Causal diagrams and causal mechanisms

There is a long history of the use of directed causal diagrams to represent hypotheses about causation. Can the mathematics and graphical systems created for statistical causal modeling be adapted to represent and evaluate hypotheses about causal mechanisms and outcomes?

In the causal modeling literature the structure of a causal hypothesis is something like this: variable T increases/ decreases the probability of the occurrence of outcome E. This is the causal relevance criterion described by Wesley Salmon in Scientific Explanation and the Causal Structure of the World. It is a fundamentally statistical understanding of causality.

Here is a classic causal path model by Blau and Duncan indicating the relationships among a number of causal factors in bringing about an outcome of interest — “respondent’s first job”.

 

This construction aims at joining a qualitative hypothesis about the causal relations among a set of factors with a quantitative measurements of the correlations and conditional probabilities that support these causal relations. The whole construction often takes its origin in a multivariate regression model.

Aage Sørensen describes the underlying methodological premise of quantitative causal research in these terms in his contribution to Frontiers of Sociology (Annals of the International Institute of Sociology Vol. 11):

Understanding the association between observed variables is what most of us believe research is about. However, we rarely worry about the functional form of the relationship. The main reason is that we rarely worry about how we get from our ideas about how change is brought about, or the mechanisms of social processes, to empirical observation. In other words, sociologists rarely model mechanisms explicitly. In the few cases where they do model mechanisms, they are labeled mathematical sociologists, not a very large or important specialty in sociology. (370)

My question here is whether this scheme of representation of causal relationships and the graphical schemes that have developed around it are useful for the analytics of causal mechanisms.

The background metaphysics assumed in the causal modeling literature is Humean and “causal-factor” based; such-and-so factor increases the probability of occurrence of an outcome or an intermediate variable, the simultaneous occurrence of A and B increase the probability of the outcome, etc. Quoting Peter Hedstrom on causal modeling:

In the words of Lazarsfeld (1955: 124-5), “If we have a relationship between x and y; and if for any antecedent test factor the partial relationships between x and y do not disappear, then the original relationship should be called a causal one.” (

Dissecting the Social: On the Principles of Analytical Sociology

)

The current iteration of causal modeling is a directed acyclic graph (DAG). Felix Elwert provides an accessible introduction to directed acyclic graphs in his contribution to Handbook of Causal Analysis for Social Research (link). Here is a short description provided by Elwert:

DAGs are visual representations of qualitative causal assumptions: They encode researchers’ expert knowledge and beliefs about how the world works. Simple rules then map these causal assumptions onto statements about probability distributions: They reveal the structure of associations and independencies that could be observed if the data were generated according to the causal assumptions encoded in the DAG. This translation between causal assumptions and observable associations underlies the two primary uses for DAGs. First, DAGs can be used to prove or disprove the identification of causal effects, that is, the possibility of computing causal effects from observable data. Since identification is always conditional on the validity of the assumed causal model, it is fortunate that the second main use of DAGs is to present those assumptions explicitly and reveal their testable implications, if any. (246)

A DAG can be interpreted as a non-parametric structural equation model, according to Elwert. (Non-parametric here means simply that we do not assume that the data are distributed normally.) Elwert credits the development of the logic of DAGs to Judea Pearl and Peter Spirtes, along with other researchers within the causal modeling community.
 
Johannes Textor and a team of researchers have implemented DAGitty, a platform for creating and using DAGs in appropriate fields, including especially epidemiology (link). A crucial feature of DAGitty is that it is not solely a graphical program for drawing graphs of possible causal relationships; rather, it embodies an underlying logic which generates expected statistical relationships among variables given the stipulated relationships on the graph. Here is a screenshot from the platform:
 

 

 
 
The question to consider here is whether there is a relationship between the methodology of causal mechanisms and the causal theory reflected in these causal diagrams. 
 
It is apparent that the underlying ontological assumptions associated with the two approaches are quite different. Causal mechanisms theory is generally associated with a realist approach to the social world, and generally rejects the Humean theory of causation. The causal diagram approach, by contrast, is premised on the Humean and statistical approach to causation.  A causal mechanisms hypothesis is not fundamentally evaluated in terms of the statistical relationships among a set of variables; whereas a standard causal model is wholly intertwined with the mathematics of conditional correlation.
 
Consider a few examples. Here is a complex graphical representation of a process understood in terms of causal mechanisms from McGinnes and Elandy, “Unintended Behavioural Consequences of Publishing Performance Data: Is More Always Better?” (link):

 

Plainly this model is impossible to evaluate statistically by attempting to measure each of the variables; instead, the researchers proceed by validating the individual mechanisms identified here as well as the direction of influence they have on other intermediate outcomes. The outcome of interest is “quality of learning” at the center of the graph; and the diagram attempts to represent the complex structure of causal influences that exist among several dozen mechanisms or causal factors.

Here is another example of a causal mechanisms path diagram, this time representing the causal system involved in drought and mental health by Vins, Bell, Saha, and Hess (link).

 
 
Here too the model is not offered as a statistical representation of covariance among variables; rather, it is a hypothetical sketch of the factors which play in mechanisms leading from drought to depression and anxiety in a population. And the assessment of the model should not take the form of a statistical evaluation (a non-parametric structural equation model), but rather a piecemeal verification of the validity of the specific mechanisms cited. (John Gerring argues that this is a major weakness in causal mechanisms theory, however, in “Causal Mechanisms? Yes, But …” (link).)
 
It seems, therefore, that the superficial similarity between a causal model graph (a DAG) and a causal mechanisms diagram is only skin-deep. Fundamentally the two approaches make very different assumptions about both ontology (what a causal relationship is) and epistemology (how we should empirically evaluate a causal claim). So it seems unlikely that it will be fruitful for causal-mechanisms theorists to attempt to adapt methods like DAGs to represent the causal claims they want to advance and evaluate.
 

Meanings and mechanisms

image: photographs of Martin Luther King, Jr. at the University of Michigan, 1962

There are two large categories of factors that are fundamental to understanding social processes — meanings and mechanisms. I’ve given a preponderance of attention to the importance of social causal mechanisms within historical and social explanation (link). We explain a social outcome when we identify the social mechanisms that brought it about.

 
It is crucial to bear in mind always, however, that there is a complementary dimension to social life and social process — the pervasive fact that people act within frames of meanings and interpretations that they bring to their social relationships and their social worlds. Human action is meaningful action, and we can’t make sense of action without attributing meanings, intentions, and frameworks of understanding and desire to the individuals who constitute a social encounter. 
 
This is not a new insight, of course; it was fundamental to the hermeneutic approach to social life, including the influential thinking of Wilhelm Dilthey (Introduction to the Human Sciences). But the classical hermeneutic approach tended to under-value the importance of causation and mechanisms in the social world; whereas it is clear today that both mechanisms and meanings are inseparably embedded within the social world.
 
It is in fact misleading to portray mechanisms and meanings as complementary “dimensions” of social change. Rather, we might say that mechanisms depend upon meanings, for the simple reason that mechanisms depend upon actions, and actions presuppose meanings. This is the thrust of my emphasis on “actor-centered” approaches to sociology (link). The actor-centered perspective takes seriously the meanings, values, cognitive and practical frameworks that individuals bring to their interactions in the social world, and it urges social scientists and historians to improve upon their current theories of the actor.

 
Institutions and organizations are often invoked as causal factors or mechanisms in the production of important social outcomes. But institutions always work by influencing the behavior of the individual actors whom they touch; so either explicitly or implicitly we need to have a theory of the actor’s mental frameworks if we are to understand the causal power of institutions to influence outcomes. 

If we want to know why there is grade inflation in universities, we need to refer to some of the institutional mechanisms that influence grading practices (causal influences!), but we also need to refer to the goals and meanings that participants bring to the interaction between students, professors, and appeals committees. Sometimes those mental frameworks are trivial and manifest — students want higher grades for reasons of career success as well as personal validation, faculty want to function in accordance with their responsibilities as neutral assessors of academic performance while at the same time demonstrating empathy for the needs of their students. These interlocking intentions and desires lead to a dynamic movement of average grades over time — sometimes higher, once in a while lower. But sometimes the underlying mental frameworks that drive important social outcomes are more obscure — for example, the disaffection and doubt that leads inner city minority students to despise high school. 

Think for a moment about how meanings and intentional actions give rise to a common social mechanism, hate-based nationalist mobilization. A few strident leaders formulate a message of hate against a group — currently, MENA immigrants in various European countries; they find means of gaining access to national media (through provocative demonstrations); and they extend their influence from the tiny percentage of racist extremists ex ante to a sizable percentage of the more moderate population. How does this work? Why do ordinary non-racist citizens fall prey to the hateful messages of the extreme right? Presumably a convincing answer will depend on the specifics of the communications strategies and messages conveyed by the nationalist party, interlocking with an astute reading of the fears and suppressed prejudices of the majority population. In other words, the mechanism of racist mobilization depends on a substratum of political emotion and belief that can be adroitly manipulated by the racist group and its leaders.

Philosophers sometimes distinguish meanings and causes as subjective and objective.(This is implied in Georg Henrik von Wright’s classic book Explanation and Understanding.) But this is not a useful way of thinking about the two categories. Meanings are often fully objective — in the sense that we can investigate them empirically and they can be demonstrated to have stable and enduring effects in the world. And social causes have an element of subjectivity built into them, for the simple reason that social causes always invoke the subjective states of mind of the actors who make them up. It isn’t even accurate to say that meanings exist solely within the actor, whereas causes exist outside the actor. The meanings that Weber identified in the notion of the Protestant Ethic are indeed embodied in a population of individuals (inward); but they are pervasive and influential on those same individuals (outward). So the Protestant Ethic is both an inner state of mind and an external and coercive set of values and beliefs.

(The photos of Dr. King above are relevant in this context because the civil rights struggle of the 1950s and 1960s offers ample examples of meanings and mechanisms in the evolving mobilizations, legislation, cycles of Jim Crow violence, and emerging ideas about Black Power within the African-American community.)

Microfoundations and mechanisms

The topics of microfoundations and causal mechanisms have come up frequently in this work. The microfoundations thesis maintains that social attributions and explanations based on macro-level entities and structures depend upon pathways at the level of the individual actors through which the entities and processes are maintained. The causal mechanisms thesis maintains that the best way of understanding causal assertions linking A to B is to identify the concrete causal mechanisms through which the powers of A bring about the properties of B.

Is there a relation between these two bodies of philosophical theory about the social world? There is, in a fairly obvious way. When we ask for the microfoundations of a hypothesized social process, we are really asking about the lower-level social mechanisms that bring the process about.

For example: What is it about an extended population that creates the observed features of the spread of rumor or panic? Or in other words, what are the social mechanisms through which socially interacting actors spread rumors or contribute to a broader occurrence of panic and fear? When we provide an account of the ways in which individuals communicate with each other and then demonstrate how messages diffuse through the given network structure, we have identified one of the social mechanisms of the social process in question.

Asking for the microfoundations of X is asking for an answer to two related questions: What is X (at the micro level)? And how does X work (also at the micro level)? The latter question can be paraphrased as: what are the sub-level mechanisms through which the X-level processes work? The first question is not so clearly a question about mechanisms; it is rather a question about composition. What is it about the substrate that gives rise to (constitutes) the observed macro-level properties of X? But in their book In Search of Mechanisms: Discoveries across the Life Sciences Craver and Darden argue that mechanisms play both roles. Mechanisms can be invoked to account for both process and structure (link). Here is their diagram illustrating the role that mechanisms can play with respect to higher-level structures and processes:

So here is a preliminary answer to the question of whether microfoundations and mechanisms are related. In the most immediate sense, we might say that the search for microfoundations is a search for a group of lower-level social mechanisms, to account for both the constitution and the causal dynamics of the higher-level structure. Searching for microfoundations involves learning more about the substrate of a given level of structure and process, and the causal mechanisms that occur at that lower level. Microfoundations is the question and mechanisms is the answer.

This response is not fully satisfactory, however, for several reasons.

First, there is an implication in this analysis that mechanisms live at the substrate level — in the case of the social world, at the level of individual social actors. This is clearly assumed in the analytical sociology literature (Hedstrom, Dissecting the Social: On the Principles of Analytical Sociology). But this is an unnecessary and narrow stipulation about causal mechanisms. It is plausible to maintain that there are causal mechanisms at a range of levels (link); for example, at the cognitive level, the motivational level, the organizational level, or the system level (link).

Second, we might also observe that various social mechanisms themselves possess microfoundations. There are processes in the causal substrate that constitute the causal necessity of a specified mechanism. A spark in the presence of methane and oxygen brings about an explosion. This is a mechanism of combustion. The substrate is the chemical composition of methane and oxygen and the chemical processes that occur when an electrical spark is introduced into the environment. So the question of “level” is a relative one. A given set of objects and causal processes has its own substrate at a lower level, and simultaneously may serve as the substrate for objects and processes at higher levels.

We might also consider the idea that the two concepts have a different grammar. They play different roles in the language of science. The microfoundations conceptual scheme immediately invokes the idea of level and substrate. It brings along with it an ontological principle (the higher level is constituted by the properties of the substrate), and a partial methodological principle (the generative strategy of showing how higher-level processes come about as a consequence of the workings of the substrate). The mechanisms conceptual scheme does not inherently presuppose higher-level and lower-level structures; instead, a mechanism is something like a unit of causation, and it may be found at any level from molecular biology to organizational change.

(In an earlier post I considered a similar question, the relation between powers and mechanisms. There I argued that these two concepts are symmetrical: mechanisms lead us to powers, and powers lead us to mechanisms.)

Large causes and component causal mechanisms

Image: Yellow River, Qing Dynasty
Image: Free and Slave States, United States 1850

One approach to causal explanation involves seeking out the mechanisms and processes that lead to particular outcomes. McAdam, Tarrow, and Tilly illustrate this approach in their treatment of contentious politics in Dynamics of Contention, and the field of contentious politics is in fact highly suitable to the mechanisms approach. There are numerous clear examples of social processes instantiated in groups and organizations that play into a wide range of episodes of contention and resistance — the mechanics of mobilization, the processes that lead to escalation, the communications mechanisms through which information and calls for action are broadcast, the workings of organizations. So when we are interested in discovering explanations of the emergence and course of various episodes of contention and resistance, it is both plausible and helpful to seek out the specific mechanisms of mobilization and resistance that can be discerned in the historical record.

This is a fairly “micro” approach to explanation and analysis. It seeks to understand how a given process works by looking for the causal mechanisms that underlie it. But not all explanatory questions in the social sciences fall at this level of aggregation. Some researchers are less interested in the micro-pathways of particular episodes and more interested in the abiding social forces and arrangements that influence the direction of change in social systems. For example, Marx declared an explanatory hypothesis along these lines in the Communist Manifesto: “The history of all hitherto existing society is the history of class struggles.” And Michael Mann provides more detailed analysis of world history that encompasses Marx’s hypothesis along with several other large structural factors in The Sources of Social Power (link).

Large social factors at this level include things like the inequalities of power and opportunity created by various property systems; the logic of a competitive corporate capitalist economy; the large social consequences of climate change — whether in the Little Ice Age or the current day; the strategic and military interests of various nations; and the social and economic consequences of ubiquitous mobile computation and communication abilities. Researchers as diverse as Karl Marx, Manuel Castells, Carl von Clausewitz, and William McNeill have sought out causal hypotheses that attempt to explain largescale historical change as the consequence, in part, of the particular configurations and variations of macro factors like these. Outcomes like success in war, the ascendancy of one nation or region over others, the configuration of power and advantage across social groups within modern democracies, and the economic rise of one region over another are all largescale outcomes that researchers have sought to explain as the consequence of other largescale social, economic, and political factors.

These approaches are not logically incompatible. If we follow along with William McNeill (Plagues and Peoples – Central Role Infectious Disease Plays in World History) and consider the idea that the modern distribution of national power across the globe is a consequence of the vulnerability of various regions to disease, we are fully engaged in the idea that macro factors have macro consequences. But it is also open to us to ask the question, how do these macro factors work at the more granular level? What are the local mechanisms that underlay the dynamics of disease in Southeast Asia, West Africa, or South America? So we can always shift focus upwards and downwards, and we can always look for more granular explanations for any form of social causal influence. And in fact, some historical sociologists succeed in combining both approaches; for example, Michael Mann in his study of fascism (Fascists), who gives attention both to largescale regional factors (the effects of demobilization following World War I) and local, individual-level factors (the class and occupational identities of fascist recruits) (link).

That said, the pragmatics of the two approaches are quite different. And the logic of causal research
appears to differ as well. The causal mechanisms theory of explanation suggests close comparative study of individual cases — particular rebellions, particular episodes of population change, particular moments of change of government. The “large social factor” approach to explanation suggests a different level of research, a research method that permits comparison of large outcomes and the co-variance of putative causal factors. Mill’s methods of causal reasoning appear to be more relevant to this type of causal hypothesis. Theda Skocpol’s study of social revolution in States and Social Revolutions is a case in point (link).

The harder question is this: are the large social factors mentioned here legitimate “causes”, or are they simply placeholders for more granular study of particular mechanisms and pathways? Should reference to “capitalism,” “world trading system,” or “modern European reproductive regime” be expected to disappear in the ideal historical sociology of the future? Or is this “large structure” vocabulary an altogether justified and stable level of social analysis on the basis of which to construct historical and social explanations? I am inclined to believe that the latter position is correct, and that it is legitimate to conceive of social research at a range of levels of aggregation (link, link). The impulse towards disaggregation is a scientifically respectable one, but it should not be understood as replacing analysis at a higher level.

(The illustrations above were chosen to provide examples of historical processes (the silting of waterways and patterns of slaveholding) that admit of explanation in terms of largescale historical factors (climate, geography, and political systems).)

Social mechanisms and ABM methods

One particularly appealing aspect of agent-based models is the role they can play in demonstrating the inner workings of a major class of social mechanisms, the group we might refer to as mechanisms of aggregation. An ABM is designed to work out how a field of actors of a certain description, in specified kinds of interaction, lead through time to a certain kind of aggregate effect. This class of mechanisms corresponds to the upward strut of Coleman’s boat. This is certainly a causal story; it is a generative answer to the question, how does it work?

However, anyone who thinks carefully about causation will realize that there are causal sequences that occur only once. Consider this scenario: X occurs, conditions Ci take place in a chronological sequence, and Y is the result. So X caused Y through the causal steps instigated by Ci. We wouldn’t want to say the complex of interactions and causal links associated with the progress of the system through Ci as a mechanism linking X to Y; rather, this ensemble is the particular (in this case unique) causal pathway from X to Y. But when we think about mechanisms, we generally have in mind the idea of “recurring causal linkages”, not simply a true story about how X caused Y in these particular circumstances. In other words, for a causal story to represent a mechanism, it needs to be a story that can be found to hold in an indefinite number of cases. Mechanisms are recurring complexes of causal sequences.

An agent-based model serves to demonstrate how a set of actors give rise to a certain aggregate outcome. This is plainly a species of causal argument. But it is possible to apply ABM methods to circumstances that are unique and singular. This kind of ABM model lacks an important feature generally included in the definition of a mechanism– the idea of recurrence across a number of cases. So we might single out for special attention those ABMs that identify and analyze processes that recur across multiple social settings. Here we might refer, for example, to the “Schelling mechanism” of residential segregation. There are certainly other unrelated mechanisms associated with urban segregation — mortgage lending practices or real estate steering practices, for example. But the Schelling mechanism is one contributing factor in a range of empirical and historical cases. And it is a factor that works through the local preferences of individual actors.

So this seems to answer one important question: in what ways can ABM simulations be said to describe social mechanisms? They do so when (i) they describe an aggregative process through which a given meso-level outcome arises, and (ii) the sequence they describe can be said to recur in multiple instances of social process.

A question that naturally arises here is whether there are social mechanisms that fall outside this group. Are there social mechanisms that could not be represented by an ABM model? Or would we want to say that mechanisms are necessarily aggregative, so all mechanisms should be amenable to representation by an ABM?

This is a complicated question. One possible response seems easily refuted: there are mechanisms that work from meso level (organizations) to macro level (rise of fascism) that do not invoke the features of individual actors. Therefore there are mechanisms that do not conform strictly to the requirements of methodological individualism. However, there is nothing in the ABM methodology that requires that the actors should be biological individuals. Certainly it is possible to design an ABM representing the results of competition among firms with different behavioral characteristics. This example still involves an aggregative construction, a generation of the macro behavior on the basis of careful specification of the behavioral characteristics of the units.

Another possible candidate for mechanisms not amenable to ABM analysis might include the use of network analysis to incorporate knowledge-diffusion characteristics into analysis of civil unrest and other kinds of social change. It is sometimes argued that there are structural features of networks that are independent of actor characteristics and choices. But given that ABM theorists often incorporate aspects of network theory into their formal representations of a social process, it is hard to maintain that facts about networks cannot be incorporated into ABM methods.

Another candidate is what Chuck Tilly and pragmatist sociologists (Gross, Abbott, Joas) refer to as the “relational characteristics” of a social situation. Abbott puts the point this way: often a social outcome isn’t the result of an ensemble of individuals making discrete choices, but rather is a dance of interaction in which each individual’s moves both inform and self-inform later stages of the interaction. This line of thought seems effective as a rebuttal to methodological individualism, or perhaps even analytical sociology, but I don’t think it demonstrates a limitation of the applicability of ABM modeling. ABM methods are agnostic about the nature of the actors and their interactions. So it is fully possible for an ABM theorist to attempt to produce a representation of the iterative process just described; or to begin the analysis with an abstraction of the resultant behavioral characteristics found in the group.

I’ve argued here that it is legitimate to postulate meso-to-meso causal mechanisms. Meso-level things can have causal powers that allow them to play a role in causal stories about social outcomes. I continue to believe that is so. But considerations brought forward here make me think that even in cases where a theorist singles out a meso-meso causal mechanism, he or she is still offering some variety of disaggregative analysis of the item to be explained. It seems that providing a mechanism is always a process of delving below the level of the explananda to uncover the underlying processes and causal powers that bring it about.

So the considerations raised here seem to lead to a strong conclusion — that all social mechanisms can be represented within the framework of an ABM (stipulating that ABM methods are agnostic about the kinds of agents they postulate). Agent-based models are to social processes as molecular biology is to the workings of the cell.

In fact, we might say that ABM methods simply provide a syntax for constructing social explanations: to explain a phenomenon, identify some of the constituents of the phenomenon, arrive at specifications of the properties of those constituents, and demonstrate how the behavior of the constituents aggregates to the phenomenon in question.

(It needs to be recognized that identifying agent-based social mechanisms isn’t the sole use of ABM models, of course. Other uses include prediction of the future behavior of a complex system, “what if” experimentation, and data-informed explanations of complex social outcomes. But these methods certainly constitute a particularly clear and rigorous way of specifying the mechanism that underlies some kinds of social processes.)

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.

Mechanisms thinking in international relations theory

source: Alex Cooley, “America and Empire” (link)

One of the most fundamental ideas underlying the philosophy of social science expressed here and elsewhere is the view that social explanations should seek out the causal mechanisms that underly the social phenomena of interest. So now we need to be able to say a lot more about what social mechanisms are, and how they relate to each other. Quite a bit of my own thinking has been devoted to this subject, and in a recent post I proposed that it would be useful to begin to compile an inventory of social mechanisms currently in use in the social sciences (link). There I suggested that it would be useful to find a motivated way of classifying the mechanisms that we discover.

Interest in mechanisms is taking hold in some sub-disciplines of political science. An especially clear statement of the appeal of the mechanisms theory of explanation for political science is offered by Andrew Bennett in “The Mother of All Isms: Causal Mechanisms and Structured Pluralism in International Relations Theory” (link). (Bennett is also co-author with Alexander George of the excellent book on case-study methodology, Case Studies and Theory Development in the Social Sciences.) In the current article Bennett reviews the progression that has occurred in IR theory from positivism and the covering law model, to the idea of high-level “paradigms” of explanation, to the idea of a diverse set of causal mechanisms as the foundation of explanation in the field. He calls the latter position “analytic eclecticism”, and he argues that it is a powerful and flexible way of thinking about the processes and research questions that make up the subject matter of IR theory.

In order to advance the value of mechanisms theory for working political scientists, Bennett argues that it will be helpful to attempt to classify the large number of mechanisms currently in use in IR theory in terms of a small number of dimensions. He proposes two dimensions in terms of which to analyze social mechanisms, which can be summarized as content and structure. The content dimension asks the question, what substantive social entities or properties are invoked by the mechanism? And the structure dimension asks the question, what is the nature of the relationship invoked by the mechanism? He proposes three large types of content: material power, functional efficiency, and legitimacy. And he suggests that there are four basic structures that can be formed: agent to agent, structure to agent, agent to structure, and structure to structure. (Notice that this corresponds exactly to the four arrows in Coleman’s boat, including the Type 4 “structure to structure” connection.) Here is how Bennett motivates this classification scheme:

This tripartite division of categories of mechanisms usefully mirrors the three leading ‘isms’ in the IR subfield: (neo)realism (with a focus on material power); (neo)liberalism (institutional efficiency); and constructivism (legitimacy). It thereby provides a bridge to the vast literature couched in terms of the isms, preserving this literature’s genuine contributions toward better theories on mechanisms of power, institutions, and social roles. (472)

Here is the resulting classification of social mechanisms that Bennett offers:

Others have found this approach to be promising. Here is an elaboration on Bennett’s classification by Mikko Huotari at the Mercator Institute for China Studies in Berlin:

(Thanks for sharing this classification, Mikko.)

I agree with Andrew in thinking that it is useful to find a non-arbitrary way of classifying mechanisms. It is quite worthwhile to make a start at this project. I’m not yet fully persuaded, however, by either of the axes that he proposes.

First, the content axis seems arbitrary — legitimacy, material power, functional efficiency. Why choose these substantive characteristics rather than a dozen other possible content features? Is it simply that these correspond to the three primary “isms” of IR theory — neorealism, neoliberalism, and constructivism (as he suggests earlier; 472)? But the thrust of the first part of the paper is that the “isms” are an unsatisfactory basis for guiding explanation in international relations theory; so why should we imagine that they serve to identify the crucial distinctions in content among social mechanisms? Would the content categories look different if we were taking our examples from feminist sociology, the sociology of organizations, or theories of legislatures? Bennett doesn’t assert that these content categories are exhaustive; but if they are not, then somehow the tabulation needs to indicate that there is an extensible list on the left. And are these categories exclusive? Can a given mechanism fall both into the legitimacy group and the functional efficiency group? It would appear that this is possible; but in that case classification is difficult to carry out.

Second, the structure axis. Why is it crucial to differentiate mechanisms according to their place within an agent-structure grid? Why is this an illuminating or fundamental feature of the mechanisms that are enumerated? Would this dimension explode if we thought of social organization as a continuum from macro to meso to micro (along the lines of Jepperson and Meyer (link), as well as several earlier posts here (link))?

An early question that needs answer here is this: What do we want from a scheme of classification of social mechanisms? Should we be looking for a strict classification with exhaustive and mutually exclusive groupings? Or should we be looking for something looser — perhaps more like a cluster diagram in which some mechanisms are closer to each other than they are to others?

 

We do have several other examples to think about when it comes to classifying mechanisms. In an earlier post I discussed Craver and Darden’s account of mechanisms in biology, and highlighted the table of mechanisms that they provide (link). It is evident that the Craver-Darden table is much less ambitious when it comes to classification. They have loosely grouped mechanisms into higher-level types — adaptation, repair, synthesis, for example; but they have not tried to further classify mechanisms in terms of the levels of the entities that are linked by the mechanism. So they offer one dimension of classification rather than two, and they leave it entirely open that there may be additional types to be added in the future. This is a fairly unexacting understanding of what is needed for a tabulation of mechanisms.

In Dynamics of Contention McAdam, Tarrow and Tilly offer a sort of classification of their own for the kinds of mechanisms they identify. They propose three types of mechanisms — environmental, cognitive, and relational (kl 375):

  • Environmental mechanisms mean externally generated influences on conditions affecting social life. Such mechanisms can operate directly: For example, resource depletion or enhancement affects people’s capacity to engage in contentious politics (McCarthy and Zald, ed. 1987).
  • Cognitive mechanisms operate through alterations of individual and collective perception; words like recognize, understand, reinterpret, and classify characterize such mechanisms. Our vignettes from Paris and Greenwood show people shifting in awareness of what could happen through collective action; when we look more closely, we will observe multiple cognitive mechanisms at work, individual by individual. For example, commitment is a widely recurrent individual mechanism in which persons who individually would prefer not to take the risks of collective action find themselves unable to withdraw without hurting others whose solidarity they value – sometimes at the cost of suffering serious loss.
  • Relational mechanisms alter connections among people, groups, and interpersonal networks. Brokerage, a mechanism that recurs throughout Parts II and III of the book, we define as the linking of two or more previously unconnected social sites by a unit that mediates their relations with one another and/or with yet other sites. Most analysts see brokerage as a mechanism relating groups and individuals to one another in stable sites, but it can also become a relational mechanism for mobilization during periods of contentious politics, as new groups are thrown together by increased interaction and uncertainty, thus discovering their common interests.
This too is a one-dimensional classification. And it appears to be intended to be exhaustive and mutually exclusive. But it isn’t clear to me that it succeeds in classifying all the mechanisms we might want to bring forward. Once again, this strikes me as a good beginning but not an exhaustive grouping of all social mechanisms.

My own preliminary grouping of mechanisms has even less structure (link). It groups mechanisms according to the subject matter or discipline from which they have emerged. But this does not serve to shed light on how these examples are similar or different from each other — one of the key purposes of a classification.

I think this is a very useful research activity, and Andrew Bennett has done a service to the theory of social mechanisms in putting forward this effort at classification. Let’s see what other schemes may be possible as well. A good scheme of classification may tell us something very important about the nature of how causation works in the social world.

A catalogue of social mechanisms

In an earlier post I made an effort at providing the beginnings of an inventory of social mechanisms from several areas of social research. Here I’d like to go a little further with that idea in order to see how it plays into good thinking about social-science methodology.

Some Types of Social Mechanisms
CONTENTION
Escalation
Brokerage
Diffusion
Coordinated action
Social appropriation
Boundary activation
Certification
Framing
Competition for power
COLLECTIVE ACTION
Prisoners’ dilemma
Free rider behavior
Convention
Norms
Selective benefits
Selective coercion
Conditional altruism
Reciprocity
ORGANIZATIONAL ENFORCEMENT
Audit and accounting
Supervision
Employee training
Morale building
Leadership
NORMS AND VALUES
Altruistic enforcement
Person-to-person transmission
Imitation
Subliminal transmission
Erosion
Charisma
Stereotype threat
ECONOMIC ACTIVITY
Market
Auction
Ministry direction
Contract
Market for lemons
Democratic decision making
Producers’ control
Soft budget constraint
GOVERNMENT
Agenda setting
Cyclical voting
Log rolling
Regulatory organizations
Influence peddling
STATE REPRESSION
Secret police files
Informers
Spectacular use of force
Propaganda
Deception
Control of communications systems

 

SOCIAL COMMUNICATIONS
Interpersonal network
Broadcast
Rumor
Transport networks

SYSTEM EFFECTS
Flash trading
Interlocking mobilization
Overlapping systems of authority (Brenner)
Non-linear networks

These mechanisms have been collected from a wide range of social scientists and researchers — Charles Tilly, Robert Axelrod, Elinor Ostrom, George Akerlof, Robert Bates, Mancur Olson, Mayer Zald, John Ferejohn, Janos Kornai, Claude Steele, and Charles Perrow, to name a few.

There are at least two kinds of questions we need to ask about a collection like this.

First, where do the entries come from? What kinds of scientific inquiry are required in order to establish that things like these are indeed mechanisms found in the social world?

The most general answer to this question concerning discovery is that much research in the various disciplines of the social sciences is specifically directed at working out the contours of mechanisms like these. Political scientists who focus on legislatures and the US Congress have become expert on identifying and validating the institutional and voting mechanisms through which legislative outcomes come to effect. Organizational sociologists study the inner workings of a range of organizations and are able to identify and validate a wide range of mechanisms at work within these organizations. Economic anthropologists and theorists study the ways in which economic transactions are conducted in a range of human settings. Social psychologists identify many of the ways that individuals acquire normative beliefs and transmit them to other individuals. The greatest difficulty in constructing a table like this is not at the level of identifying mechanisms that might be included; it is the problem of limiting the number of mechanisms identified to a more or less manageable number. There is some reason to fear that social scientists have identified thousands of mechanisms in their research, not dozens.

And second, what role does a table like this play in the conduct of research in the social sciences?

Craver and Darden argue that biologists often approach novel phenomena with something like this table in the backs of their heads — an inventory of known causal mechanisms in the domain of biology. From there they attempt to solve the puzzle: what combination of known mechanisms might be concatenated in order to reproduce the observed phenomenon?

Strikingly enough, this description of a heuristic for arriving at an explanatory analysis of a situation has a lot in common with the way that McAdam, Tarrow, and Tilly proceed in Dynamics of Contention. (Here is a more developed analysis of their mechanisms-based approach; link.) MT&T argue that there is a relatively manageable list of social mechanisms that can be observed in many cases of social contention. And they approach new instances with the idea that we may be able to understand the dynamics of the case by teasing out the workings of some of those mechanisms. It seems that MT&T are involved in both parts of the inquiry — discovery and isolation of recurring mechanisms of contention, and application of these discoveries to the explanation of specific episodes of contention.

For example, they introduce their case studies in Part III of the book in these terms:

Part III of the study takes up three distinct literatures regarding contention — revolution, nationalism, and democratization — in view of the paths our quest has followed. The goal of that concluding section is to emphasize the commonalities as well as the differences in those forms of contention through an examination of the explanatory mechanisms and political processes we have uncovered in Parts I and II. (kl 511)

And a few paragraphs later:

Let us insist: Our aim is not to construct general models of revolution, democratization, or social movements, much less of all political contention whenever and wherever it occurs. On the contrary, we aim to identify crucial causal mechanisms that recur in a wide variety of contention, but produce different aggregate outcomes depending on the initial conditions, combinations, and sequences in which they occur. (kl 519)

Here is how they summarize their attempt to explain particular episodes of social contention. They focus on a “number of loosely connected mechanisms and processes”:

  • A mobilization process triggered by environmental changes and that consists of a combination of attribution of opportunities and threats, social appropriation, construction of frames, situations, identities, and innovative collective action.
  • A family of mechanisms still to be elucidated around the processes of actor and identity constitution and the actions that constitute them.
  • A set of mechanisms often found in trajectories of contention that recurs in protracted episodes of contention, competition, diffusion, repression, and radicalization. (kl 941)

And this body of social mechanisms is taken to provide a basis for historically grounded explanations of the forms of contention observed in specific cases.

This seems to parallel fairly closely the intellectual process that Craver and Darden describe in the case of biology: create an inventory of common causal mechanisms and analyze new cases by trying to see to what extent some of those known mechanisms can be discerned in the new material.

This account of an important type of social science research resonates well with a broad range of social science disciplines. It aligns with Robert Merton’s notion of “theories of the middle range” in the social sciences, and the idea of developing a toolbox of patterns of social behavior on the basis of which to explain specific episodes. Rather than looking for general theories on the basis of which to unify wide swaths of the social world under a deductive explanatory system, this mechanisms-based approach suggests coming at social explanation piecemeal: finding the components and sub-processes of observed social ensembles, on the basis of which we can explain some aspects of the behavior of those ensembles.

We might usefully consider two additional questions. First, is there a theoretically useful way of classifying social mechanisms (formation of the individual actor, collective action, communication, repression, collective decision making, …)? Can our catalogue provide content-relevant “chapters”? We might argue that a good taxonomy of social mechanisms actually provides a way of theorizing the main dimensions of social activity and organization. And second, are there more fundamental things we can say about how some or many of these mechanisms work? Does a good theory of the actor and a good theory of social organizations suffice to account for the workings of a great many of these mechanisms? If we respond affirmatively to this question, then once again we may have made a small degree of progress towards offering a somewhat more general theory of the social world.

Craver on mechanisms methodology

Carl Craver and Lindley Darden provide in In Search of Mechanisms: Discoveries across the Life Sciences an extensive treatment of what a mechanisms-based methodology looks like. Their work originates in study of the biological sciences, but I find that much of what they have to say is very helpful in the philosophy of social science as well.

Craver and Darden argue that the biological sciences have largely adopted a mechanisms-centered view of the nature of their science. So what is a mechanism, on their view?

Mechanisms are how things work, and in learning how things work we learn ways to do work with them. Biologists try to discover mechanisms because mechanisms are important for prediction, explanation, and control…. Mechanisms are entities and activities organized such that they are productive of regular changes from start or set-up to finish or termination conditions. (kl 581)

Fundamentally Craver and Darden  argue that a search for mechanisms is frequently a guided and constrained process, involving an attempt to match the observed activities of the system with a concatenation of known mechanism components. They want to provide a more granular account of the process of research and discovery in science, and they take issue with the idea of a flash of inspiration as the source of scientific insight. Instead, they see the process of a great deal of scientific research as one in which a methodical effort at puzzle-solving takes place, trying out different combinations of known mechanisms to see whether they may serve to explain the phenomenon in question.

In short, one often begins the search for mechanisms with a ready-made layout of the space of possible mechanisms, and the goal is to use empirical findings to eliminate regions of that space. The nature of the phenomenon and the store of accepted mechanism types thus work together to frame the discovery problem: to reveal the layout of the space of possible mechanisms and perhaps to tell one how to decide among them. (kl 1595)

They don’t mean to say that there is no place for novelty or originality in scientific research; but they argue for a kind of cumulative process for much of the scientific work of discovery that builds upon the prior discovery of mechanisms and components of mechanisms.

Although occasionally biology calls upon a Darwin or a Harvey to introduce an altogether novel kind of mechanism, most episodes of mechanism discovery play out within the space of known mechanism types within a scientific field. (kl 1604)

There are many interesting and useful contributions offered in the book. One is represented in the following figure (5.1), in which Craver and Darden point out that there are multiple ways in which mechanisms are invoked in scientific research, not just one. The most common way in which we think of mechanisms is as “producers” of outcomes — the first panel of the figure. But there are several other valid uses as well. There is the “X underlies Y” relation (panel 2), in which we provide a set of mechanisms X as an explanation of how the properties of Y are constituted; and there is the “X maintains Y” relation, in which we provide a set of mechanisms X as an explanation of the homeostasis of Y (the feedback loops and corrective mechanisms that return Y’s properties to equilibrium after a period of drift or change).

 
 
Another interesting observation that C-D develop is the idea of “modular subassembly”. 

This process, modular subassembly, involves reasoning about how mechanism components might be combined in surprising ways. One hypothesizes that a mechanism consists of (either known or unknown) modules or types of modules. One cobbles together different modules to construct a hypothesized how-possibly mechanism, guided by the goal of finding modules to fill all the gaps in a productively continuous mechanism. In doing so, scientists draw upon their knowledge of the store of types of entities and activities and modules (i.e., interconnected entities and activities that have a particular function). (kl 1726)

This description invokes the idea of realistic inquiry into the subprocesses that give continuous action to the mechanism. Essentially this invokes the idea of opening the black box of the mechanism and asking how the mechanism itself works. And the ontological assumption is that the mechanism consists of discrete sup-processes.
 
A third valuable idea that is advanced in this work is the idea of multi-level mechanisms. 

Biological mechanisms typically span multiple levels. Scientists working at higher levels work on ecosystems, populations, and the behaviors of organisms within their environments. Others study mechanisms within organisms, such as the nervous or circulatory systems, and mechanisms within organs and cells, and, ultimately, mechanisms with smaller entities, such as macromolecules, small molecules, and ions. Different fields of biology are often (to a first approximation) associated with different levels. (kl 688)

This is an important point for social scientists as well, given the common tendency to bifurcate into “macro” and “micro” features of the social world. Instead, C-D give further grounds for insisting that there is a wide and continuous range of levels of aggregation in the social world, and that it is perfectly legitimate to formulate representations of mechanisms that span these levels. 
 
A key feature of C-D’s view of biological research is the notion that researchers make use of a wide but known stock of existing mechanisms in their efforts to understand novel phenomena. What are some of those mechanisms? Here is a very interesting table of miscellaneous biological mechanisms that Craven and Darden provide:
 
 


This table is useful exactly because it is not intended to be comprehensive or exhaustive. Rather, it is intended to provide a list of concrete mechanisms that have been observed and investigated in the biological sciences. And, as Craver and Darden argue, a large available base of known mechanisms provides a starting point for researchers who are confronting a novel phenomenon.


A collection of social mechanisms along these lines would also be valuable for researchers in the 
social sciences. Here is my own beginning of a table of social mechanisms:

Some Types of Social Mechanisms

CONTENTION
Escalation
Brokerage
Paramilitary organizations

COLLECTIVE ACTION
Prisoners’ dilemma
Free rider behavior
Convention
Norms
Selective benefits
Selective coercion

ORGANIZATIONAL ENFORCEMENT
Audit and accounting
Supervision
Employee training
Morale building
Leadership

SOCIAL COMMUNICATIONS
Interpersonal network
Broadcast
Rumor
Transport networks

 
 
 
 
ECONOMIC ACTIVITY
Market
Auction
Ministry direction
Contract
Democratic decision making
Producers’ control

GOVERNMENT
agenda setting
Log rolling
Regulatory organizations

STATE REPRESSION
Secret police
Informers
Spectacular use of force
Propaganda
Deception

SYSTEM
Flash trading
Interlocking mobilization
Overlapping systems of authority (Brenner)

 

How applicable is the Craver-Darden view of mechanism thinking when we turn to various areas of social research? There are obvious differences between the domains of biology and the social sciences, and this seems to be true when it comes to mechanisms.

One visible difference is the relative precision with which we can describe the workings of mechanisms in the two domains. The mechanism of “mismatch repair” mentioned in the C-D table under DNA Repair Mechanisms can be described in a great deal of precision, and this mechanism generally works in the same way in all settings. Compare that with the mechanism of “Audit and accounting” under Organizational Enforcement in my table above. This is also a “repair” function. But the audit function in an organization can be implemented in many different ways with varying degrees of coercion and voluntary compliance. So there is a much wider range of activities encompassed by “audit and accounting” than by “mismatch repair”.

There is another kind of precision mismatch that seems to exist between biology and social science as well — the idea that a mechanism produces the same results in a wide range of settings. Because of the molecular biology that underlies most of the mechanisms that C-D consider, these mechanisms perform like clock-work. Each tick leads to the same advancement of the wheel. But in the social world, the precision of relationship between input to a mechanism and output from the mechanism is much more slack. When a group of workers are called upon to support a wildcat strike, we may hypothesize that the free-rider mechanism will be invoked in this social setting. But free-riding may be so extensive as to cripple the strike, and it may be so limited as to barely influence the outcome at all. We can learn more about the social factors that differentiate these two outcomes. But the key point is that the mechanism is in play in both scenarios, but with very different effects.

One special strength of In Search of Mechanisms is the fact that it is a work of philosophy of science that is highly detailed in its treatment of some of the scientific content of a specific field. We cannot resolve the question of whether mechanisms are a good way of organizing scientific inquiry on the basis of apriori reasoning alone. Rather, we need to see how mechanisms-based reasoning is expressed in a range of scientific areas of inquiry. And this is exactly what Craver and Darden do in this book for a range of biological disciplines.

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