
• The postulation of a set of prices and amenities associated with possible housing sites throughout the region to a distance of 25 miles
• The postulation of a rate of relocation for urban dwellers and a rate of immigration of new residents

Now run this set of assumptions forward through multiple generations, with individuals choosing location based on their preferences, and observe the patterns of habitation that result.

This description of a simulation of urban-suburban residential distribution over time falls within the field of economic geography. It has a lot in common with the nineteenth-century von Thunen's Isolated State analysis of a city's reach into the farm land surrounding it. (Click here for an interesting description of von Thunen's method written in 1920.) What agent-based modeling adds to the analysis is the ability to use plentiful computational power to run models forward that include thousands of hypothetical agents; and to do this repeatedly so that it is possible to observe whether there are groups of patterns that result in different iterations. The results are then the aggregate consequence of the assumptions we make about large numbers of social agents -- rather than being the expression of some set of general laws about "urbanization".

And, most importantly, some of the results of the agent-based modeling and modeling of complexity performed by scholars associated with the Santa Fe Institute demonstrate the understandable novelty that can emerge from this kind of simulation. So an important theme of novelty and contingency is confirmed by this approach to social analysis.

There are powerful software packages that can provide a platform for implementing agent-based simulations; for example, NetLogo. Here is a screen shot from an implementation called "comsumer behavior" by Yudi Limbar Yasik. The simulation has been configured to allow the user to adjust the parameters of agents' behavior; the software then runs forward in time through a number of iterations. The graphs provide aggregate information about the results.

Collective behavior and resource mobilization theory

The study of collective behavior and social movements has been a central sub-discipline of sociology since the 1970s. This is understandable for several reasons -- first, because collective behavior is inherently an important sociological process, and second, because the 1960s and 1970s witnessed particularly significant social movements in the US and other parts of the world. The US civil rights movement, the Vietnam anti-war movement, Czechoslovakia and France in 1968, and a variety of anti-colonial struggles in Asia, Latin America, and Africa made social movements particularly salient for sociologists in the 70s and 80s.

There are several different kinds of research questions that can be posed about social movements. One line of inquiry is descriptive and ethnographic. Researchers could immerse themselves in the concrete details of specific examples of social movements, discovering some of the specific characteristics and processes that were to be found in specific examples. Moreover, researcher could recognize the importance of failure and provide a similar level of description and narrative for failed social movements as well. This kind of descriptive research is very important in the study of any complex social phenomenon.

Second, given the interest that sociologists have in the explanation of social processes, it would be natural for sociologists to attempt to discover the causes of successful social mobilization. Comparative sociologists might approach this task by trying to discover some macro-social factors that would appear to distinguish successful from unsuccessful mobilizations. In other words, they might isolate a handful of examples of successful and unsuccessful social movements, and then use sociological theory and imagination to identify a set of macro-factors that might be thought to be conducive to (or inhibiting of) successful social mobilization. This strategy suggests use of Mill's methods to sort out necessary and/or sufficient conditions for the outcome. And it would issue in pronouncements like "successful social movements require X, Y, and Z as necessary conditions."

A third possible approach combines some features of both of these. This third approach acknowledges that each social event embodies a great deal of particularity and contingency -- thus requiring a substantial amount of descriptive research. But this third approach also postulates that there are causes of successful and unsuccessful mobilization and that these take the form of concrete social-causal mechanisms. So this approach directs the researcher to engage in concrete research with the goal of discovering some of the concrete social mechanisms that appear to have been critical. This research in turn has some promise in providing the basis for some limited generalizations in the study of social movements. If we find that there are some common challenges that efforts at social mobilization confront, this is a beginning of a more general treatment. And if we find that there are a handful of key mechanisms that recur in many cases, this further supports the development of more generalized statements about mobilization. (This is roughly the approach that McAdam, Tarrow and Tilly take in Dynamics of Contention.)

Now let's return to the role that resource mobilization theory plays in the study of social movements. This concept is said to be one of the primary theories of social movements. Its primary competitor on the 1980s was "political process theory." My question here is a simple one: in what sense do either of these concepts function as theories of social movements? If they are intended to serve as nouns in sentences like these -- "Social movements always occur in circumstances where there is more X in the social context" -- then I want to say that neither concept is likely to serve well and neither really functions as a theory of collective behavior. This usage is attempting to fulfill the second project above, namely, offering an account of the necessary and sufficient conditions of mobilization. However, given the contingency and heterogeneity of social events, it is unlikely that there are any such conditions. But the situation is much better if we take the view that both "resource mobilization" and "political process" theories serve to describe social mechanisms that are found in many different instances of social movements -- though often in different forms and levels of importance. On this approach, "resource mobilization" is a theory of a social process or circumstance that is a relevant causal mechanism in many different instances of social movements. But it does not function as a general theory of social movements; instead, it is a developed description of a social mechanism that can be recognized in a variety of contexts (not all of which involve social movements).

In other areas of science a theory of a domain is thought to be a compact set of hypotheses that explain all the phenomena of the domain. "Resource mobilization" and "political process" cannot function in this way. However, each of these concepts can function as a description of a limited but real social mechanism; and in this way they each can play a constructive role in explaining important instances of collective mobilization and social movements.

Social causal explanations

To explain an outcome is to demonstrate what conditions combined to bring it about -- what caused the outcome in the circumstances, or caused it to be more likely to occur. The most fundamental aspect of an explanation is a hypothesis about what caused the circumstance we want to explain. So social explanation requires that we provide accounts of the social causes of social outcomes. (There may be non-social causes of social outcomes -- e.g. "The Roman Empire declined because of the high concentrations of lead in wine vessels"; but these extra-social explanations don't really fall within the social sciences.)

So we need to raise two sorts of questions. First, what kind of thing is a social cause -- how do social facts cause other social facts? And second, what kind of social research can allow us to identify the causes of a social outcome or pattern? (Notice that explaining an outcome is very different from explaining a pattern.)

Generally speaking, a cause is a condition that either necessitates or renders more probable its effect, in a given environment of conditions. (For the philosophers, this means that "C is sufficient in the circumstances to bring about E or to increase the likelihood of E.") Normally a cause is also necessary for the production of its effect -- "if C had not occurreD, E would not have occurred." (The probabilistic version: "If C had not occurred, the likelihood of E would have been lower.) (Wesley Salmon explores the intricacies in much greater detail -- Scientific Explanation and the Causal Structure of the World.)

This account depends upon something that Hume abhorred: the idea of necessity. For natural causes we have a suitable candidate in the form of natural necessity deriving from the laws of nature: "C and the laws of nature => necessarily E." However, there are no "laws of society" that function ontologically like laws of nature. So how can there be "social necessity"? Fortunately, there is an alternative to law-based necessity, in the form of a causal mechanism. A mechanism is a particular configuration of conditions that always leads from one set of conditions to an outcome. Mechanisms bring about specific effects. (So we might say that mechanisms are widgets of natural laws.) For example, "over-grazing of the commons" is a mechanism of resource depletion. And it is the case that, whenever the conditions of the mechanism are satisfied, the result ensues. Moreover, we can reconstruct precisely why this would be true for rationally self-interested actors in the presence of a public good. So we can properly understand a claim for social causation along these lines: "C causes E" means "there is a set of causal mechanisms that convey circumstances including C to circumstances including E."

Are there any social mechanisms? There are many examples. "Collective action problems often cause strikes to fail." "Increasing demand for a good causes prices to rise for the good in a competitive market." "Transportation systems cause shifts of social activity anad habitation."

So this provides an answer to the first question: explaining a social outcome or pattern involves providing an account of the social-causal mechanisms that typically bring it about, or brought it about in specific circumstances.

Now let us turn to inquiry. How would we detect social causation? Fundamentally there are only three ways. We can exploit the mechanism requirement and seek out particular or common social mechanisms. Both social theory and process-tracing can serve us here. Second, we can exploit the probabilistic implications of a causal claim by looking for correlations and conditional probabilities among the conditions associated with hypothesized causal mechanisms. This feature underpins standard "large-N" quantitative research methods in social science. And third, we can exploit the "necessary and sufficient condition" feature by using comparative methods like Mill's methods. In each case, we must keep fully in mind the centrality of causal mechanisms. A discovery of a statistical association between X and Y is suggestive of causation, but we need to be able to hypothesize the mechanism that would underly the association if we are to attribute causation. Likewise, the discovery that a study of multiple cases suggests that A is necessary for E and A&B are sufficient for E requires us to consider the question, what is the concrete social mechanism that links A, B, and E?

What is "understanding social life"?

There have been two very different approaches to social explanation since the nineteenth century, and they differ most basically over a distinction between "explanation" and "understanding" or "cause" and "meaning". This distinction divides over two ways of understanding a "why" question when it comes to social events. "Why did it happen?" may mean "What caused it to happen?"; or it may mean "Why did the agents act in such a way to bring it about?".

The verstehen approach holds that the most basic ontology of social life is the meaning of an action. Social life is constituted by social actions, and actions are meaningful to the actors and to the other social participants. Moreover, subsequent actions are oriented towards the meanings of prior actions; so understanding the later action requires that we have an interpretation of the meanings that various participants assign to their own actions and those of others. (Central exponents of this tradition include Weber, Dilthey, Heidegger, Ricoeur, and Gadamer.)

This approach places interpretation of meaning at the center of social inquiry. And it drew much of its methodology and tools of inquiry from the hermeneutic tradition -- the tradition of biblical and literary interpretation stemming from Dilthey and other nineteenth-century German thinkers. This tradition is adapted to the "human sciences" by using the metaphor of action as text. The interpreter (a biographer, for example) considers the many elements of the action, life, or complex of actions, and attempts to arrive at an interpretation that makes sense of the various parts.

A central problem that authors in this tradition wrestle with is the "hermeneutic circle" -- the fact that there is no neutral, external standpoint from which to objectively measure the meaning of a system of signs or actions. Instead, interpretation begins and ends with the given -- the text or the action -- and the only evidence available for assessing the interpretation is interior to the text itself. So it may appear that interpretations are self-confirming -- an unhappy conclusion if we think that social explanations ought to have rational justification and empirical support.

The hermeneutic approach got a large boost from the fertile field of interpretive anthropology in the 1970s and 1980s, especially through the work of Clifford Geertz and Turner. However, there is little evidence of a direct intellectual connection from hermeneutic philosophy to interpretive anthropology.

There are several valid insights that the verstehen approach depends on. Most important is the insistence on the point that social action is meaningful and intentional, and that it is both desirable and feasible to arrive at interpretations of these meanings. Moreover, being able to arrive at such interpretations is often essential to historical and ethnographic explanation. Geertz's interpretation of the Balinese cock-fight and Darnton's interpretation of the great cat massacre both illustrate this point: in neither case would we understand the behavior without a deep interpretation of the significances the participants attribute to their actions.

This said, it is incorrect to imagine that the verstehen approach is inconsistent with the causal approach. Rather, the two approaches are compatible and complementary. It is a fact that human action is meaningful and intentional, and all social science must take account of this fact. But it is also true that actions aggregate to larger causes and they have effects on social outcomes. Meaningful, deliberate action is often the mechanism through which a given set of institutional arrangements (a property system, say) cause a social outcome (slow investment in new technologies, say). So meanings are themselves causes and causal mechanisms (a point that Donald Davidson makes in the case of individual action).

Finally, a social science that restricted itself to hermeneutic interpretation would be radically incomplete. It would exclude from the scope of social science research the whole range of causal relationships, structural influences on action, and the workings of unintended consequences in social processes.

Explaining large social formations: fascism

In a previous post I discussed the problem of explaining fascism. Let's return to this issue as a topic for historical and social inquiry.

There are clearly a number of different explanatory questions we might have in mind: why did fascist movements emerge and gain popular support in the first three decades of the twentieth century? Why did these movements prevail in several countries and not in others? (This version parallels Skocpol's question about revolutions.) Why did fascist states develop the political institutions they did in Germany, Italy, and Spain? How did fascist states and leaders exercise power? What prevented the rise of powerful fascist movements on France and Britain -- in spite of the presence of ultra-nationalist leaders and organizations?

These are all different questions -- even if there are relations among them. A particularly central question concerns the factors that were conducive to the emergence of extremist beliefs and organizations in certain periods and what factors favored the growth and power of some of these movements. This is a bundle of questions about the conditions that favor collective mobilization and ideological formation on a mass society. It is the sort of research question that Chuck Tilly and other scholars of popular mobilization have been concerned with.

Another set of questions about the course of fascism has more to do with institution building and state formation. Given the goal of creating powerful stare institutions within the general framework of fascist ideas and goals, what institutional and organizational possibilities existed? Here we might refer to the repertoire of mass organization that fascist "revolutionaries" brought to their movement, as well as the historical and practical options that existed. This area of inquiry may provide a basis for answering questions about the particular nature of fascist political institutions.

Finally, the distinct question of why it was that fascist movements and leaders were able to defeat democratic movements and states requires that we identify some of the circumstances that weakened democratic regimes. This may be a wide range of factors: challenges of war, ideological conflict with communists and other critics of the state, and the economic circumstances of the great depression. (These fall in the same category as the circumstances that Skocpol brings forward as being relevant to the success or failure of revolutions.)

It would appear that social scientists and historians have better tools for addressing the issue of successful mobilization than the institutional or causal conditions surrounding seizure of power and state building. Schematically, we might consider a causal narrative along these lines: Conditions that favor fascism include the presence of a marginalized group of young people who are subject to great economic insecurity; an ideology that combines nationalism, ethnic suspicion, and disaffection from established social institutions and values, and a compelling narrative of how and why this group ought to wield power. To this we might add a few propitious international conditions: the threat of war, a widening economic crisis, and a broad view that the modern state isn't up to handling these challenges.

This approach sketches out a view of what might be a basis for an explanation of the rise of fascist social movements. Here we have singled out several causal-social factors that facilitate popular mobilization and the politicization of social movements. What it doesn't yet explain is why and in what circumstances these movements are likely to grow powerful enough to challenge the existing state structure; this remains for another discussion.

Varieties of social causation

What are some chief mechanisms through which social behavior is shaped and social outcomes are caused? Ideally the best answer to this question would result from a survey or inventory of many explanations. But consider some high level possibilities that could serve as a causal mechanism bringing about a social phenomenon of interest.

Selection mechanisms. Why are passengers on commercial aircraft better educated than the general population? Because most airline passengers are business travelers, and high-level and mid-level business employees tend to have a higher level of education than the general population.

Evolutionary explanations. Why does the level of firm efficiency tend to rise over time? Because the net efficiency of a firm is the product of many small factors. These small factors sometimes change, with an effect on the efficiency of the firm. Low efficiency firms tend ultimately to lose market share and decline into bankruptcy. Surviving firms will have features that produce higher efficiency.

Imitation mechanisms. Why did the no-huddle offense become so common in the NFL in the 1980s? Because it was successful for a few teams, and others copied the offense in the hope that they too would win more games.

Rational-intentional explanations. Why do rebellions often fizzle out? Because participants are rational agents with private goals, and they make calculating decisions about participation.

Aggregative explanations (aggregate consequences of individual-level strategies). Why does technological innovation occur continuously within a market-based society? Because manufacturers are constantly looking for lower-cost and higher-value-added methods of manufacturing, and this search leads them to innovations in products and technologies.

Conspiracy explanations (covert strategems of the powerful). Why did the United States move away from passenger railroads as the primary form of intercity transportation? Because powerful interests took political actions to assure that private automobiles would be encouraged as the primary form of transport.

Mentality explanations (behavior is changed by changing beliefs and attitudes). Why were so many Quaker men conscientious objectors at great personal cost during World War II? Because their religious beliefs categorically rejected the violence in war and they refused to participate in this immoral activity.

Historical / path-dependency explanations. Why do we still use the very inefficient QWERTY keyboard arrangement that was devised in 1874? Because this arrangement, designed to keep typists from typing faster than the mechanical keyboard would permit, was so deeply embodied in the typing skills of a large population and the existing typewriter inventory by 1940 that no other keyboard arrangement could be introduced without incurring massive marketing and training costs.