Heuristics for a mechanisms-based methodology

Let’s imagine that I’m a young sociologist or political scientist who has gotten interested in the social-mechanisms debates, and I’d like to frame my next research project around a set of heuristics that are suggested by the mechanisms approach. What might some of those heuristics look like? What is a “mechanisms-based methodology” for sociological research? And how would my research play out in concrete terms? Here are a few heuristics we might consider.

  1. Identify one or more clear cases of the phenomenon I’m interested in understanding
  2. Gain enough empirical detail about the cases to permit close examination of possible causal linkages
  3. Acquaint myself with a broad range of social mechanisms from a range of the social sciences (political science, economics, anthropology, public choice theory, critical race studies, women’s studies, …)
  4. Attempt to segment the phenomena into manageable components that may admit of separate study and analysis
  5. Use the method of process-tracing to attempt to establish what appear to be causal linkages among the phenomena
  6. Use my imagination and puzzle-solving ability to attempt to fit one or more of the available mechanisms into the phenomena I observe
  7. Engage in quasi-experimental reasoning to probe the resulting analysis: if mechanism M is involved, what other effects would we expect to be present as well? Do the empirical realities of the case fit these hypothetical expectations?

These heuristics represent in a rough-and-ready way the idea that there are some well understood social processes in the world that have been explored in a lot of empirical and theoretical detail. The social sciences collectively provide a very rich toolbox of mechanisms that researchers have investigated and validated. We know how these mechanisms work, and we can observe them in a range of settings. This is a realist observation: the social world is not infinitely variable, and there is a substrate of activity, action, and interaction whose workings give rise to a number of well understood mechanisms. Here I would include free rider problems, contagion, provocation, escalation, coercion, and log-rolling as a very miscellaneous set of exemplars. So if we choose to pursue a mechanisms-based methodology, we are basically following a very basic intuition of realism by asking the question, “how does this social phenomenon work in the settings in which we find it?”.

So how might a research project unfold if we adopt heuristics like these? Here is a striking example of a mechanisms approach within new-institutionalist research, Jean Ensminger’s account of bridewealth in the cattle-herding culture of Kenya (Making a Market: The Institutional Transformation of an African Society). First, some background. The cattle-herding economic regime of the Orma pastoralists of Kenya underwent substantial changes in the 1970s and 1980s. Commons grazing practices began to give way to restricted pasturage; wage labor among herders came to replace familial and patron-client relations; and a whole series of changes in the property system surrounding the cattle economy transpired as well. This is an excellent example for empirical study from a new-institutionalist perspective. What explained the particular configuration of norms and institutions of the earlier period? And what social pressures led to the transition towards a more impersonal relationship between owners and herders? These are questions about social causation at multiple levels.

Ensminger examines these questions from the perspective of the new institutionalism. Building on the theoretical frameworks of Douglass North and others, she undertakes to provide an analysis of the workings of traditional Orma cattle-management practices and an explanation of the process of change and dissolution that these practices underwent in the decades following 1960. The book puts forward a combination of close ethnographic detail and sophisticated use of theoretical ideas to explain complex local phenomena.

How does the new institutionalism approach help to explain the features of the traditional Orma cattle regime identified by Ensminger’s study? The key institutions in the earlier period are the terms of employment of cattle herders in mobile cattle camps. The traditional employment practice takes the pattern of an embroidered patron-client relation. The cattle owner provides a basic wage contract to the herder (food, clothing, and one head of cattle per year). The good herder is treated paternally, with additional “gifts” at the end of the season (additional clothing, an additional animal, and payment of the herder’s bridewealth after years of service). The relation between patron and client is multi-stranded, enduring, and paternal.

Ensminger understands this traditional practice as a solution to an obvious problem associated with mobile cattle camps, which is fundamentally a principal-agent problem. Supervision costs are very high, since the owner does not travel with the camp. The owner must depend on the herder to use his skill and diligence in a variety of difficult circumstances—rescuing stranded cattle, searching out lost animals, and maintaining control of the herd during harsh conditions. There are obvious short-term incentives and opportunities for the herder to cheat the employer—e.g. allowing stranded animals to perish, giving up on searches for lost animals, or even selling animals during times of distress. The patron-client relation is one possible solution to this principal-agent problem. An embedded patron-client relation gives the herder a long-term incentive to provide high-quality labor, for the quality of work can be assessed at the end of the season by assessment of the health and size of the herd. The patron has an incentive to cheat the client—e.g. by refusing to pay the herder’s bridewealth after years of service. But here the patron’s interest in reputation comes into play: a cattle owner with a reputation for cheating his clients will find it difficult to recruit high-quality herders.

This account serves to explain the evolution and persistence of the patron-client relation in cattle-camps on the basis of transaction costs (costs of supervision). Arrangements will be selected that serve to minimize transaction costs. In the circumstances of traditional cattle-rearing among the Orma the transaction costs of a straight wage-labor system are substantially greater than those associated with a patron-client system. Therefore the patron-client system is selected.

This analysis identifies mechanisms at two levels. First, the patron-client relation is the mechanism through which the endemic principal-agent problem facing cattle owners is solved. The normal workings of this relation give both patron and client a set of incentives that leads to a stable labor relation. The higher-level mechanism is somewhat less explicit, but is needed for the explanation to fully satisfy us. This is the mechanism through which the new social relationship (patron-client interdependency) is introduced and sustained. It may be the result of conscious institutional design or it may be a random variation in social space that is emulated when owners and herders notice the advantages it brings. Towards the end of the account we are led to inquire about another higher-level mechanism, the processes through which the traditional arrangement is eroded and replaced by short-term labor contracts.

This framework also illustrates the seventh heuristic above, the use of counterfactual reasoning. This account would suggest that if transaction costs change substantially (through improved transportation, for example, or through the creation of fixed grazing areas), that the terms of employment would change as well (in the direction of less costly pure wage-labor contracts). And in fact this is what Ensminger finds among the Orma. When villages begin to establish “restricted grazing areas” in the environs of the village, it is feasible for cattle owners to directly supervise the management of their herds; and in these circumstances Ensminger finds an increase in pure wage labor contracts.

What are the scientific achievements of this account? There are several. First, it takes a complicated and detailed case of collective behavior and it makes sense of the case. It illuminates the factors that influence choices by the various participants. Second, it provides insight into how these social transactions work (the mechanisms that are embodied in the story). Third, it begins to answer — or at least to pose in a compelling way — the question of the driving forces in institutional change. This too is a causal mechanism question; it is a question that focuses our attention on the concrete social processes that push one set of social behaviors and norms in the direction of another set of behaviors and norms. Finally, it is an empirically grounded account that gives us a basis for a degree of rational confidence in the findings. The case has the features that we should expect it to have if the mechanisms and processes in fact worked as they are described to do.

A final achievement of this account is very helpful in the context of our efforts to arrive at explanations of features of the social world. This is the fact that the account is logically independent of an effort to arrive at strong generalizations about behavior everywhere. The account that Ensminger provides is contextualized and specific, and it does not depend on the assumption that similar social problems will be solved in the same way in other contexts. There is no underlying assumption that this interesting set of institutional facts should be derivable from a general theory of behavior and institutions. Instead, the explanation is carefully crafted to identify the specific (and perhaps unique) features of the historical setting in which the phenomenon is observed.

(Here is a nice short article by David Collier on the logic of process-tracing; link. And here is an interesting piece by Aussems, Boomsma, and Snijders on the use of quasi-experimental methods in the social sciences; link.)

Realism and methodology

Methodology has to do with the strategies and heuristics through which we attempt to understand a complicated empirical reality (link). Our methodological assumptions guide us in the ways in which we attempt to collect data, the kinds of data we collect, the explanatory hypotheses we bring forward for that range of empirical findings, and the ways we seek to validate our findings. Methodology is to the philosophy of social science as historiography is to the philosophy of history.

Realism is also a set of assumptions that we bring to empirical investigation. But in this case the assumptions are about ontology — how the world works, in the most general ways. Realism asserts that there are real underlying causes, structures, processes, and entities that give rise to the observations we make of the world, natural and social. And it postulates that it is scientifically appropriate to form theories and hypotheses about these underlying causes in order to arrive at explanations of what we observe.

This description of realism is couched in terms of a distinction between what is observable and what is unobservable but nonetheless real — the “observation-theoretic” distinction. But of course the dividing line between the two categories shifts over time. What was once hypothetical becomes observable. Extra-solar planetary bodies, bosons, and viruses were once unobservable; they are now observable using various forms of scientific instrumentation and measurement. So the distinction is not fundamental; this was an essential part of the argument against positivist philosophy of science. And we might say the same about many social entities and structures as well. We understand “ideology” much better today than when Marx theorized about this idea in the mid-19th century, and using a variety of social research methods (public opinion surveys, World Values Survey, ethnographic observation, structured interviews) we can identify and track shifts in the ideology of a group over time. We can observe and track ideologies in a population. (We may now use a different vocabulary — mentality, belief framework, political values.)

There are several realist methodologies that are possible in the social sciences. The methodology of paired comparisons is a common part of research strategies in the historical social sciences. This is often referred to as “small-N research.” (Here is a description of the method as practiced by Sid Tarrow; linklink.) The method of paired comparisons is also based on realism and derives from causal ideas; but it is not specifically derived from the idea of causal mechanisms.  Rather, it derives from the simpler notion that causal factors function as something like necessary and/or sufficient conditions for outcomes. So if we can find cases that differ in outcome and embody only a small number of potential contributing causal factors, we can use Mill’s methods (or more general truth-table methods) to sort out the causal roles played by the factors. (Here is a discussion of some of these concepts; link.) These ideas contribute to methodology at two levels: they give the investigator a specific idea about how to lay out his/her research (“seek out relevantly similar cases with different outcomes”), and they embody a method of inference from findings to conclusions about causal relations (the truth-table method). These methods allow the researcher to arrive at statements about which factors play a role in the production of other factors. (This is a logically similar role to the use of multiple regression in quantitative studies.)

Another possible realist approach to methodology is causal mechanisms theory (CM). It rests on the idea that events and outcomes are caused by specific happenings and powers, and it proposes that a good approach to a scientific explanation of an outcome or pattern is to discover the real mechanisms that typically bring it about. It also brings forward an old idea about causation — no action at a distance. So if we want to maintain that class privilege causes ideological commitment, we need to be able to tell an empirically grounded story about how the first kind of thing conveys its influence to changes in the second kind of thing. (This is essentially the call for microfoundations; link.) Causal mechanisms theory is more basic than either paired comparisons or statistical causal modeling, in that it provides a further explanation for findings produced by either of these other methods. Once we have a conception of the mechanisms involved in a given social process, we are in a position to interpret a statistical finding as well as a finding about the necessary and/or sufficient conditions provided by a list of antecedent conditions for an outcome.

It is an interesting question to consider whether realism in ontology leads to important differences in methodology. In particular, does the idea that things happen as the result of an ensemble of real causal mechanisms that can be separately understood lead to important new ideas about methodology and inquiry?

Craver and Darden argue in In Search of Mechanisms: Discoveries across the Life Sciences that mechanisms theory does in fact contribute substantially to contemporary research in biology, at a full range of levels (link). They maintain that the key goal for much research in contemporary biology is to discover the mechanisms that produce an outcome, and that a central component of this methodology is the effort to explain a given phenomenon by trying to fit one or more known mechanisms to the observed process. So working with a toolbox of known mechanisms and “problem-solving” to account for the new phenomenon is an important heuristic in biology. This approach is both ontological and methodological; it presupposes that there are real underlying mechanisms, and it recommends to the researcher that he/she be well acquainted with the current inventory of known mechanisms that may be applied to new settings.

I think there is a strong counterpart to this idea in a lot of sociological research as well. There are well understood social mechanisms that sociologists, political scientists, and other researchers have documented — easy riders, prisoners dilemmas, conditional altruism — and the researcher often can systematically explore whether one or more of the known mechanisms is contributing to the complex social outcomes he or she is concerned with. A good example is found in Howard Kimeldorf’s Reds or Rackets?: The Making of Radical and Conservative Unions on the Waterfront. Kimeldorf compares two detailed case histories and strives to identify the concrete social mechanisms that led to different outcomes in the two cases. The mechanisms are familiar from other sociological research; Kimeldorf’s work serves to show how specific mechanisms were in play in the cases he considers.

This kind of work can be described as problem-solving heuristics based on application of a known inventory of mechanisms. It could also be described as a “normal science” process where small theories of known processes are redeployed to explain novel outcomes. As Kuhn maintains, normal science is incremental but creative and necessary in the progress of science.

A somewhat more open-ended kind of inquiry is aimed at discovery of novel mechanisms. McAdam, Tarrow and Tilly sometimes engage in this second kind of discovery in Dynamics of Contention — for example, the mechanism of social disintegration (kl 3050). Another good example of discovery of mechanisms is Akerlof’s exposition of the “market for lemons” (link), where he lays out the behavioral consequences of market behavior with asymmetric knowledge between buyer and seller.

So we might say that mechanisms theory gives rise to two different kinds of research methodology — application of the known inventory to novel cases and search for novel mechanisms (based on theory or empirical research).

Causal-mechanisms theory also suggests a different approach to data gathering and a different mode of reasoning from both quantitative and comparative methods. The approach is the case-studies method: identify a small set of cases and gain enough knowledge about how they played out to be in a position to form hypotheses about the specific causal linkages that occurred (mechanisms).

This approach is less interested in finding high-level generalizations and more concerned about the discovery of the real inner workings of various phenomena. Causal mechanisms methodology can be applied to single cases (the Russian Revolution, the occurrence of the Great Leap Forward famine), without the claim to offering a general causal account of famines or revolutions. So causal mechanisms method (and ontology) pushes downward the focus of research, from the macro level to the more granular level.

The inference and validation component associated with CM looks like a combination of piecemeal verification (link) and formal modeling (link). The case-studies approach permits the researcher to probe the available evidence to validate specific hypotheses about the mechanisms that were present in the historical case. The researcher is also able to try to create a simulation of the social situation under study, confirm as much of the causal internal connectedness as possible from study of the case, and examine whether the model conforms in important respects to the observed outcomes. Agent-based models represent one such set of modeling techniques; but there are others.

So the methodological ideas associated with CM theory differ from both small-N and large-N research. The search for causal mechanisms is largely agnostic about high-level regularities — either of things like revolutions or things like metals. It is an approach that encourages a more specific focus on this case or that small handful of cases, rather than a focus on finding general causal properties of high-level entities. And it is more open to and tolerant of the possibility of a degree of contingency and variation within a domain of phenomena. To postulate that civil disorders are affected by a group of well-understood social mechanisms does not imply that there are strong regularities across all civil disorders, or that these mechanisms work in exactly the same way in all circumstances. So the features of contingency and context dependence play an organic role within CM methodology and fit badly in paired-comparisons research and statistical modeling approaches.

So it seems that the ontology of causal-mechanisms theory does in fact provide a set of heuristics and procedures for undertaking social research. CM does have implications for social-science methodology.

What is methodology?


As social science researchers, we would all like to have an excellent methodology for carrying out the tasks we confront in our scientific work. But what precisely are we looking for when we aspire to this goal? What is a methodology, and what is it intended to allow us to do?

A methodology is a set of ideas or guidelines about how to proceed in gathering and validating knowledge of a subject matter. Different areas of science have developed very different bodies of methodology on the basis of which to conduct their research. We might say that a methodology provides a guide for carrying out some or all of the following activities:

  • probing the empirical details of a domain of phenomena
  • discovering explanations of surprising outcomes or patterns
  • identifying entities or forces
  • establishing patterns
  • providing predictions
  • separating noise from signal
  • using empirical reasoning to assess hypotheses and assertions
Here is what Andrew Abbott has to say about methods in Methods of Discovery: Heuristics for the Social Sciences:

Social scientists have a number of methods, stylized ways of conducting their research that comprise routine and accepted procedures for doing the rigorous side of science. Each method is loosely attached to a community of social scientists  for whom it is the right way to do things. But no method is the exclusive property of any one of the social sciences, nor is any social science, with the possible exception of anthropology, principally organized around the use of one particular method. (13)

So a method or a methodology is a set of recommendations for how to proceed in doing scientific research within a certain domain. Sometimes in the history of philosophy there has been a hope that science could proceed on the basis of a pure inductive logic: collect the data, analyze the data, sift through the findings, report the strongest regularities found in the data set. But scientific inquiry requires more than this; it requires discovery and imagination.

What form might a methodology take? The simplest idea is that a methodology is a recipe for arriving at justified scientific statements with respect to a domain of empirical phenomena. A recipe is a set of instructions for treating a number of ingredients in a sequential way and producing a specific kind of output — a soufflé or a bowl of pad thai. If you follow the recipe, you are almost certain to arrive at the soufflé. But it is clear that scientific methodology cannot be as prescriptive as a recipe. There is no set of rules that are certain or likely to lead to the discovery of compelling hypotheses and explanations.So if a scientific methodology isn’t a set of recipes, then what is it? Here is another possibility: a methodology consists of a set of heuristics that serve to guide the activities, data collection, and hypothesis formation of the scientist. A heuristic is also a set of rules; but it is weaker than a recipe in that there is no guarantee of success. Here is a heuristic for consumers: “If you are selecting a used car to purchase, pay attention to rust spots.” This is a good guide to action, not because rust spots are the most important part of a car’s quality, but because they may serve as a proxy for the attentiveness to maintenance of the previous owner — and therefore be an indication of hidden defects.

Andrew Abbott mentions several key topics for specification through methodology — “how to propose a question, how to design a study, how to draw inferences, how to acquire and analyze data” (13), and he shows that we can classify methods by placing them into the types of question they answer.

types of data gathering
           data analysis
        posing a question
  • history
  • direct interpretation
  • case-study analysis
  • ethnography
  • quantitative analysis
  • small-N comparison
  • surveys
  • formal modeling
  • large-N analysis
  • record-based analysis
Abbott suggests that these varieties can be combined into five basic approaches:
  • ethnography
  • historical narration
  • standard causal analysis
  • small-N comparison
  • formalization
And he arranges them in a three-dimensional space, with each dimension increasing from very particular knowledge at the origin to more abstract knowledge further out the axis. (Commonsense understanding of the facts lies at the origin of the mapping.) The three axes are formal modeling (syntactic program), pattern finding (semantic program), and cause finding (pragmatic program) (28).
Abbott is a sociologist whose empirical and theoretical work is genuinely original and important, and we can learn a lot from his practice as a working researcher. His meta-analysis of methodology, on the other hand, seems fairly distant from his own practice. And I’m not sure that the analysis of methodology represented here provides a lot of insight into the research strategies of other talented social scientists (e.g. Tilly, Steinmetz, Perrow, Fligstein). This perhaps illustrates a common occurrence in the history of science: researchers are not always the best interpreters of their own practice.

It is also interesting to observe that the discovery of causal mechanisms has no explicit mention in this scheme. Abbott never refers to causal mechanisms in the book, and none of the methods he highlights allow us to see what he might think about the mechanisms approach. It would appear that mechanisms theory would reflect the pragmatic program (searching for causal relationships) and the semantic program (discovering patterns in the observable data).

My own map of the varieties of the methods of the social sciences suggests a different scheme altogether. This is represented in the figure at the top of the post.

Skocpol on the 1979 revolution in Iran


An earlier post reviewed Theda Skocpol’s effort in States and Social Revolutions: A Comparative Analysis of France, Russia and China to provide a comparative, structural account of the occurrence of social revolutions. There I suggested that the account is too deterministic and too abstract. It gives the impression, perhaps undeserved, that there are only a small number of pathways through which social revolutions can take place, and only a small number of causal factors that serve to bring them about. The impression emerges that Skocpol has offered a set of templates into which we should expect other social revolutions to fit.

One of the benefits of re-reading a book that is now 35 years old, however, is that history presents new cases that are appropriately considered by the theory. One such case is the Iranian Revolution, which unfolded in 1979. And, as Skocpol indicates forthrightly, the Iranian Revolution does not fit the model that she puts forward in States and Social Revolutions very closely. Skocpol considered the complexities and challenges which the Iranian Revolution posed to her theory in an article which appeared in 1981, before the dust had fully settled in Tehran. The article is included in her collection, Social Revolutions in the Modern World. Here is the challenge that the Iranian Revolution created for Skocpol’s causal theory of social revolutions:

A few of us have also been inspired to probe the Iranian sociopolitical realities behind these events. For me, such probing was irresistible – above all because the Iranian revolution struck me in some ways is quite anomalous. This revolution surely qualifies as a sort of “social revolution.” Yet its unfolding – especially in the events leading to the Shah’s overthrow – challenged expectations about revolutionary causation that I developed through comparative-historical research on the French, Russian, and Chinese Revolutions. (240)

Skocpol finds that the large features of the Iranian Revolution did indeed fit the terms of her definition of a social revolution, but that the causal background and components of this historical event did not fit her expectations.

The initial stages of the Iranian revolution obviously challenged my previously worked-out notions about the causes of social revolutions. Three apparent difficulties come immediately to mind. First, the Iranian Revolution does seem as if it might have been simply a product of excessively rapid modernization…. Second, in a striking departure from the regularities of revolutionary history, the Shah’s army and police – modern coercive organizations over 300,000 men strong – were rendered ineffective in the revolutionary process between 1977 and early 1979 without the occurrence of a military defeat in foreign war and without pressures from abroad…. Third, if ever there has been a revolution deliberately “made” by a mass–based social movement aiming to overthrow the old order, the Iranian revolution against the Shah surely is it. (241-242)

So the Iranian Revolution does not fit the mold. Does this imply that the interpretation of social revolution offered in States and Social Revolutions is refuted? Or does it imply instead that there are more narrow limits on the strength of the generalizations offered in that book than appear on first reading? In fact, it seems that the latter is the case:

Fortunately, in States and Social Revolutions I explicitly denied the possibility of fruitfulness of a general causal theory of revolutions that would apply across all times and places…. The Iranian Revolution can be interpreted in terms analytically consistent with the explanatory principles I used in States and Social Revolutions – this is what I shall briefly try to show. However, this remarkable revolution also forces me to deepen my understanding of the possible role of idea systems and cultural understandings in the shaping of political action – in ways that I show indicate recurrently at appropriate points in this article. (243)

One important difference between the revolutions studied by Skocpol’s earlier work and the Iranian revolution is the urban base of the latter revolution. “Opposition to the Shah was centered in urban communal enclaves where autonomous and solitary collective resistance was possible” (245). “In the mass movements against the Shah during 1977 and 1978, the traditional urban communities of Iran were to play an indispensable role in mobilizing in sustaining the core of popular resistance” (246). This is a difference in the social composition of the social revolution; peasant unrest and uprisings were crucial in the cases of France, Russia, and China; but not in the case of Iran.

Another key difference in the circumstances of the Iranian Revolution was the role played by Shi’a Islam. This is what Skocpol was referring to when she indicated the important role of idea systems and cultural understandings.  “In sum, Shi’a Islam was both organizationally and culturally crucial to the making of the Iranian revolution against the Shah” (249). So ideas and values played a role in mobilizing and sustaining revolutionary actions by the population that does not have a valid counterpart in China, France, or Russia. This is a more serious divergence from the reasoning of SSR, because it introduces an entirely new causal factor — “idea systems”. In SSR the motivations that are ascribed to activists and followers are interest-based; whereas her treatment of Shi’a Islam and the Iranian Revolution forces a broadening of the theory of the actor to incorporate the workings of non-material values and commitments.

How does Skocpol think that ideas and culture function in the context of social unrest? “In and of themselves, the culture and networks of communication do not dictate mass revolutionary action. But if a historical conjuncture arises in which a vulnerable state faces oppositionally inclined social groups possessing solidarity, autonomy, and independent economic resources, then the sorts of moral symbols and forms of social communication offered by Shi’a Islam in Iran can sustain the self-conscious making of a revolution” (250). So the value system of Shi’a Islam, and the passions and commitments that it engendered, played a key causal role in the success of the revolutionary actors in Tehran, in the view that Skocpol offers in the current article.

So the social actors can be different and the causal factors involved can be different. What about the outcomes of the processes of social revolution? Can we at least keep the idea that a social revolution, once underway, has a certain logic of development that leads to certain kinds of outcomes? Here again, Skocpol is clear in saying that we cannot.

On the contrary, Skocpol brings the fact of contingency into her account here in a way that is not apparent in the earlier book. In her treatment of the Iranian Revolution she is brought to acknowledge and recognize the deep contingency that exists within a social revolution.

Of course, events in Iran may outrun that Shi’a revolutionary leadership. The clerics may lose their political unity and the army or a secular political party may step in. Or regional revolts and foreign subversion may lead to the dismemberment of the country. (254)

Or in other words: there is no necessary sequence of events in this social revolution, or any other.So what remains? How does comparative study of social revolutions contribute to explanation? Rather than hoping for a causal diagram that identifies factors, forces, and outcomes, it seems unavoidable that we need to look for more limited findings. And this pushes us in the direction of the disaggregated approach that McAdam, Tarrow, and Tilly take in their own subsequent treatments of social contention in Dynamics of Contention.

According to that approach, there are some common causal processes — we would now call them “mechanisms of contention” — that give some insight into the critical events that transpire within a given historical sequence. But these common mechanisms do not have primacy over the myriad other factors in play — the behavior of the military, the emergence of a secular political party, the sudden appearance of a charismatic movie actor turned political leader, the eruption of international conflict (like the war that Iran was forced to wage with Iraq), and countless other possible causal branches. And this means something very deep for the project of comparative theorizing about social revolution, or any other large-scale social change: we should regard these processes as importantly sui generis rather than general, and we should look for the sub-processes and mechanisms rather than high-level macro-causal relationships.

Skocpol on the Chinese Revolution

(Sources: States and Social Revolutions, pp. 155, 282)

In States and Social Revolutions: A Comparative Analysis of France, Russia and China (1979) Theda Skocpol set out to discover a causal analysis of the occurrence of social revolution, and she offered case-study narratives of the major revolutions in France, Russia, and China. She provides a 54-page narrative of the Chinese Revolution which can serve as a thumbnail account of the major events and causal factors that made it up. Her narrative is deliberately framed in comparative terms; she wants to locate features of the Chinese situation in relation to relevantly similar characteristics of the French and Russian cases.

Here is Skocpol’s definition of a social revolution:
Social revolutions are rapid, basic transformations of a society’s state and class structures; and they are accompanied and in part carried through by class-based revolts from below. Social revolutions are set apart from other sorts of conflicts and transformative processes above all by the combination of two coincidences: the coincidence of societal structural change with class upheaval; and the coincidence of political with social transformation. (Introduction)

The summary tables above both mirror the definition Skocpol has crafted and reveal the essence of her comparative causal analysis of the three primary cases. Tables 1A and 1B provide a coding of the states of affairs in France, Russia, and China in what she identifies as the relevant initial structural conditions — conditions relevant to political crisis and peasant uprisings. Table 1C represents her view of the proximate outcomes of these conjunctions in the three cases — breakdown of effective state power and emergence of widespread rural unrest. And Table 2 reflects her effort to code the more distant outcomes in the three cases, when the dust had settled — the nature of the political configurations and state systems that emerged from the revolutions that took place.
This is historical sociology, not social-science history. The goal is not to be a full historical account of these revolutions in detail, but instead to identify relatively limited number of structural and agentic causes that may be relevant to the occurrence of revolution in the individual cases.
It is worth noting what this account does not provide. It does not attempt to disaggregate revolutionary processes into underlying causal social mechanisms. Rather, it presupposes a fairly macro-level conception of causal conditions and factors. This is what allows Skocpol to make use of a Millian method for discovering what she takes to be necessary and sufficient causes for social revolution. And second, it gives no attention to the possibilities of contingency and path dependency. Rather, she is looking for causal conditions that co-occur in some historical circumstances and then lead to social revolution as an outcome. This is the conjunctural part of her story.
This is a very specific conception of comparativist social explanation. It is anti-positivist, in an important sense, in that it expressly rejects the idea that there might be fundamental laws from which the occurrence of revolution might be derived. But it is also anti-reductionist, in that it is not interested in explaining the large outcomes, or similarities of oarge outcomes, based on underlying mechanisms or processes. I find it hard to think of an example of causal explanation in biology, geology, or physics that has a similar structure. Explanations of the transition of a group of tree species within a forest might look similar — the ecologist looks for macro-level circumstances that favor one species over another. But there is always the underlying mechanism of natural selection and differential rates of reproduction that provides a microfoundation for the explanation.
In Skocpol’s analysis of China several events and structures were most fundamental in the unfolding of China’s social revolution.

  1. The devolution of power to the regional level that had occurred in the final years of the old regime (pre-1911). This reflects the great weakening of the central imperial state and military and the emergence of warlords and local elites with their own militias.
  2. The poverty and oppression of the peasantry. The deprivation of farmers at the hands of landlords and local elites left peasants in a state of misery and deprivation that left them ready for radicalization and mobilization.
  3. The fact of European imperialist military and economic pressure from mid-nineteenth century forward, which both weakened the imperial state and delegitimized it.

The account of the Chinese Revolution provided by Bianco and described in the previous post gives attention to another key factor: the organizational capacity and revolutionary strategies of the CCP. To some extent this runs contrary to Skocpol’s vigorous opposition to the idea of revolution as an intentional process. But Bianco is clearly right, that the strategies and coordination of the CCP provided a vital component of the eventual success of the Chinese Revolution.

Moreover, the more disaggregated studies of the Chinese Revolution that have emerged since Skocpol’s book make it clear to me that there were deep contingencies in the process as it unfolded, and that multiple outcomes were possible. So the antecedent structural conditions that she identifies did not suffice to bring about the eventual revolution.
Skocpol’s comparativist methodology was an exciting innovation when it appeared in 1979. With the hindsight of thirty-five years, however, I am inclined to think that it is a failed experiment. It remains too close to the methodology that asks the researcher to find a set of conditions that vary appropriately with the outcome, and in the end it is methodologically committed to the idea that we can discover an answer to the question, what conditions do all social revolutions share? The critique that McAdam, Tarrow, and Tilly offer of theories of contentious politics that simply look for large generalizations across groups of large scale contentious events seems to apply here as well. The focus in Skocpol’s analysis remains too macro, with social revolutions constituting the units of analysis. But as MTT argue, it is more useful to drop down a level or two and look to the mechanisms and processes that make up social revolutions, rather than trying to identify high-level generalizations across groups of cases, whether large-N or small-N.

Mechanisms and methodology

In its origin the causal mechanisms approach (link) is chiefly an answer to the question, “what is a good social explanation?”. So it turns out that much of the mechanisms discussion has taken place within the philosophy of science, especially the philosophy of social science and the philosophy of biology. The question I’d like to formulate here is whether mechanisms theory has any relevance to methodology as well? Can sociologists make better progress on concrete research problems by organizing some of their thinking around the construct of a social mechanism?

This kind of question comes up with respect to a number of the topics and innovations that have occurred in the philosophy of social science in recent years — critical realism, causal powers, and strategic fields, for example. It is certainly worthwhile developing theories and refinements of each of these concepts within the philosophy of social science. But it is an additional question to ask whether these concepts have a valuable role to play in discussions of research methodology and design as well.

So what is the problem of methodology, from the point of view of the working sociologist? The researcher has a number of preliminary tasks: What is the domain of social phenomena that are of interest? How can those phenomena be studied using available empirical tools? How can we theorize what is going on in this domain? How can we think about the nature of the entities, processes, causes, and meanings that make up this domain? And how can we probe the properties and dynamics of those sociological entities and processes?

Take a phenomenon like corruption. China is said to face a social and political problem deriving from widespread corrupt practices. How would we investigate the phenomenon of corruption in China (or India, the United States, or Finland)? Corruption is an umbrella concept that describes patterns of behavior across a wide range of domains: interactions between police and the public, practices through which business contracts are secured, enforcement of environmental and safety regulations, enforcement of trade regulations, practices through which individuals secure services from hospitals and licensing authorities, and there are indefinitely many other examples. Moreover, we can identify similar patterns of behavior in many countries, so there is an element of international comparison in play as well.

And yet not all instances of rule breaking are instances of corruption. So there is a preliminary task for the researcher, to engage in conceptual work and to define, for the purpose of the research enterprise, what kinds of behavior by agents and citizens will be counted as “corrupt”. Here we would like the researcher to work like a philosopher of language in some ways: “What do we mean by ‘X’ in ordinary or technical parlance?” In the current example, we would like the researcher to arrive at a working specification of corruption that is both reasonably practicable in application but also reasonably conformant to our prior assumptions about the category. (A definition of “corruption” that identifies corruption as “income-enhancing strategies by an economic actor” may be easy to apply but entirely inadequate as a specification of what we mean by corruption.) Robert Klitgaard does this kind of conceptual work in his 1988 and 1989 books, Controlling Corruption and Corrupt Cities: A Practical Guide to Cure and Prevention.

So let’s say we’ve offered a specification of corruption along these lines:

“[One species of] corruption involves situations in which individuals with decision-making power with respect to rules, fines, approvals, or contracts expects and receives covert payments from the consumer in exchange for the desired decision.”

This definition would capture many of the examples provided above: police officers giving speeding tickets, customs inspectors closing their eyes to valuable undeclared items, hospital staff making decisions about admissions and treatment of patients, safety inspectors approving a given location or activity — in exchange for a gift from the affected individual. Essentially the corrupt agent is “selling” a service or benefit which he or she controls to an individual who needs that service, contrary to the rules of the organization.

Now the researcher needs to specify a research question. It might be descriptive:

  • “How frequent are instances of corrupt behavior by this description in setting X?”

It might be comparative:

  • “How does institution X compare with institution Y with respect to the frequency of corrupt behavior by its agents?”

It might be explanatory:

  • “Why do some institutions have higher rates of corrupt behavior than others?”

Or it might be policy-oriented:

  • “What features of institutions can be introduced to reduce rates of corrupt behavior by the agents of the institution?”

The mechanisms theory is particularly relevant to methodology for at least the final three tasks. The background assumptions the researcher brings to his or her work about what a good explanation, a good policy design, or a good comparison ought to look like will strongly affect the ways in which he or she proceeds from this point further.

If the researcher adopts the simple empiricist model of explanation — find characteristics that appropriately co-vary with the dependent variable — then the research path is fairly clear:

Or he or she might pursue the necessary-and-sufficient-condition version of the approach:

  • Identify a set of cases (again with provisos about selection of cases) and see whether we can identify necessary and/or sufficient conditions using Mill’s methods or other analytical tools. (Gary Goertz describes strategies like these in Necessary Conditions: Theory, Methodology, and Applications.)

On the other hand, if the researcher adopts the causal-mechanisms approach — identify causal mechanisms and processes that affect the occurrence or frequency of the outcome of interest — then he or she will proceed differently. The researcher will examine the individual cases carefully, looking to identify the factors and mechanisms that appear to be involved in the outcomes of interest; he or she will then look to see whether there are common processes involved in multiple cases; and he or she will consider whether available theories of social processes are relevant to the explanation of the outcomes observed. (This is essentially the method pursued by McAdam, Tarrow, and Tilly in Dynamics of Contention.)

For example, the extensive theorizing and discussions of principal-agent problems in political science may shed light on concrete mechanisms through which corrupt behaviors are controlled in a variety of existing circumstances. The Principal wants the Agent to act according to the rules of the organization; the Agent is to some extent outside his observation and control. So what mechanisms of self-enforcement are available to lead the Agent to comply with the expectations of the Principal?

One mechanism of compliance that the Principal may consider is a Corrupt Practices Tipline, whereby consumers can anonymously report corruption by specific officers. This extends the Principal’s ability to gather information about the Agent’s behavior. The Agent, knowing that the Tipline exists, constrains his otherwise corrupt inclinations, and the incidence of corrupt practices declines.

Another possible approach for the Principal is to link the Agent’s longterm rewards to his/her longterm success in assigned tasks. Jean Ensminger describes the practice of gifts of “bridewealth” in these terms, as a way in which cattle owners maintain the loyalty of their herders during the long periods of time that they are out of sight in the foraging areas (Making a Market: The Institutional Transformation of an African Society) Deferred compensation and stock options may play a similar role in the modern business organization.

Another mechanism that might be considered is selective investigation and enforcement. The Principal may know that many customs agents are accepting small gifts of money when evaluating customs declarations, and that a small number of these transactions involve high-value items and correspondingly high-value gifts. It might be sensible to focus investigation and enforcement on this smaller incidence of high-value transactions. Choosing this strategy may have the effect of significantly reducing “big corrupt transactions” while leaving “small corrupt transactions” essential unchanged.

A final mechanism that might be considered here (out of many possible avenues of investigation) is a cultural factor — training, education, and inculturation. We might consider whether one cultural setting does a better job of preparing individuals to play honest roles in organizations than another based on the educational and formative experiences that are offered to them. This can provide the basis for a hypothesis about a causal mechanism leading to a high (or low) rate of corrupt behavior; and it might provide a basis for a possible policy intervention (workplace training to shift basic values).

This is one example of the way a concrete research strategy might evolve. The important point of the example is that the philosophical orientations described here — “simple empiricism”, “mechanisms theory” — lead researchers to structure their investigations in very different ways. The researcher who is attuned to causal mechanisms will focus his or her efforts on uncovering the concrete social pathways or processes through which a given pattern of behavior is either encouraged or discouraged; and the researcher will be led to consider comparative cases to see whether similar arrangements lead to similar patterns of behavior in the other cases. This suggests that the discussion of the ins and outs of causal mechanisms theory in philosophy of social science may in fact be an important contribution to social science methodology as well.

How to probe public attitudes?

We are almost always interested in knowing how the public thinks and feels about various issues — global warming, race relations, the fairness of rising income inequalities, and the acceptability of same-sex marriage, for example. The public is composed of millions of individuals, and the population can be segmented in a variety of relevant ways — gender, age, race, region, political affiliation, and many other cleavages. So we might want to know how teenagers think about alcohol, and how these attitudes have changed over time, or how attitudes towards the equality of women have evolved since 1960.

What research tools are available to us to investigate public opinion? And how reliable are these tools?

The most immediate answer to this question is survey research. We can formulate a set of survey questions, select a population of respondents, and tabulate the distribution of responses. And if we do this on several occasions over time, we can make some inferences about changes in attitudes over time. There are innumerable examples of these kinds of studies, from the GSS to the euro barometer to the Pugh organization’s frequent polling data. And we seem to learn some important things from studies like these concerning the distribution of attitudes across time and space. Spaniards are less concerned about fair trade produce than Swedes, young people have become more accepting of single-sex marriage, people over 65 are more sympathetic to Tea Party values than people in their thirties.

Another research approach takes a more qualitative approach. Researchers sometimes use open-ended interviews and focus groups to learn more directly how various groups and individuals think about certain topics. We may learn more from such studies than we can learn from a mass survey — for example, the interviewer may gain a better understanding of the reasoning that individuals use to reach their beliefs. A survey question may ask whether a consumer is willing to pay 10% more for fair trade bananas, whereas a series of interviews may determine that the “no’s” break into a group who don’t have the discretionary money and another group who oppose fair trade pricing on ideological grounds.

There are more indirect methods for studying public opinion as well. We might examine the comments that are submitted to newspapers on topics of interest and try to quantify over time the “temperature” of those comments — more intolerant, more angry, more reflective. Likewise, we might attempt to quantify the streams of social media — Twitter, Facebook, tumblr — with an eye towards testing the attitudes and emotions of various segments of the public. The vitriol that exploded on twitter following the selection of Miss New York as Miss America a few weeks ago says something about contemporary racism.

Attitudes towards race in America are especially interesting to me. How have Americans changed in the ways they think about race? Have Americans become less racially intolerant since the civil rights movement decade? Survey data seems to give a qualified “yes” to this question. Answers to survey questions that explicitly probe the individual’s level of racial antagonism seem to support the notion that on average, antagonism has declined. But scholars in race studies such as Tyrone Forman and Eduardo Bonilla-Silva argue that the survey results are misleading (link). They use a methodology of extended interviews, along with a rigorous way of interpreting the results, which suggests that there is a widening divergence between the responses American college students give to surveys probing their racial attitudes and the values and beliefs that are revealed through extensive open-ended interviews.

In consonance with this new structure, various analysts have pointed out that a new racial ideology has emerged that, in contrast to the Jim Crow racism or the ideology of the color line (Johnson, 1943, 1946; Myrdal, 1944), avoids direct racial discourse but effectively safeguards racial privilege (Bobo et al., 1997; Bonilla-Silva and Lewis, 1999; Essed, 1996; Jackman, 1994; Kovel, 1984). That ideology also shapes the very nature and style of contemporary racial dis-cussions. In fact, in the post civil rights era, overt discussions of racial issues have become so taboo that it has become extremely difficult to assess racial attitudes and behavior using conventional research strategies (Myers, 1993; Van Dijk, 1984, 1987, 1997). Although we agree with those who suggest that there has been a normative change in terms of what is appropriate racial discourse and even racial etiquette (Schuman et al., 1988), we disagree with their interpret-ation of its meaning. Whereas they suggest that there is a ‘mixture of progress and resistance, certainty and ambivalence, striking movement and mere surface change’ (p. 212), we believe (1) that there has been a rearticulation of the domi-nant racial themes (less overt expression of racial resentment about issues anchored in the Jim Crow era such as strict racial segregation in schools, neigh-borhoods, and social life in general, and more resentment on new issues such as affirmative action, government intervention, and welfare) and (2) that a new way of talking about racial issues in public venues – a new racetalk – has emerged. Nonetheless, the new racial ideology continues to help in the reproduction of White supremacy. (52)

They argue that a new “racetalk” has emerged that makes explicitly racist utterances socially unacceptable; but that the underlying attitudes have not changed as much. And this implies that survey research is likely to misrepresent the degree of change in attitudes that has occurred.

Here is a good example of the kind of analysis Forman and Bonilla-Silva provide for transcripts from the open-ended interviews:

The final case is Eric, a student at a large midwestern university , an example of the students who openly expressed serious reservations about interracial mar-riages (category 6). It is significant to point out that even the three students who stated that they would not enter into these relationships, claimed that there was nothing wrong with interracial relationships per se. Below is the exchange between Eric and our interviewer on this matter.

Eric: Uh . . . (sighs) I would say that I agree with that, I guess. I mean . . . I would say that I really don’t have much of a problem with it but when you, ya know, If I were to ask if I had a daughter or something like that, or even one of my sisters, um . . . were to going to get married to a minority or a Black, I . . . I would probably . . . it would probably bother me a little bit just because of what you said . . . Like the children and how it would . . . might do to our family as it is. Um . . . so I mean, just being honest, I guess that’s the way I feel about that. Int.: What would, specifically , if you can, is it . . . would it be the children? And, if it’s the children, what would be the problem with, um . . . uh . . . adjustment, or Eric: For the children, yeah, I think it would just be . . . I guess, through my experience when I was younger and growing up and just . . . ya know, those kids were different. Ya know, they were, as a kid, I guess you don’t think much about why kids are dif-ferent or anything, you just kind of see that they are different and treat them differ-ently . Ya know, because you’re not smart enough to think about it, I guess. And the, the other thing is . . . I don’t know how it might cause problems within our family if it happened within our family, ya know, just . . . from people’s different opinions on some-thing like that. I just don’t think it would be a healthy thing for my family. I really can’t talk about other people. Int.: But would you feel comfortable with it pretty much? Eric: Yeah. Yeah, that’s the way I think, especially , um . . . ya know, grandparents of things like that. Um, right or wrong, I think that’s what would happen. (Interview # 248: 10)

Eric used the apparent admission semantic move (“I would say that I agree with that”) in his reply but could not camouflage very well his true feelings (“If I were to ask if I had a daughter or something like that, or even one of my sisters, um . . . were [sic] to going to get married to a minority or a Black, I . . . I would probably . . . it would probably bother me a little bit”). Interestingly , Eric claimed in the interview that he had been romantically interested in an Asian-Indian woman his first year in college. However, that interest “never turned out to be a real big [deal]” (Interview # 248: 9). Despite Eric’s fleeting attraction to a person of color, his life was racially segregated: no minority friends and no meaningful interaction with any Black person.

This is an important argument within race studies. But it also serves as an important caution about uncritical reliance on survey research as an indicator of public attitudes and thinking.

Political polarization?

Is the American electorate “polarized” with regard to sets of political issues? McCarty, Rosenthal, and Poole accept the common view that we have in fact become more polarized in our politics over the past twenty years, and they offer an interesting theory of what is causing this polarization in Polarized America: The Dance of Ideology and Unequal Riches (Walras-Pareto Lectures). This theory was discussed in an earlier post. Delia Baldassarri and Peter Bearman take a different perspective, however, in a 2007 article, “Dynamics of Political Polarization” (AMERICAN SOCIOLOGICAL REVIEW, 2007, VOL. 72 (October:784–811)). Here is how Baldassarri and Bearman frame their research:

In this article we provide a parsimonious account for two puzzling empirical outcomes. The first is the simultaneous presence and absence of political polarization—the fact that attitudes rarely polarize, even though people believe polarization to be common. The second is the simultaneous presence and absence of social polarization—the fact that while individuals experience attitude homogeneity in their interpersonal networks, these networks retain attitude heterogeneity overall. We do this by investigating the joint effects of personal influence on attitudes and social relations. (784)

Baldassarri and Bearman quote a range of studies that find that the mass of the US population is not polarized in the bulk of its political attitudes, and that it has not increased in polarization in the past decade. “The evidence suggests that, aside from a small set of takeoff issues, ‘the policy preferences of different social groupings generally move in parallel with each other’” (784). They resolve part of the paradox by distinguishing between activist opinions and public opinion:

In the same vein, Fiorina and colleagues (2005) dispute “The Myth of a Polarized America” and suggest that the “culture war” commonly conjured up in the media is a fictive construction. According to their analysis, there is no popular polarization, but simply partisan polarization—“those who affiliate with a party are more likely to affiliate with the ‘correct’ party today than they were in earlier periods” (p. 25). It is the political elite and a small number of party activists that are polarized.

This all seems a little paradoxical, so it’s worth looking at the assumptions these two groups of researchers are making about “polarization”. 

To start, what is meant by polarization with respect to a given issue — say gay marriage? Essentially the concept is a characteristic of a population’s distribution across an attitudinal scale from strongly support to strongly oppose with respect to the issue in question. A population is homogeneous if the distribution of scores has a single peak and a small standard deviation, and is polarized if it has two (or more) peaks. Here is a diagram representing the results of their agent-based model of attitude diffusion. Each issue eventually shows a pronounced degree of polarization after several hundred iterations, with about half the population distributed around a positive attitude and the other half distributed around a negative attitude. Presumably we can define increase in polarization as a shift apart of the two peaks (kurtosis) and perhaps a decrease in the deviation around the peaks. 

Theoretically a population could be segmented into three distinct groups — perhaps one-third who cluster around the zero point of indifference and two extreme groups on the left and right. 

The most original part of their work here is an effort to model the emergence of issue polarization based on a theory of how social interactions in networks and small groups influence individuals’ attitudes. They offer a sociological theory of inter-personal influence to explain how attitude diffusion occurs within a population, and they report the results of network simulations to illustrate the consequences of this theory. They argue that this model explains how members of society can perceive polarity while actually embodying a high degree of homogeneity. 

In more general terms, we show that simple mechanisms of social interaction and personal influence can lead to both social segregation and ideological polarization. (785)

Our goal has been to deploy a model of inter-personal influence sensitive to dynamics of political discussion, where actors hold multiple opinions on diverse issues, interact with others relative to the intensity and orientation of their political preferences, and through evolving discussion networks shape their own and others’ political contexts. In the model, opinion change depends on two factors: the selection of interaction partners, which determines the aggregate structure of the discussion network, and the process of interpersonal influence, which determines the dynamics of opinion change. In the next section, we organize the description of the model around these two elements. Table 1 summarizes the simulation algorithm. (788)

The simulations are very interesting. The authors specify assumptions about the structure of interactions; they specify how an individual’s attitude is affected by the interaction; and they creat an initial distribution of attitudes for the 100 actors in the simulation. They then run the set of actors and interactions through 500 iterations and observe the resulting patterns of distribution of attitudes. 

The cases resolve into two large groups: non-takeoff, where polarization does not emerge and takeoff, where polarization does occur. The first group is much more common, validating the prior finding that public opinion is not becoming more polarized. The “takeoff” group is much less common but important. For some initial distributions of attitudes and interaction pathways the population does develop IMO two sharply divided sub-groups. These two diagrams illustrate these two possibilities. 


In the second figure the population is moving strongly towards polarization around the issue, whereas the first figure represents a population with no pattern of polarization.

Several things are striking about this work. First is the degree to which it presents a picture of public opinion that seems highly counterintuitive in 2012. The first half of their paradox seems even more compelling today than five years ago — the American public does seem to be very divided in its opinions about social and moral issues. The second striking thing is perhaps an omission in the foundations of their theory of attitude formation. Their model works through 1-1 interactions. But it seems evident that a lot of attitude formation is happening through exposure to the media — television, radio, Internet, social media. There doesn’t appear to be an obvious way to incorporate these powerful influences into their model. And yet these may be much more influential than 1-1 interactions. 

This research is of interest for two important reasons. First, it is a sustained effort to account for how issue separation occurs in real social groups. And second, it provides an excellent and detailed example of a microfoundational approach to an important social process, using a variety of agent-based modeling techniques to work out the consequences of the theory of social influence with which they begin. The models allow Baldassarri and Bearman to carefully probe the assumptions of the theory of individual-level attitude dynamics that they postulate. So the work is both substantively and methodologically rewarding. It is analytical sociology at its best.

Actor-based sociology


I’ve advocated many times here for the advantages of what I’ve referred to as “actor-centered” sociology. Let’s see here whether it is possible to say fairly specifically what that means. Here is an elliptical description of three aspects of what I mean by “actor-centered sociology”:

First, it reflects a view of social ontology: Social things are composed, constituted, and propertied by the activities and interactions of individual actors — perhaps 2, perhaps 300M. Second, it puts forward a constraint on theorizing: Our social theories need to be compatible with the ontology. The way I put the point is this: social theories, hypotheses, and assertions need microfoundations. Third, “actor-centered sociology” represents a heuristic about where to focus at least some of our research energy and attention: at the ordinary processes and relations through which social processes take place, the ordinary people who bring them about, and the ordinary processes through which the effects of action and interaction aggregate to higher levels of social organization.

(a) This means that sociological theory need to recognize and incorporate the idea that all social facts and structures supervene on the activities and interactions of socially constructed individual actors. It is meta-theoretically improper to bring forward hypotheses about social structures that cannot be appropriately related to the actions and interactions of individuals. Or in other words, it means that claims about social structures require microfoundations.

(b) The meta-theory of actor-centered sociology requires that all social theories, at whatever level, require a theory of the actor. Economics and ethnomethodology differ in the level of specificity they offer for their theories of the actor; but both have such a theory.  They both put forward fundamental ideas about how actors think and the mental processes that influence their actions.

(c) Actor-centered sociology suggests that careful study of local social mechanisms and behaviors is a worthwhile exercise for sociological research.  Ethnomethodology and the careful, place-based investigations offered by Goffman and Garfinkel move from the wings to the stage itself.

(d) It appears to imply that we may be able to provide an explanation of at least some higher-level social facts by showing how they emerge as a result of the workings of actors and their structured interactions. This is the aggregation-dynamics methodology (link).  Or in terms discussed elsewhere here, it is the micro-to-macro link of Coleman’s boat (link).

(e) The actor-based sociology approach seems to imply that the regularities that may exist at the level of macro-social phenomena are bound to be weak and exception-laden. Heterogeneity within and across actors — across history and across social settings — seems to imply multiple sets of attainable aggregate outcomes.  Would fascist organizations flourish in Italy after World War I? The answer is indeterminate.  There were numerous groups of social actors with important differences in their states of agency, and these groups in turn were influenced by organizations of varying characteristics. So it would be impossible to say in advance with confidence either that fascism was likely to emerge or that it was unlikely to emerge (link).

(f) The actor-centered approach suggests that we can do better sociology by being more attentive to subtle differences in agency in specific groups and times. George Steinmetz’s careful attention to the processes of formation through which colonial administrators took shape in nineteenth-century Germany illustrates the value of paying attention to the historical particulars of various groups of actors, and the historically specific circumstances in which their frames of agency were created (link). It implies that context and historical processes are crucial to sociological explanation.

(g) The actor-centered approach highlights the importance of careful analysis of the mechanisms of communication and interaction through which individuals influence each other and through which their actions aggregate to higher level social outcomes and structures.  Social networks, competitive markets, mass communications systems, and civic associations all represent important inter-actor linkages that have massively important consequences for aggregate social outcomes.

(h) Finally, the actor-centered approach has some of the advantages of the spotlight in a three-ring circus. The idea of actor-centered sociology points the spotlight to the parts of the arena where the action is happening: to the formation of the actor, to the concrete setting of the actor, to the interactions that occur among actors, to the aggregative processes that lead to larger outcomes, and to the causal properties that those larger structures come to have. 

One thing that is somewhat troubling for anyone who has been reading this blog over time is that there seems to be a glaring inconsistency in two lines of thought emphasized repeatedly here: first, that social facts require microfoundations; and second, that meso-structures can have autonomous causal properties. Are these two ideas consistent? 

In particular, one might interpret the imperative of actor-centered sociology as a particularly restrictive view of social causation: from configurations of actors to meso-level social facts.  So all the causal “action” is happening at the level of the actors, not the structures.  Dave Elder-Vass attempts to avoid this implication by arguing for emergent social causal properties (link); I’ve approached the problem by talking about relatively autonomous causal properties at the meso-level (link).  I continue to think the latter view works reasonably well.  In a post on “University as a causal structure,” for example, I think a plausible case is made for both ideas: the tenure system is causally effective in constraining individual faculty members’ behavior as well as being causally effective in influencing other structural features of the university; and every aspect of this system has microfoundations in the form of the structured circumstances of action and culturation through which the bureaucratic agents in the system behave. Or in other words: it is consistent to maintain both parts of the dilemma, actor-centered sociology and relatively autonomous meso-level social causation (link).

Scenario-based projections of social processes

As we have noted in previous posts, social outcomes are highly path-dependent and contingent (linklinklinklink). This implies that it is difficult to predict the consequences of even a single causal intervention within a complex social environment including numerous actors — say, a new land use policy, a new state tax on services, or a sweeping cap-and-trade policy on CO2 emissions. And yet policy changes are specifically designed and chosen in order to bring about certain kinds of outcomes. We care about the future; we adopt policies to improve this or that feature of the future; and yet we have a hard time providing a justified forecast of the consequences of the policy.

This difficulty doesn’t only affect policy choices; it also pertains to large interventions like the democracy uprisings in the Middle East and North Africa. There are too many imponderable factors — the behavior of the military, the reactions of other governments, the consequent strategies of internal political actors and parties (the Muslim Brotherhood in Egypt) — so activists and academic experts alike are forced to concede that they don’t really know what the consequences will be.

One part of this imponderability derives from the fact that social changes are conveyed through sets of individual and collective actors. The actors have a variety of motives and modes of reasoning, and the collective actors are forced to somehow aggregate the actions and wants of subordinate actors. And it isn’t possible to anticipate with confidence the choices that the actors will make in response to changing circumstances. At a very high level of abstraction, it is the task of game theory to model strategic decision-making over a sequence of choices (problems of strategic rationality); but the tools of game theory are too abstract to allow modeling of specific complex social interactions.

A second feature of unpredictability in extended social processes derives from the fact that the agents themselves are not fixed and constant throughout the process. The experience of democracy activism potentially changes the agent profoundly — so the expectations we would have had of his/her choices at the beginning may be very poorly grounded by the middle and end. Some possible changes may make a very large difference in outcomes — actors may become more committed, more open to violence, more ready to compromise, more understanding of the grievances of other groups, … This is sometimes described as endogeneity — the causal components themselves change their characteristics as a consequence of the process.

So the actors change through the social process; but the same is often true of the social organizations and institutions that are involved in the process. Take contentious politics — it may be that a round of protests begins around a couple of loose pre-existing organizations. As actors seek to achieve their political goals through collective action, they make use of the organizations for their communications and mobilization resources. But some actors may then also attempt to transform the organization itself — to make it more effective or to make it more accommodating to the political objectives of this particular group of activists. (Think of Lenin as a revolutionary organization innovator.) And through their struggles, they may elicit changes in the organizations of the “forces of order” — the police may create new tactics (kettling) and new sub-organizations (specialized intelligence units). So the process of change is likely enough to transform all the causal components as well — the agents and their motivations as well as the surrounding institutions of mobilization and control. Rather than a set of billiard balls and iron rods with fixed properties and predictable aggregate consequences, we find a fluid situation in which the causal properties of each of the components of the process are themselves changing.

One way of trying to handle the indeterminacy and causal complexity of these sorts of causal processes is to give up on the goal of arriving at specific “point” predictions about outcomes and instead concentrate on tracing out a large number of possible scenarios, beginning with the circumstances, actors, and structures on the ground. In some circumstances we may find that there is a very wide range of possible outcomes; but we may find that a large percentage of the feasible scenarios or pathways fall within a much narrower range. This kind of reasoning is familiar to economists and financial analysts in the form of Monte Carlo simulations. And it is possible that the approach can be used for modeling likely outcomes in more complex social processes as well — war and peace, ethnic conflict, climate change, or democracy movements.

Agent-based modeling is one component of approaches like these (link).  This means taking into account a wide range of social factors — agents, groups, organizations, institutions, states, popular movements, and then modeling the consequences of these initial assumptions. Robert Axelrod and colleagues have applied a variety of modeling techniques to these efforts (link).

Another interesting effort to carry out such an effort is underway at the RAND Pardee Center, summarized in a white paper called Shaping the Next One Hundred Years: New Methods for Quantitative, Long-Term Policy Analysis. Here is how the lead investigators describe the overall strategy of the effort:

This report describes and demonstrates a new, quantitative approach to long-term policy analysis (LTPA).  These robust decisionmaking methods aim to greatly enhance and support humans’ innate decisionmaking capabilities with powerful quantitative analytic tools similar to those that have demonstrated unparalleled effectiveness when applied to more circumscribed decision problems.  By reframing the question “What will the long-term future bring?” as “How can we choose actions today that will be consistent with our long-term interests?” robust decisionmaking can harness the heretofore unavailable capabilities of modern computers to grapple directly with the inherent difficulty of accurate long-term prediction that has bedeviled previous approaches to LTPA. (iii)

LTPA is an important example of a class of problems requiring decisionmaking under conditions of  deep uncertainty—that is, where analysts do not know, or the parties to a decision cannot agree on, (1) the appropriate conceptual models that describe the relationships among the key driving forces that will shape the long-term future, (2) the probability distributions used to represent uncertainty about key variables and parameters in the mathematical representations of these conceptual models, and/or (3) how to value the desirability of alternative outcomes. (iii)

And here, in a nutshell, is how the approach is supposed to work:

This study proposes four key elements of successful LTPA:

• Consider large ensembles (hundreds to millions) of scenarios.
• Seek robust, not optimal, strategies.
• Achieve robustness with adaptivity.
• Design analysis for interactive exploration of the multiplicity of plausible futures.

These elements are implemented through an iterative process in which the computer helps humans create a large ensemble of plausible scenarios, where each scenario represents one guess about how the world works (a future state of the world) and one choice of many alternative strategies that might be adopted to influence outcomes. Ideally, such ensembles will contain a sufficiently wide range of plausible futures that one will match whatever future, surprising or not, does occur—at least close enough for the purposes of crafting policies robust against it.  (xiii)

Thus, computer-guided exploration of scenario and decision spaces can provide a prosthesis for the imagination, helping humans, working individually or in groups, to discover adaptive near-term strategies that are robust over large ensembles of plausible futures. (xiv)

The hard work of this approach is to identify the characteristics of policy levers, exogenous uncertainties, measures, and relationship (XLRM).  Then the analysis turns to identifying a very large number of possible scenarios, depending on the initial conditions and the properties of the actors and organizations.  (This aspect of the analysis is analogous to multiple plays of a simulation game like SimCity.) Finally, the approach requires aggregating the large number of scenarios to allow the analysis to reach some conclusions about the distribution of futures entailed by the starting position and the characteristics of the actors and institutions.  And the method attempts to assign a measure of “regret” to outcomes, in order to assess the policy steps that might be taken today that lead to the least regrettable outcomes in the distant future.

It appears, then, that there are computational tools and methods that may prove useful for social explanation and social prediction — not of single outcomes, but of the range of outcomes that may be associated with a set of interventions, actors, and institutions.

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