Current issues in causation research

This week’s conference on Causality and Explanation in the Sciences in Ghent was an unusually good academic meeting (link). Participants gathered from all over Europe, as well as a few from North America, Australia, and South Africa, to debate the logic and substance of causal interpretations of the world. Among other things, it provided all participants with a very good sense of the ideas about causation that are generating the most discussion today.

A general perception that emerges from the gestalt of papers at the conference is that there are three large focus areas in current research on scientific causation. First, there is interest in specifying what causal assertions and concepts mean in scientific explanations. What are the logical, conceptual, and pragmatic issues associated with causal assertions and explanations?

Second, there is a large body of work focusing on the methods we can use to support causal inference in the sciences. Every field of science produces volumes of data about variables and events over time. What methods exist to permit inferences about causal relationships among the observed variables and entities? This includes causal modeling statistical methods, but also comparative methods deriving from Mill’s methods of difference and similarity.

Third, there is a group of philosophers and scientists who are primarily interested in the ontology of causation in various parts of the sciences. How do various factors exercise causal powers in ecology, the social sciences, or complex systems? Researchers in these areas need provisional answers to questions raised by the first two groups, but their focus is on substantive causal processes rather than the logic of causal statements.

It is useful to inventory half a dozen approaches that were repeatedly cited. This survey is impressionistic but gives an idea of the current landscape.

The mechanisms approach. The idea that we can explicate causation through the idea of a mechanism has been rising in importance over the past twenty years. The idea here is that the fundamental causal concept is that of a mechanism through which X brings about or produces Y. This is argued to be key to causation from single-case studies to large statistical studies suggesting a causal relationship between two or more variables. Peter Hedstrom and other exponents of analytical sociology are recent voices for this approach for the social sciences, though expositions of this approach don’t usually go into the level of detail expected by philosophers like Woodward and Cartwright. An important paper by Peter Machamer, Lindley Darden and Carl Craver, “Thinking about Mechanisms”, sets the terms of current technical discussions; their view is referred to as the MDC theory. A common concern is that the approach hasn’t been as clear as it should be about what precisely a mechanism is. James Mahoney made this criticism in 2001 in “Beyond Correlational Analysis” reviewing Charles Ragin, Fuzzy-Set Social Science and Peter Hedstrom and Richard Swedberg, Social Mechanisms: An Analytical Approach to Social Theory (link), and we still need a more generally recognized specification of the idea. (See an earlier post on this approach; link.)

Jim Woodward is perhaps the leading exponent of the manipulability (or interventionist) account. He develops his views in detail in his recent book, Making Things Happen: A Theory of Causal Explanation. The view is an intuitively plausible one: causal claims have to do with judgments about how the world would be if we altered certain circumstances. If we observe that the concentration of sulphuric acid is increasing in the atmosphere, we might consider the increasing volume of H2SO4 released by coal power plants from 1960 to 1990. And we might speculate that there is a causal connection between these facts. A counterfactual causal statement holds that: If X (increasing emissions) had not occurred, then Y (increasing acid rain) would not have occurred. The manipulability theory adds this point: if we could remove X from the sequence, then we would alter the value of Y. And this in turn makes good sense of the ways in which we design controlled experiments.

Difference-making. Another strand of thinking about causation focuses on the explanations we are looking for when we ask about the cause of some outcome. Here philosophers note that there are vastly many conditions that are causally necessary for an event but do not count as being explanatory. Lee Harvey Oswald was alive when he fired his rifle in Dallas; but this doesn’t play an explanatory role in the assassination of Kennedy. Crudely speaking, we want to know which causal factors were salient; which factors made a difference in the outcome. Michael Strevens provides a detailed and innovative explication of this set of intuitions in his recent book Depth: An Account of Scientific Explanation, where he introduces his theory of “Kairetic” explanation.

Contrastive analysis as a theory of explanation. When we seek an explanation of something, we generally have something specific in mind: why X rather than X’? And an explanation that keys off the wrong contrast will fail, even though its premises are correct. Bas van Fraassen (1980), The Scientific Image, is often cited in this context. A conference participant, Petri Ylikoski, develops a contrastive counterfactual theory in his dissertation (link). This body of work seeks to clarify pragmatic issues concerning explanation, including understanding and explanatory relevance. If we ask for an explanation for why X occurred, we are usually presupposing a question like this:Why did X occur [rather than Y]?

  • Why is John carrying his umbrella [rather than not]?
  • Why is John carrying his umbrella [rather than his raincoat]?
  • Why is John carrying his umbrella [rather than his assistant Harry]?

These all demand different answers:

  • Because he expects rain;
  • Because it is too warm for a raincoat;
  • Because Harry is carrying three heavy suitcases.

Here is a much-cited review article by Nancy Cartwright on van Fraasen’s work (link), and here is a discussion of contrastive explanation by Jonathan Schaffer (link).

Causal modeling theory. This topic refers to the large body of statistical theory devoted to identifying potential causal relationships among observable variables in a large data set. Hubert Blalock is a founder of this approach (Causal Inferences in Nonexperimental Research; 1964) with his statistical models for causal path analysis. (Here is a short account of the history of path analysis in genetics.) Judea Pearl has contributed a great deal to the method of structural equation modeling (SEM) in Causality: Models, Reasoning and Inference and elsewhere. Here is a handbook article in which he explains the method and its causal relevance (link). Pearl maintains a research blog on causality hereGranger causalityis a specific technique for assessing causal relationships within time series data: X Granger-causes Y if variations in X and Y together do a better job of predicting Y than variations in Y by itself.

Prior foundations of philosophical theories of causation. Two older discussions of causality also received some notice in these papers: J. L. Mackie on INUS conditions and causal fields (The Cement of the Universe: A Study of Causation) and Wesley Salmon on the causal structure of the world (Scientific Explanation and the Causal Structure of the World).

Nancy Cartwright’s “Causation: One Word, Many Things” provides a very good contemporary review of the varieties of approaches that are currently being taken to the idea of causation (link).

Much of the intellectual vitality of this group of philosophers is captured in the major work recently edited by Phyllis McKay Illari, Federica Russo, and John Williamson, Causality in the Sciences. The book contains a very wide range of disciplines and approaches in its treatment of the topic.

Social explanation and causal mechanisms

To explain a social outcome or regularity, we need to provide an account of why and how it came about; and this means providing a causal analysis in terms of which the explanandum appears as a result.

Having a causal theory of a realm requires having an ontology: what kinds of things exist in this realm, and how do they work? Along with others, I offer a social ontology grounded in the actions and relations of socially constituted actors, which I refer to as methodological localism (link). (This is also the ontology asserted by the programme of “analytical sociology”;  link.)

This entails, basically, that we need to understand all higher-level social entities and processes as being composed of the activities and thoughts of individual agents at a local level of social interaction; we need to be attentive to the pathways of aggregation through which these local-level activities aggregate to higher-level structures; and we need to pay attention to the iterative ways in which higher-level structures shape and influence individual agents.  Social outcomes are invariably constituted by and brought into being by socially constituted, socially situated individual actors (methodological localism). Both aspects of the view are important. By referring to “social constitution” we are invoking the fact that past social arrangements have created the social actor. By referring to “social situatedness” we invoke the idea that existing social practices and rules constrain and motivate the individual actor. So this view is not reductionist, in the sense of aiming to reduce social outcomes to pre-social individual activity.

We also want to refer to supra-individual actors — firms, agencies, organizations, social movements, states. The social sciences are radically incomplete without such constructs. But all such references are bound by a requirement of microfoundations: if we attribute intentionality to a firm, we need to be able to sketch out an account of how the individuals of the firm are led to act in ways that lead to the postulated decision-making and action (link).

So, then: what is involved in asserting that social circumstance A causally produces social circumstance B? There are, of course, numerous well developed answers to this question: statistical inference based on correlations of occurrences, conditional probabilities, and necessary-sufficient condition analysis. My view, however, is that there is a more basic meaning of causation: A caused B iff there is a sequence of causal mechanisms leading from A to B. This approach is especially suitable for the social realm because, on the one hand, there are few strong statistical regularities among social outcomes, and on the other, it is feasible to identify social mechanisms through a variety of social research methods — comparative analysis, process tracing, case studies, and the like.

The social mechanisms approach (and the scientific realism that lies behind it) goes back at least as early as the late 1980s. An early statement of the view was presented in my Varieties Of Social Explanation: An Introduction To The Philosophy Of Social Science in 1991.  Mario Bunge and Jon Elster took similar positions. The view took a large step forward, on the theory side, with the publication of Hedstrom and Swedberg’s Social Mechanisms: An Analytical Approach to Social Theory (1998), and on the empirical research side with the publication of McAdam, Tarrow, and Tilly’s Dynamics of Contention (2001). There are important differences; theorists within analytical sociology largely favor methodological individualism and mechanisms grounded in rational individuals, whereas Tilly and his colleagues favor “relational” mechanisms. But in each case the model of agent-centered explanations that either require microfoundations or are plainly compatible with such a requirement.  (Here is a recent post on causal mechanisms.)

Several social scientists have anticipated this approach through their own concrete analysis of aggregation phenomena.  A good illustration is Thomas Schelling.  His work presents a large number of examples of mundane social outcomes that he explains on the basis of simple individual-level choices and an aggregation mechanism (Micromotives and MacrobehaviorChoice and Consequence). Features of organized crime, traffic patterns, segregation, and dying seminars all come in for treatment.  Schelling demonstrates in concrete terms what sorts of things we can identify as “social mechanisms” and traces them back to the circumstances of action of individuals in social situations.

The framework of social mechanisms as a basis for social explanation raises an important question about the role and scope of generalizability that we expect from a social explanation. Briefly, the mechanisms identified here show a degree of generalizability; as McAdam, Tarrow and Tilly assert, social mechanisms can be expected to recur in other circumstances and times. But the event itself is one-of-a-kind. This is a familiar feature of Tilly’s way of thinking about contentious events as well: the American Civil War was a singular historical event. But a good explanation will invoke mechanisms that recur elsewhere. We shouldn’t expect to find general theories of civil wars; but our explanations of particular civil wars can invoke quasi-general theories of mid-level mechanisms of conflict and escalation. (Here is a recent posting on general and specific causal claims.)

Another important methodological question for this approach to social explanation is the issue of explaining general statistical patterns in social life.  What if we want to explain something more quantitative — say a gradually rising divorce rate or the finding that co-habitants before marriage have higher divorce rates than non-co-habitants? On the social mechanisms approach, we would want two things. First, we would like an agent-level mechanism that explains the statistic; and second, we would like to find a common cause if the phenomenon is similar in several countries.

Finally, the actor-based mechanisms approach invites an area of study which is now being referred to as “aggregation dynamics” (linklink).  We need to have theories and tools that permit us to aggregate different micro-level processes over time into meso- and macro-outcomes, taking into account the complexity of causal interactions in a dynamic process.  The tools of agent-based modeling are relevant here (link).

Spartacus, Kitty Genovese, and social explanation


What is most interesting in paying attention to social life is noticing the surprising outcomes that often materialize from a number of uncoordinated choices and actions by independent individuals. We want to understand why and how the aggregate-level social fact came to be: was it a set of features of the individual actors’ preferences or decision-making?  Was it the unintended result of strategic choices by various actors?  Was it simply the path-dependent and contingent outcome of a serial interactive process?  Was it brought about by structural conditions — power, wealth, race — within the context of which actors made their choices?  And what were the mechanisms of constraint, aggregation, contagion, and escalation through which actions and processes at the more proximate level came together into the outcome at the distal level?

Consider a pair of examples. Kitty Genovese is attacked by an assailant over an extended period of time in a dense neighborhood in Queens, many people observe the crime, and no one intervenes.  The woman is eventually murdered.  The question here is, why was there a total absence of intervention by any individual or group in this crime?  And a parallel surprise: General Marcus Licinius Crassus, having trapped the rebellious slave army of Spartacus, announces that the slaves will be spared death if they give up Spartacus for crucifiction.  Spartacus rises to his feet to say, “I am Spartacus.” And in minutes the army of men rise as well, all declaring “I am Spartacus.”  Here the question is the reverse: why do these men expose themselves to death to stand in solidarity with Spartacus?  In each case, there is an occasion for action presented to a group of individuals, in which members of the group can attempt to save the life of another person.  The collective behavior is fundamentally different in the two cases.   Why so? What are the mechanisms, psychological and social, that led to non-intervention in the first case and fatal solidarity in the second?

We might form a number of hypotheses about both of these cases in order to explain the very different outcomes.  In the Kitty Genovese case, we might cite anomy and anonymity as possible causes of the lack of response by bystanders.  With a low level of civic bonds, perhaps city dwellers have such a low level of emotional involvement with each other that even the slightest effort is unjustified.  Or perhaps it is the fact that each potential responder is anonymous to the others that leads to the result; he/she can make the decision to refrain from offering aid without fear of criticism from others.  Or perhaps collective behavior is strongly influenced by the actions of the first few, with later observers mimicking earlier non-aiders.  So the outcome might have been highly different if the first or second witness had intervened; others might have followed suit.   In the case of Spartacus, we might hypothesize that the bonds of solidarity forged by a history of fighting the Roman army gave the soldiers the moral motivation to support Spartacus; or perhaps it is the publicity of the scene, or the early example of the first few supporters, that spread to the behavior of the others.  Or perhaps it is an expression of fundamental mistrust by the soldiers of the good faith of Marcus Crassus; “he will kill us anyway.” With nothing to lose, the army makes its symbolic statement of rejection.  These are each social psychological hypotheses, concerning the ways that individuals choose to involve themselves in an emergency and a situation of potential sacrifice.

Each of these hypotheses represents a social mechanism that can be incorporated into a narrative explaining the aggregate outcome.  In order for such a story to be scientifically compelling, we need to have some way of using empirical evidence to evaluate whether the postulated mechanism actually works in the real world of human behavior.  Is there empirical evidence for a social psychology of mimicry?  Do we have evidence to suggest that members of a crowd are more likely to do X or Y if a few others have already done so?  Is there empirical support for a theory of solidarity as a social motivation: do combat teams, groups of deep-ground miners, or emergency room doctors develop a higher willingness to conform their behavior to the good of the group of of other individuals in the group?  These examples of social mechanisms all fall in the category of putative behavioral regularities, and it should be possible to investigate them experimentally and statistically.

The challenge of explanation for any social outcome, we might say, is that of constructing an interpretation of the states of minds of a set of actors; the constraints and opportunities within which they choose a course of action; and the interactions that are created as they act within a common environment, leading to the outcome in question.  This is what we can refer to as an aggregative explanation, and it lies at the heart of Thomas Schelling’s methodology in Micromotives and Macrobehavior.  As Schelling points out, sometimes the explanation turns on specific features of agency (the actors’ preferences or their modes of decision-making), and sometimes it turns on the specifics of the environment of choice (the fact that the outcome of action is a public good).  But in general, explanation proceeds by showing how agents with specific features, acting within a social and natural environment with specific characteristics, bring about specific kinds of outcomes.

This, in a nutshell, represents a simple but powerful statement of a philosophy of social explanation.  It also represents the rudiments of a social ontology: higher-level social features are composed of the actions and states of agency of a set of actors within the context of locally embodied rules, norms, and expectations.  This is what I refer to as “methodological localism”:

This theory of social entities affirms that there are large social structures and facts that influence social outcomes. But it insists that these structures are only possible insofar as they are embodied in the actions and states of socially constructed individuals. The “molecule” of all social life is the socially constructed and socially situated individual, who lives, acts, and develops within a set of local social relationships, institutions, norms, and rule. (link)

Social explanations derive their force from empirical research into the nature of the actor, the nature of the locally embodied social environment, and the processes of aggregation through which actions by multiple actors coalesce into social outcomes.  The explanation satisfies us when it demonstrates the pathways through which individuals, constituted as they are found to be, located in institutions of the sort described, contribute to collective outcomes of the kinds described.

Hobbes an institutionalist?

Here is a surprising idea: of all the modern political philosophers, Thomas Hobbes comes closest to sharing the logic and worldview of modern social science. In Leviathan (1651) he sets out the problem of understanding the social world in terms that resemble a modern institutionalist and rational-choice approach to social explanation. It is a constructive approach, proceeding from reasoning about the constituents of society, to aggregative conclusions about the wholes that are constituted by these individuals. He puts forward a theory of agency — how individuals reason and what their most basic motives are. Individuals are rational and self-concerned; they are strategic, in that they anticipate the likely behaviors of other agents; and they are risk-averse, in that they take steps to avoid attack by other agents. And he puts forward a description of two institutional settings within which social action takes place: the state of nature, where no “overawing” political institutions exist; and the sovereign state, where a single sovereign power imposes a set of laws regulating individuals’ actions.

In the first institutional setting, he argues that individual competition in the context of the absence of sovereignty leads to perpetual violent competition. In the second institutional setting, he argues that individual self-striving within the context of a system of law leads to the accumulation of property and peaceful coexistence.

Here are some of Hobbes’s premises about individual agents from chapter XIII of Leviathan:

From this equality of ability ariseth equality of hope in the attaining of our ends. And therefore if any two men desire the same thing, which nevertheless they cannot both enjoy, they become enemies; and in the way to their end (which is principally their own conservation, and sometimes their delectation only) endeavour to destroy or subdue one another. And from hence it comes to pass that where an invader hath no more to fear than another man’s single power, if one plant, sow, build, or possess a convenient seat, others may probably be expected to come prepared with forces united to dispossess and deprive him, not only of the fruit of his labour, but also of his life or liberty. And the invader again is in the like danger of another.

So that in the nature of man, we find three principal causes of quarrel. First, competition; secondly, diffidence; thirdly, glory. The first maketh men invade for gain; the second, for safety; and the third, for reputation. The first use violence, to make themselves masters of other men’s persons, wives, children, and cattle; the second, to defend them; the third, for trifles, as a word, a smile, a different opinion, and any other sign of undervalue, either direct in their persons or by reflection in their kindred, their friends, their nation, their profession, or their name.

The passions that incline men to peace are: fear of death; desire of such things as are necessary to commodious living; and a hope by their industry to obtain them. And reason suggesteth convenient articles of peace upon which men may be drawn to agreement. These articles are they which otherwise are called the laws of nature, whereof I shall speak more particularly in the two following chapters.

And these motives and forms of behavior by individuals lead to a predictable outcome for the collectivity in the state of nature: a war of all against all.

Whatsoever therefore is consequent to a time of war, where every man is enemy to every man, the same consequent to the time wherein men live without other security than what their own strength and their own invention shall furnish them withal. In such condition there is no place for industry, because the fruit thereof is uncertain: and consequently no culture of the earth; no navigation, nor use of the commodities that may be imported by sea; no commodious building; no instruments of moving and removing such things as require much force; no knowledge of the face of the earth; no account of time; no arts; no letters; no society; and which is worst of all, continual fear, and danger of violent death; and the life of man, solitary, poor, nasty, brutish, and short.

This is an institutionalist argument. It models the behavior that is expected of a certain kind of agent within a certain kind of institutional setting; and it projects the consequences of these “microfoundations” for the aggregate society. In other words, Hobbes is offering a micro- to macro-argument based on analysis of modes of agency and assumptions about a particular institutional context.

Compare this logic with a description of the logic of social explanation offered by contemporary rational-choice social theorist James Coleman in Foundations of Social Theory:

A second mode of explanation of the behavior of social systems entails examining processes internal to the system, involving its component parts, or units at a level below that of the system. The prototypical case is that in which the component parts are individuals who are members of the social system. In other cases the component parts may be institutions within the system or subgroups that are part of the system. In all cases the analysis can be seen as moving to a lower level than that of the system, explaining the behavior of the system by recourse to the behavior of its parts. This mode of explanation is not uniquely quantitative or uniquely qualitative, but may be either. (2)

So the logic of Hobbes’s argument is fairly clear; and it is deeply similar to that of institutionalist rational-choice theorists. Thomas Schelling’s title, Micromotives and Macrobehavior, captures the idea in three words: derive descriptions of macro-level social arrangements and behavior from premises concerning individual-level motivation and action.

It is not a profound criticism of Hobbes’s philosophical analysis to quarrel with Hobbes’s specific assumptions about what is possible within the state of nature. And in fact, a number of contemporary political scientists argue that it is possible for men and women to create non-political institutions within the context of what Hobbes calls the state of nature. Coordination and cooperation are indeed possible within a “state of nature”; it is possible to achieve coordination within anarchy. From a sociological point of view, this is really a friendly amendment; it simply adds a further premise about the feasibility of certain kinds of cooperation. So the “cooperation within anarchy” criticism of Hobbes is advanced as a substantive argument about the feasibility of durable social institutions that do not depend upon a central coercive authority. And it depends upon several specific assumptions about the circumstances and mechanisms through which local groups of people can establish self-enforcing forms of cooperation that overcome free-riders and predatorial behavior. It is likely enough that Hobbes would not have been persuaded by this argument; but ultimately it is an empirical question.

Several arguments against Hobbes’s conclusions about the state of nature are especially valuable from this point of view. First, I find Michael Taylor’s arguments in Community, Anarchy and Liberty particularly convincing — essentially, that peasant communities have traditionally found ways of creating and sustaining cooperative institutions and relationships that persist without the force of law to stabilize them. “Contracts” backed by legal systems are not the only way of establishing coordination and cooperation among independent agents. Robert Netting provides relevant examples in Smallholders, Householders: Farm Families and the Ecology of Intensive, Sustainable Agriculture, around traditional forms of labor-sharing and seasonal cooperation. And Elinor Ostrom and her collaborators make similar arguments in their historical and sociological studies of “common property resource regimes” — essentially, stable patterns of cooperation maintained by local voluntary enforcement rather than central legislation (Governing the Commons: The Evolution of Institutions for Collective Action). Ostrom documents dozens of important historical cases where traditional communities have managed fisheries, forests, water resources, and other common properties without having a central state to support these patterns of cooperation and coordination.

But these are empirical and theoretical refinements to a fundamentally coherent model of social explanation that is full-fledged in Hobbes’s work in the mid-seventeenth century: explain aggregate (macro) social outcomes as the result of mechanisms and actions at the level of individual actors.

System tendencies?

A central theme of many of the posts here is the contingency, heterogeneity, and path dependency of social processes. I used the metaphor of a “constrained random walk” in an earlier posting to characterize many social processes. This figure is intended to stand in contrast to the idea of an inevitable development towards an optimum or equilibrium point, on the one hand, or the idea of an inevitable system failure, on the other.

The idea here is this: from starting point A, there are numerous possible states of affairs Oi that might be reached over an extended period of time. There is no sense in which the course from A to the actual historical outcome Om is inevitable or unique. (From the starting point of Europe in 1910, including the social, political, and economic realities of the nations of Europe, multiple outcomes were accessible by the time of 1920: exhausting war, emergence of new and effective international organizations that sustained the peace, inspired just-in-time diplomacy bringing hostilities to an early termination, …). Each of the pathways leading from A to Oi might be individually explicable, in terms of the situations of structure and agency that were present during the period of development. Virtually every point in the “space” of outcomes would be accessible, although some outcomes might be substantially less likely than others. Along the way there are likely to be cul-de-sacs; but in the aggregate, the space of possible outcomes from many historical starting points covers the full sphere of possibilities. Putting the point crudely, you can get anywhere from anywhere.

This conception emphasizes deep contingency in social change. But what about the symmetrical facts of “constraint” and “imperative” — the limitations imposed by existing institutions and organizations at any specific stage and the positive impulses to change that are often embodied in the incentive structures of existing institutions? Is the contingency of social events to some extent reduced by the relative durability of existing core social institutions? Is there such a thing as a “logic of institutions” that is embodied in a particular configuration of core social institutions, with the result that societies embodying these institutions will be most likely to develop in one way rather than another?

This description lies at the heart of Marx’s analysis of social systems as modes of production. Marx believed that the core institutions that defined the property system, the system of labor control, and the distribution of wealth have deep effects on individual agency, leading and constraining agents to behave in ways that lead in the aggregate to certain kinds of social outcomes. Modes of production have system tendencies that can be inferred from their basic institutional features. A particularly clear example is his analysis of the “law” of the falling rate of profit within capitalism: firms are required to maximize profits; they have the opportunity of introducing capital-intensive technologies that lower costs, thereby increasing profits in the short run; competition with other profit-maximizing firms pushes prices down to the new cost of production; the rising capital-labor ratio in industry creates a falling rate of profit. So capitalism embodies a system tendency towards a falling rate of profit over time. Similar reasoning underlies Marx’s prediction of financial crises within capitalism. (See an earlier posting on Marx’s conception of capitalism.)

And in fact, if we could make two assumptions, then Marx’s reasoning about the tendencies of capitalism would be very compelling: the assumption that the core economic institutions are fixed and unchanging, and the assumption that there are no other social-political-economic institutions in play that might serve as resources for policies and actions that would offset the predicted tendencies of capitalism. However, neither of these assumptions is correct. The institutions of any major social order — feudalism, the Chinese agrarian economy, capitalism, state socialism — are always the composite of a vast number of lower-level institutions; and these lower-level institutions are usually in a state of flux. So the core institutions are not fixed and unchanging. The traditional Chinese agrarian economy was remarkably resilient in face of a range of deep challenges over centuries; adjustment of basic social institutions permitted Chinese society to cope better with environmental and international circumstances than a modeled Chinese economy would have predicted.

Second, even more fundamentally, a society is not simply a “mode of production,” constituted by an economic structure. Rather, there are a range of other, equally fundamental institutions and practices — cultural, political, legal, community-based and national — through which resourceful agents attempt to solve personal or social problems at various points in time. So the “logic” of the economic institutions is only one part of the overall social trajectory; instead, we have the strategic interaction and aggregation of political, cultural, social, demographic, and legal institutions that complement and offset the workings of the economic structure. And further, we can correctly say that each of these aspects of social organization has its own “system tendencies.” Elected legislatures have a logic that derives from the calculations of political self-interest of the legislators, community-based organizations have their own logic, various demographic regimes have their own tendencies (for example, the favoring of boy children produces skewed sex ratios that have negative political effects), and so forth.

So the tentative conclusion that I draw from these various considerations is, once again, to give the nod to contingency while recognizing the partial imperatives created by the various sets of core institutions that are embodied in a society at a given time. Structures do of course constrain agents. But structures interact with each other, leading to surprising results. And structures change in response to a variety of causes, including the strategic efforts of agents to modify them. So the upshot is, once again, that we should expect a high degree of contingency in outcomes over extended periods of historical time. Historical experience may well support the discovery that “capitalism creates a tendency towards X” or “fascist politics create a tendency towards Y”. To that extent, there are “system tendencies”. But it is rare for one particular sub-system (property relations, electoral system, demographic regime) to dominate the overall historical trajectory. And so the system tendencies of one partial set of core institutions rarely become the system tendencies of the overall social whole.


Throughout much of our social experience we expect continuity: tomorrow will be pretty similar to today, and when changes occur they will be small and gradual. We expect our basic institutions — economic, social, and political — to maintain their core characteristics over long periods of time. We expect social attitudes and values to change only slowly, through gradual evolution rather than abrupt transformation. And we expect the same of a range of social conditions — for example, highway safety, crime rates, teen pregnancy rates, and similar social features.

It is evident that this expectation of gradual, continuous change is not always a valid guide to events. Abrupt, unexpected events occur — revolutions, mass cultural changes like the 1960s, sweeping political and legislative changes along the lines of the Reagan revolution. And of course we have the current example of abrupt declines in financial markets — see the graph of the Dow Jones Industrial Average for the week of September 23-30, 2008 below. So the expectation of continuity sometimes leads us astray. But continuity is probably among our most basic heuristic assumptions about the future when it comes to our expectations about the social world and our plans for the future.

The deeper question is an ontological one: what features of social causation and processes would either support or undermine the expectation of continuity? We can say quite a bit about the features of continuity and discontinuity in physical systems; famously, “non-linearities” occur in some physical systems that lead to singularities and discontinuities, but many physical systems are safely linear and continuous all the way down. And these mathematical features follow from the fundamental physical mechanisms that underlie physical systems. But what about the social world?

Take first the stability of large social and political institutions. Is there a reason to expect that major social and political institutions will retain their core features in face of disturbing influences? Consider for example the SEC as a financial regulatory institution; the European Union as a multinational legislative body; or a large health maintenance organization. Here institutional sociologists have provided a number of important insights. First, institutions often change through the accumulation of a myriad of small adaptations in different locations within the institution. This is a process that is likely to give rise to slow, continuous, gradual change for the institution as a whole; and this is continuous behavior. Second, though, institutional sociologists have identified important internal forces that work actively to preserve the workings of the institution: the stakeholders who benefit from the current arrangements. Stakeholders are given incentives to actively reinforce and preserve the current institutional arrangements — the status quo. Both of these factors suggest that institutional change will often be slow, gradual, and continuous.

Consider next the ways in which attitudes and values change in a population. Here it is plausible to observe that individuals change their attitudes and values slowly, through exposure to other individuals and behaviors. And the attitudes and values of a new generation are usually transmitted through processes that are highly decentralized — again suggesting a slow and gradual process of change. So this suggests that changes in attitudes and values might behave analogously to the spread of a pathogen through a population — with a slow and continuous spread of “contagion” resulting in a gradual change in population attitudes.

Consider last the example of social measures such as crime rates or teen pregnancy rates. If we take it as a premise that crime and teen pregnancy are influenced by social factors that in turn influence the behavior of individuals, and if we take it that these background social factors change slowly and continuously — then it is credible to reason that the aggregate measures of the associated behaviors will change slowly and continuously as well. The reasoning here is probabilistic: when large numbers of people with a specified set of background social psychologies are exposed to common environmental circumstances, then it is plausible to predict that the average rate of teen pregnancy will remain fairly steady if the background circumstances remain steady.

These are all reasons for expecting a degree of stability and continuity in social arrangements and social behavior. But before we conclude that the social world is a continuous place, consider this: We also have some pretty clear models of how social phenomena might occur in a dis-continuous fashion. Critical mass phenomena, tipping points, and catastrophic failures are examples of groups of social phenomena where we should expect discontinuities. The behavior of a disease in a population may change dramatically once a certain percentage of the population is infected (critical mass); a new slang expression (“yada yada yada”) may abruptly change its frequency of useage once a certain number of celebrities have adopted it (tipping point); a civic organization may be stretched to the breaking point by the addition of new unruly members and may suddenly collapse or mutate. (The hypothesis of punctuated equilibrium brings this sort of discontinuity into Darwinian theory of evolution.)

So there are some good foundational reasons for expecting a degree of continuity in the social environment; but there are also convincing models of social behavior that lead to important instances of discontinuous outcomes. This all seems to lead to the slightly worrisome piece of advice: don’t bet on the future when the stakes are high. Stock markets collapse; unexpected wars occur; and previously harmonious social groups fall into fratricidal violence. And there is no fool-proof way of determining whether a singularity is just around the corner.

Equilibrium reasoning

A system is in equilibrium with respect to a given characteristic when there is a system of forces in play that push the system back to the equilibrium state when it is subjected to small disturbances or changes. This is referred to as a homeostatic system.

The temperature in a goldfish bowl is in equilibrium if the bowl is provided with a thermostatically controlled heater and cooler; when the external temperature falls and the water temperature begins to fall as well, the thermostat registers the change of temperature and turns on the heater, and when the external temperature rises, the thermostat turns on the cooler. A population of squirrels in a bounded forest may reach an equilibrium size that is balanced by excess reproductive capacity (pushing the population upwards when it falls below the feeding capacity of the environment) and by excess mortality from poor nutrition (pushing the population downwards when it rises above the feeding capacity of the environment).

These examples embody very different causal mechanisms; but each represents a case in which the variable in question (temperature or population size) oscillates around the equilibrium value determined by the features of the environment and the features of the adjustment mechanisms.

There are other physical systems where the concept of equilibrium has no role. The trajectory of a fly ball is not an equilibrium outcome, but rather the direct causal consequence of the collision between bat and ball. And if the course of the baseball is disturbed — by impact with a passing bird or an updraft of wind — then the terminus of the ball’s flight will be different. The number of telephone calls between Phoenix and Albany is not an equilibrium outcome, even if it is fairly stable over time, but simply the aggregate consequence of the contingent telephone behavior of large numbers of people in the two cities. So systems that reach and maintain equilibrium are somewhat special.

It is also interesting to observe that there are other circumstances that produce a stable steady state in a system besides equilibrium processes. We may observe that elevators in a busy office building most frequently have 10 passengers. And the explanation for this may go along these lines: 10 is the maximum number of adults who can be squeezed into the elevator car; there are always many people waiting for an elevator; so virtually every car is at full capacity of 10 persons. This is an example of a pattern that derives from a population of events that demands full utilization, and a limit condition in the location where activity takes place. In this example, 10 passengers is not an equilibrium outcome but rather a forced outcome deriving from excess demand and a logistical constraint on the volume of activity. A large city may show a population history that indicates a trend of population increase from 4 million to 6 million to 10 million — and then it stops growing. And the explanation of the eventual stable population size of 10 million may depend on the fact that the water supplies available to the city cannot support a population significantly larger than 10 million.

To what extent are social ensembles and processes involved in equilibrium conditions? The paradigm example of equilibrium reasoning in the social sciences arises in microeconomic theory. Supply and demand curves are postulated as being fixed, and the price of a good is the equilibrium position where the quantity produced at this price is equal to the quantity consumed at this price. If the price rises, demand for the good falls and the price falls; if the price falls below the equilibrium position, producers manufacture less of the good and consumers demand more of it, which induces a price rise.

Another important example of equilibrium analysis in social behavior is the application of central place theory to economic geography. The theory is that places (cities, towns, villages) will be positioned across the countryside in a way that embodies a set of urban hierarchies and a set of commercial pathways. The topology of the system and the size of the nodes are postulated to be controlled by social variables such as transport cost and demand density. And individuals’ habitation decisions are influenced in a way that reinforces the topology and size hierarchy of the central place system.

However, even in these simple examples there are circumstances that can make the equilibrium condition difficult to attain. If the supply and demand curves shift periodically, then the equilibrium price itself moves around. If the price and production response characteristics are too large in their effects, then the system may keep bouncing around the equilibrium price, from “too high” to “too low” without the capacity of finetuning production and consumption. The resulting behavior would look like a graph of the stock market rather than a stable, regular system returning to its “equilibrium” value. And, in the case of habitation patterns, some places may gain a reputation for fun that offsets their disadvantages from the point of view of transport and demand density — thereby disrupting the expected equilibrium outcomes.

So if the conditions defining the terms of an equilibrium change too quickly, or if the feedback mechanisms that work to adjust the system value to current equilibrium conditions are too coarse, then we should not expect the system to arrive at an equilibrium state. (The marble rolling on a rotating dinner plate will continue to roll across all parts of the plate rather than arriving at the lowest point on the plate and staying there.)

I’m inclined to think that equilibria are relatively rare in the social world. The reasons for this are several: it is uncommon to be able to discover homeostatic mechanisms that adjust social variables; when quasi-homeostatic mechanisms exist, they are often too coarse to lead to equilibrium; and, most fundamentally, the constraints that constitute the boundary conditions for idealized equilibria among social variables are often themselves changing too rapidly to permit an equilibrium to emerge. Instead, social outcomes more often look like constrained random walks, in which social actions occur in a fairly uncoordinated way at the individual level and aggregate to singular social outcomes that are highly path-dependent and contingent. Social outcomes are more often stochastic than being guided by homeostatic mechanisms.

Turning points

Are there turning points in history? How would we know if we’re in the midst of one? Does the current financial crisis represent a turning point in the development of the US economy? Did the election of Ronald Reagan represent a turning point in American politics and government?

Often what is announced as a turning point eventually seems like a change without a difference — an example of rearranging the deck chairs on the Titanic, of changing drivers but not direction. Nguyen van Thieu takes office in Vietnam in 1967 and a new era is announced; but then the same old policies persist and Vietnam slides ever further towards Communist victory.

A turning point might be defined as an event, action, or choice, that profoundly alters the direction of a whole series of subsequent events. The New Deal is perhaps a candidate in the development of the political-social culture of the United States — a new set of policies, laws, and strategies that set the United States on a new direction and that substantially constrained later choices by government. The notion of a turning point conveys the situation of contingency — up until T things might have continued within the existing pattern P, but after T things shifted to P‘. And it conveys the idea of path dependency as well — now that the turning point has occurred and P’ is embodied, it is much more difficult to return to P. So a turning point results from some contingent event that occurs within a system at a particular time and substantially inflects the future dynamics of development of the system. The idea turns on the background assumption that there are mechanisms or forces that sustain the development of the system, and that contingent events can “push” the system onto a different course for a while.

What sorts of things can have turning points? Can an individual have one? What about a family or a marriage? How about a business or a university? And how about a nation or a civilization? We might say that anything that has a recognizable and somewhat stable pattern of development can display a turning point. So each of these orders of human affairs can do so. An individual may be influenced by a traumatic event or a charismatic person and may change his ways; from that point forward he may behave differently — more honestly, more cautiously, more compassionately. The event was a turning point on his development. A “velvet revolution” may be on a course that gives great importance to non-violent tactics. Then something happens — a violent repression by the state, the emergence of a new clique of leaders more open to violence. The velvet revolution undergoes a turning point and becomes more violent in its strategies.

Schematically, the idea of a turning point involves an ontology something like this: system properties in a state of persistence > singular event > new system properties in a state of persistence.

So how could we know that we’re at a turning point? The answer seems to be: we can’t. Only the larger course of history can indicate whether contemporary changes will be large and persistent, or cosmetic and evanescent.

The idea of a “turning point” is perhaps one of the analytical categories that we use to characterize and analyze the sweep of history. It is a narrative device that highlights persistence, contingency, and direction. And, it would appear, we’ve got to wait until the Owl of Minerva spreads its wings before we can say with confidence when they occur.

What social science can do

Quite a few postings here emphasize the limits of social science knowledge. Prediction of the behavior of large social wholes is difficult to impossible. There are few strong regularities among social phenomena. Social entities and processes are heterogeneous, plastic, and path-dependent. So the question arises: what can the social sciences do that takes them beyond the realm of description and reportage of the blooming, buzzing confusion of social comings and goings, to something that is more explanatory and generalizable?

I think there is an answer to this, and it has to do with identifying mid-level mechanisms and processes that recur in roughly similar ways in a range of different social settings. The social sciences can identify a fairly large number of these sorts of recurring mechanisms. For example —

  • public goods problems
  • political entrepreneurship
  • principal-agent problems
  • features of ethnic or religious group mobilization
  • market mechanisms and failures
  • rent-seeking behavior
  • the social psychology associated with small groups
  • the moral emotions of family and kinship
  • the dynamics of a transport network
  • the communications characteristics of medium-size social networks
  • the psychology and circumstances of solidarity

Further, the social sciences can attempt to discover the circumstances at the level of individual agents that make these mechanisms robust across social settings. They can model the dynamics and features of aggregation that they possess. And they can attempt to discover the workings of such mechanisms in particular social and historical settings, and work towards explanations of particular features of these events based on their theories of the properties of the mechanisms. Finally, they can attempt to find rigorous ways of attempting to model the effects of aggregating multiple mechanisms in a particular setting.

What this comes down to is the view that the main theoretical and generalizing contribution that the social sciences can make is the discovery and analysis of a wise range of recurring social mechanisms grounded in features of human agency and common institutional and material settings. They can help to constitute a rich tool box for social explanation. And, in a weak and fallible way, they can lay the basis for some limited social generalizations — for example, “In circumstances where a group of independent individuals make private decisions about their actions, the public goods shared by the group will be under-provided.”

This approach affords a degree of explanatory capacity and generalization to the social sciences. What it does not underwrite is the ability to offer general, comprehensive theories about any complex kind of phenomenon — cities, schools, revolutions. And it does not provide a foundation for confidence about large predictions about the future behavior of complex social wholes.

Social surprises

The near meltdown of the US financial system this week came as a surprise to most of us — experts, legislators, and citizens alike. That isn’t to say that the components of the disaster were unknown — the subprime crisis, the earlier financial undoings of Fannie Mae and Bear Stearns this summer, and the sudden collapse of Lehman Brothers last week. But what has come as a surprise is the severity of the warnings by the Federal Reserve and Treasury that the entire financial system is only a few steps from seizure and collapse. This is a catastrophic system failure — and no one would have anticipated its possibility six months ago.

Think of a few other surprises in the past thirty years — the collapse of the Soviet Union, the Iranian Revolution, or the emergence of China as a roaring engine of market-based growth. In each case the event was a discontinuous break from the trajectory of the past, and it surprised experts and citizens alike. (The photo above depicts the surprising Yeltsin standing on a tank in 1991.)

So what is a surprise? It is an event that shouldn’t have happened, given our best understanding of how things work. It is an event that deviates widely from our most informed expectations, given our best beliefs about the causal environment in which it takes place. A surprise is a deviation between our expectations about the world’s behavior, and the events that actually take place. Many of our expectations are based on the idea of continuity: tomorrow will be pretty similar to today; a delta change in the background will create at most an epsilon change in the outcome. A surprise is a circumstance that appears to represent a discontinuity in a historical series.

It would be a major surprise if the sun suddenly stopped shining, because we understand the physics of fusion that sustains the sun’s energy production. It would be a major surprise to discover a population of animals in which acquired traits are passed across generations, given our understanding of the mechanisms of evolution. And it would be a major surprise if a presidential election were decided by a unanimous vote for one candidate, given our understanding of how the voting process works. The natural world doesn’t present us with a large number of surprises; but history and social life are full of them.

The occurrence of major surprises in history and social life is an important reminder that our understanding of the complex processes that are underway in the social world is radically incomplete and inexact. We cannot fully anticipate the behavior of the subsystems that we study — financial systems, political regimes, ensembles of collective behavior — and we especially cannot fully anticipate the interactions that arise when processes and systems intersect. Often we cannot even offer reliable approximations of what the effects are likely to be of a given intervention. This has a major implication: we need to be very modest in the predictions we make about the social world, and we need to be cautious about the efforts at social engineering that we engage in. The likelihood of unforeseen and uncalculated consequences is great.

And in fact commentators are now raising exactly these concerns about the 700 billion dollar rescue plan currently being designed by the Bush administration to save the financial system. “Will it work?” is the headline; “What unforeseen consequences will it produce?” is the subtext; and “Who will benefit?” is the natural followup question.

It is difficult to reconcile this caution about the limits of our rational expectations about the future based on social science knowledge, with the need for action and policy change in times of crisis. If we cannot rely on our expectations about what effects an intervention is likely to have, then we can’t have confidence in the actions and policies that we choose. And yet we must act; if war is looming, if famine is breaking out, if the banking system is teetering, a government needs to adopt policies that are well designed to minimize the bad consequences. It is necessary to make decisions about action that are based on incomplete information and insufficient theory. So it is a major challenge for the theory of public policy, to attempt to incorporate the limits of knowledge about consequences into the design of a policy process. One approach that might be taken is the model of designing for “soft landings” — designing strategies that are likely to do the least harm if they function differently than expected. Another is to emulate a strategy that safety engineers employ when designing complex, dangerous systems: to attempt to de-link the subsystems to the extent possible, in order to minimize the likelihood of unforeseeable interactions. (Nancy Leveson describes some of these strategies in Safeware: System Safety and Computers.) And there are probably other heuristics that could be imagined as well.

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