Microfoundations and causal powers

Image: Three Mile Island control room

There isn't a lot of cross-over between the microfoundations literature (Peter Hedstrom, Dissecting the Social: On the Principles of Analytical Sociology) and the causal-powers literature (Greco and Groff, Powers and Capacities in Philosophy: The New Aristotelianism). People who advocate the importance of microfoundations in the social sciences are usually looking for something like the individual-level mechanisms through which a higher-level pattern or entity comes about and persists. So the most natural relation is between microfoundations and mechanisms. And it is rare to find a powers theorist discussing the issue of microfoundations at all.

But it seems that this lack of intersection is the result of a clash of philosophical styles rather than an inherent logical or ontological fissure. The microfoundations group (e.g. Hedstrom, Elster, or myself in earlier versions) tends to be somewhat inclined towards an enlightened reductionism -- showing how higher level properties are produced by the workings of a lower level of phenomena. The causal powers group (e.g. Groff, Mumford and Anjum) are stoutly anti-reductionist; they seem to want to maintain that the powers of a thing are an irreducible and essential feature of the thing, not derivative from anything more fundamental.

But this opposition between the two research communities doesn't really seem compelling; it seems to derive from an abstract ontological preference rather than analytical arguments. So let's consider the question directly: how do the theories of microfoundations and causal powers relate to each other? Is it legitimate for microfoundations stories to invoke causal powers? And do causal-powers claims themselves require (or admit of) microfoundations?

The latter question seems to be the easier one. Whenever we attribute a causal power to a kind of stuff (conductivity to metal, violent volatility to a crowd, propensity to accidents to an organization), it is logical and appropriate to ask what it is about the substrate of the stuff that creates the power in question. What is it about the microstructure of metals that leads them to conduct electricity? What is it about crowds that leads them to be vulnerable to surges of violence? And what is it about certain kinds of organizations that leads them to be conducive to accidents like Three Mile Island or Bhopal? And when we answer these questions by detailing the microstructure of the stuff (metal, crowd, organization) and demonstrate how it is that this structure creates the durable power in question, then we have provided a microfoundation for the power. So powers admit of microfoundations. This response highlights the fact that the quest for microfoundations is really just an illustration of a pervasive explanatory strategy: investigate and measure the micro structure of the thing in question in order to discover why and how it behaves as it does.

Here is how I tried to sort out these relations in an earlier post on current thinking concerning the metaphysics of causality:

On this standpoint, powers are attributions we make to things when we don't know quite enough about their composition to work out the physics (or sociology) of the underlying mechanisms. They do attach to the entity or structure in question, surely enough; but they do so in virtue of the physical or sociological composition of the entity, not because of some inherent metaphysical property.

We might try to reconcile these two perspectives with a few simple ideas:

• Entities and structures at a range of levels of being have causal powers: active capacities to influence other entities and structures.
• Whenever we identify a causal power of a thing, it is always open to us to ask how this power is embodied; what it is about the inner constitution of the entity that gives it this power.
• When we succeed in arriving at a good scientific answer to this question, we will have shown that the power in question is not irreducible; it is rather the consequence of a set of mechanisms set in play by the constitution of the entity.

So the discovery of a given causal power of a thing is not a metaphysical fundamental; it is rather an empirical scientific discovery that invites analysis into its underlying composition.

The harder question is whether there is any compelling reason for microfoundations theorists to think they need to refer to causal powers in their accounts. And this is where the powers theorists have a strong position: it is hard to make sense of the idea of a mechanism without referring to a real (perhaps reducible) causal power. This argument was made in an earlier post (link). Here is the key observation in that post:

My thesis of the mutual compatibility of powers and mechanisms goes along these lines. If we press down on a putative mechanisms explanation, we are led eventually to postulating a set of causal powers that provide the motive force of the postulated mechanisms. But equally, if we press down on the claim that a certain kind of entity has a specified causal power or disposition, we are led to hypotheses about what mechanisms are set in play be its constituents so as to bring about this disposition.

Begin with a causal mechanism story:
C => {x happens bringing about y, bringing about z, bringing about u, which is E} => E

How is it that the sub-links of this chain of mechanism pieces happen to work to bring about their consequent? We seem to have two choices: We can look to discover a further underlying mechanism; or we can postulate that the sub-link entity or structure has the power to bring about its consequent. So if we push downward within the terms of a mechanism explanation, one way to close the story is by postulating a causal power at some level.

So we might say that the relation among these three ideas goes something like this: A demand for microfoundations is a demand for the causal mechanisms at work within the substrate of the stuff in question. Mechanisms require provisional reference to causal powers; so microfoundations in turn require reference to causal powers. And finally, causal powers at a given level both demand and admit of provision of microfoundations to explain how they in turn work. So microfoundations theorists can't really dispense with the topic of causal powers, and powers theorists shouldn't dispense with microfoundations either. The diagram at the top illustrates this logic. It is turtles, all the way down.

Modeling organizational recruitment

One defect of the ABMs considered in the prior post about the emergence of civil conflict is that they do not incorporate the workings of organizations into the dynamics of mobilization. And yet scholars like Tilly (Dynamics of Contention) and Bianco (Peasants without the Party: Grassroots Movements in Twentieth Century China) make it clear that organizations are critical to the development and scope of mobilization of a populace. So a model of civil conflict needs to be able to incorporate the effects of organizations in the mobilization and activation of large groups of individual agents. Here I will explore what we might want from an ABM that incorporates organizations.

Ideally I would like to see a model that incorporates:

• NxN individual actors (50x50 in the diagram above, or 2,500 agents)
• M organizations with different characteristics competing for membership among the actors
• A calculation of "uprising behavior" based on the net activation of a threshold percentage of actors in a circumscribed region

How might organizations be introduced into an agent-based model of social contention? I can imagine two quite different approaches. (A) We might look at organizations as higher-level agents within the process. As each organization works its way through the population it gains or loses members; and this affects individual behavior and the geographical distribution of activated agents. This would be an attempt to directly model the mechanism of mobilization through organizational mobilization. (B) Another possible and simpler approach is to represent organizations as environmental factors, analogous to disease vectors, which percolate through the population of first-order agents and alter their behavior. Let's consider both. 

(A) Organizations as meso-level agents. The first approach requires that we provide rules of behavior for both kinds of agents, and recognize that the two processes (organizational recruitment and individual action) may influence each other iteratively. Organizations compete for members and strive to create collective action in support of their agendas. Membership in an organization influences the individual actor by increasing activation. And increasing membership influences the functioning of the organization.

Individual actors gain organizational properties when they are recruited to one of the organizations. Suppose that individual actors have these properties (largely drawn from the Epstein model):

• grievance level
• risk aversiveness
• income level
• salience of ethnicity for identity 
• location
• Organization-driven properties of activation
• derived: level of activation (probability of involvement in response to an appeal from the organization)

If we want to model organizations as agents, then we need to specify their properties and action rules as well. We might begin by specifying that organizations have properties that affect their actions and their ability to recruit:

• content of political agenda / call to action
• perceived effectiveness
• real effectiveness
• number of cadres devoted to mobilization effort

For a simulation of inter-group conflict, we would like to include two ethnic groups, and one or more organizations competing within each group.

Mobilization occurs at the individual level: actors receive invitations to membership sequentially, and they respond according to the net effect of their current characteristics. Once an actor has affiliated, he/she remains susceptible to appeals from other organizations, but the susceptibility is reduced.

Membership in an organization affects an individual's level of engagement in a set of grievance issues and his/her propensity for action. Individuals may express their organizational status at a range of levels of activism:

• highly engaged 
• moderately engaged
• disengaged 

The model calculates each agent's behavior as a function of grievance, risk, appeal, location, and organizational influence.

This approach suggests development of two stages of simulation: first a simulation of the competition of two organizations within a group; and second, a simulation of the individual-level results of calls to action by multiple organizations involving a specified distribution of organizational affiliations.

(B) Organizations as infection vectors. A simpler approach is to represent the various organizations as contagious diseases that have differential infection rates depending on agent properties, and differential effects on behavior depending on which "infection" is present in a given agent. Presumably the likelihood of infection is influenced by whether the individual has already been recruited by another organization; this needs to be represented in the rules governing infection. It also implies that there is a fair amount of path dependence in the simulation: the organization that starts first has an advantage over competitors.

It seems it would be possible to incorporate a disease mechanism into the Epstein model to give a role for organizations in the occurrence of civil unrest.

Now imagine running the model forward with two types of processes occurring simultaneously. The organizations recruit members iteratively and the activation status of each individual is calculated on each tick of the model. At each tick every individual has a membership status with respect to the organizations ("infections"), and each has an activation level (low, medium, high). When a concentration of, say, 40% of agents are activated to a high level in a region of a given size, this constitutes an episode of uprising / ethnic violence / civil unrest.

Two fundamental questions arise about this hypothetical simulation. First, is the simulation assumption that "organizational mobilization is like an infectious disease" a reasonable one? Or does organizational mobilization have different structural and population dynamics than the spread of a disease? For example, diseases percolate through direct contact; perhaps organizational mobilization has more global properties of diffusion. And second, does the resulting simulation give rise to patterns that have realistic application to real processes of social contention? Do we learn something new about social contention and mobilization by incorporating the additional factor of "organization" in this way that the Epstein model by itself does not reveal?

(It should be noted that organizations are a peculiar kind of agent. They have properties that are characteristic of "complex adaptive systems": they are supra-individual, they are influenced by the actors they touch, and they influence the behavior of the actors they touch. So the behavioral properties of an organization perhaps should not be specified exogenously.)

(NetLogo is a sophisticated modeling package that permits researchers to develop small and medium-sized agent-based models, and it provides a number of relevant examples of simulations that are of interest to social scientists (link). Particularly interesting for the current purposes are a simulation of the Epstein model of rebellion discussed earlier (link) and an implementation of an AIDS contagion model that could be considered as a platform for modeling the spread of an organization or a set of ideas as well (link). Here is the link for NetLogo:
Wilensky, U. (1999). NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.)

ABM approaches to social conflict

Source: Pfautz and Salwen (link)

An earlier post addressed the question of the dynamics through which a stable community consisting of multiple groups may begin to polarize and fission into antagonisms and conflict. I speculated there that the tools of agent-based modeling might be of use here. What I had in mind was something like this. Suppose we have an urban population spread across space in a distribution that reflects a degree of differentiation of residence by income, religion, and race. Suppose religion is more segregated than either income or race across the region. And suppose we have some background theoretical beliefs about social networks, civic associations, communication processes and other factors influencing a disposition to mobilize. Perhaps ABM methods could allow us to probe different scenarios to see what effects these different settings produce for polarization and conflict.

There is a fair amount of effort at modeling this kind of social phenomena within the field of social simulation. Carlos Lemos et al provide an overview of applications of ABM techniques in social conflict and civil violence in "Agent-based modeling of social conflict, civil violence and revolution: state-of-the-art-review and further prospects" (link). Here is an overview statement of their findings about one specific approach, the threshold-based approach:

Social conflict, civil violence and revolution ABM are inspired on classical models that use simple threshold-based rules to represent collective behavior and contagion effects, such as Schelling’s model of segregation [7] and Granovetter’s model of collective behavior [15]. Granovetter’s model is a theoretical description of social contagion or peer effects: each agent a has a threshold Ta and decides to turn “active” – e.g. join a protest or riot – when the number of other agents joining exceeds its threshold. Granovetter showed that certain initial distributions of the threshold can precipitate a chain reaction that leads to the activation of the entire population, whereas with other distributions only a few agents turn active. (section 3.1)

Here is a diagram of their way of conceptualizing the actors and the processes of social conflict into which they are sometimes mobilized.

Armano Srbljinovic and colleagues attempt to model the emergence of ethnic conflict in "An Agent-Based Model of Ethnic Mobilisation" (link). Their original impulse is to better explain the emergence of polarized and antagonistic ethnic conflict in the former Yugoslavia; their method of approach is to develop an agent-based model that might capture some of the parameters that induce or inhibit ethnic mobilization. They refer to the embracing project as "Social Correlates of the Homeland War". They believe an ABM can potentially illuminate the messy and complex processes of ethnic mobilization observed on the ground:

Our more moderate goals are based on a seemingly reasonable assumption that the results observed in a simplified, artificial society could give us some clues of what is going on, or perhaps show us where to centre our attention in further and more detailed examination of a more complex real-world society. (paragraph 1.4)

They describe the eighties and nineties in this region in these terms:

So, by the end of the eighties and the beginning of the nineties, the ethnic roles in the society of the former Yugoslavia, that were kept toward the middle of Banton's social roles-scale for more than forty years, now under the influence of political entrepreneurs, increased in importance. (paragraph 2.5)

And they would like to explain some aspects of the dynamics of this transition. They single out a handful of important social characteristics of individuals in the region: (a) ethnic membership, (b) ethnic mobilization, (c) civic mobilization, (d)grievance degree, (e) social network, (f) environmental conditions, and (g) appeals to action. Each actor in the model is assigned a value for factors a-e; environmental conditions are specified; and various patterns of appeals are inserted into the system over a number of trials

The algorithm of the model calculates the degree of mobilization intensity for all the agents as a function of the frequency of appeals, the antecedent grievance level of the agent, and a few features of the agents' social networks. If we add a substantive hypothesis about the threshold of M after which group action arises, we then have a model of the occurrence of ethnic strife.

The model uses a "SWARM" methodology. It postulates 200 agents, half red and half blue; and it calculates for each agent a level of mobilization intensity for a sequence of times, according to the following formula:

• mi(t+1) = mi(t) + (miapp + misocnet + micool)Δt    (paragraph 3.8)

This formula calculates the i^th individual's new level of mobilization intensity m depending on the prior intensity, the delta created by the appeal, the delta created by the social network, and the "cooling" for the current period. (It is assumed that mobilization intensity decays over time unless re-stimulated by appeals and social network effects.)

This is a very interesting experiment in modeling of a complex interactive social process. But it also raises several important issues. One thing that is apparent from careful scrutiny of this model is that it is difficult to separate "veridical" results from artifacts. For example, consider this diagram:

Is the periodicity shown by Red and Blue mobilization intensities a real effect, or is it an artifact of the design of the model?

Second, it is important to notice the range of factors the simulation does not consider, which theorists like Tilly would think to be crucial: quality of leadership, quality and intensity of organization, content of appeals, differential pathways of appeals, and variety of political psychologies across agents. This simulation captures several important aspects of this particular kind of collective action. But it omits a great deal of substantial factors that theorists of collective action would take to be critical elements of the dynamics of the situation.

Here is a second example of an attempt to simulate aspects of ethnic mobilization provided by Stacey Pfautz and Michael Salwen, "A Hybrid Model of Ethnic Conflict, Repression, Insurgency and Social Strife" (link). Pfautz and Salwen describe their work in these terms:

Ethnic Conflict, Repression, Insurgency and Social Strife (ERIS) is a comprehensive, multi-level model of ethnic conflict that simulates how population dynamics impact state decision making and, in turn, respond to state actions and policies. Population pressures (e.g., relocation, civil unrest) affect and are affected by state actions. The long term goal of ERIS is to support operations development and analyses, enabling military planners to evaluate evolving situations, anticipate the emergence of ethnic conflict and its negative consequences, develop courses of action to defuse ethnic conflict, and mitigate the second and third order effects of U.S. actions on ethnic conflict. (211)

They refer to theirs as a hybrid model, incorporating a macro-level "systems dynamics" model and a micro-level ABM model. Their model thus attempts to represent both micro and macro causal forces on ethnic mobilization, illustrated in the diagram at the top. This model increases the level of "realism" in the assumptions represented in the simulation. Agents are heterogeneous, and their decision-making is contextualized to location on a GIS grid.

Agents represent 1000 individuals and are uniform with respect to religious affiliation. Agents are sampled with respect to age and sex ratio; however, skew sampling is used to create agents with different demographic profiles with respect to these attributes. Agents also have attributes to capture propensities to conflict and tolerance, which affect agent behavior and interact in the aggregate with the macro-level model to localize reports of conflict. (212)

Key variables in their simulation are religious identity, demographic change, population density, the history of recent inter-group conflict, and geographical location. The action space for individuals is: move location, mobilize for violence. And their model is calibrated to real data drawn from four states in Northwest India. Their basic finding is this: "Conflict is predicted in this model where islands or peninsulas of one ethnicity are surrounded by a sea of another (Figure 2.1)."

Kent McClelland offers a computational model that responds to Randall Collins' concepts of "C-Escalation" and "D-Escalation" in inter-group conflict. McClelland's piece is "CYCLES OF CONFLICT A Computational Modeling Alternative to Collins’s Theory of Conflict Escalation" (link). Here is how he describes his approach:

In this paper, I use a variation of systems theory to construct a multi-agent computational model of dynamic social interaction that shows how the conflict-escalation processes described by Collins can be generated in computer simulations. Like his, my model relies on feedback loops, but the mathematical formulas in my model use negative feedback loops, rather than positive feedback loops, to generate the collective processes of positive feedback described in Collins’s model of conflict escalation. My analysis relies on perceptual control theory (PCT), a dynamic-systems model of human behavior, which proposes that neural circuits in the brain are organized into hierarchies of negative-feedback control systems, and that individuals use these control systems to manipulate their own environments in order to control the flow of perceptual input in accordance with their internally generated preferences and expectations. (6)

Lars-Erik Cederman uses an ABM approach to model geopolitical boundaries (link). Here is how he describes his goals:

A decade ago, the Soviet Union ceased to exist, Yugoslavia started to disintegrate, and Germany reunified. Marking the end of the Cold War, these epochal events illustrate vividly that change in world politics features not just policy shifts but also can affect states' boundaries and, sometimes, their very existence. Clearly, any theory aspiring to explain such transformations or, more generally, the longue durée of history, must endogenize the actors themselves.

The current paper describes how agent based modeling can be used to capture transformations of this boundary transforming kind. This is a different argument from that advanced by most agent-based modelers, who resort to computational methods because they lend themselves to exploring heterogeneous and boundedly rational, but otherwise fixed, actors in complex social environments (1, 2). Without discounting the importance of this research, I will use illustrations from my own modeling framework to illustrate how it is possible to go beyond this mostly behavioral agenda. The main emphasis will be on the contribution of specific computational techniques to conceptualization of difficult to grasp notions such as agency, culture, and identity. Although a complete specification of the models goes beyond the current scope, the paper closes with a discussion of some of their key findings.

Cederman's model incorporates three primary dynamics: "Emergent Polarity" (the idea that boundaries result from a process of conquest); "Democratic Cooperation" (the idea that "Democracy" functions as a tag facilitating cooperation among subsets of actors); and "Nationalist Systems Change" (the idea that boundaries result from actors seeking locations placing them in proximity to other actors possessing the same ethnic identity).

Here is a diagram representing stylized results of the simulation.

Epstein, Steinbruner, and Parker offer a model of civil violence (link). Here are the parameters that are assigned to all actors (population and cops): grievance, hardship, perceived legitimacy, risk aversiveness, field of vision, net risk, location, and decision to act. This is a very simple analysis of collective action, plainly derivative from a rational-choice approach. Each actor decides to act or not depending on his/her calculation of risk and hardship/grievance. These assumptions are vastly weaker than those offered by students of contentious politics like McAdam, Tarrow, and Tilly; but they generate interesting collective results when embodied in a generative ABM.

This research is specifically interesting in the context of the question posed here about fissioning. Consider this series of frames from an animation reflecting the results of random fluctuation of densities in an ethnically mixed community:

Peaceful coexistence

Animation of process leading to ethnic separation / ethnic cleansing

With "peace-keepers" the results are different:

These are interesting results. Plainly the presence or absence of peace-enforcers is relevant to the extent of ethnic violence that occurs. But notice once again how sparse the behavioral assumptions are. The simulations essentially serve to calculate the interactive effects of this particular set of assumptions about agents' behavior -- with no ability to represent organizations, communication, variations in motivation, etc.

All these models warrant study. They attempt to codify the behavior of individuals within geographic and social space and to work out the dynamics of interaction that result. But it is very important to recognize the limitations of these models as predictors of outcomes in specific periods and locations of unrest. These simulation models probably don't shed much light on particular episodes of contention in Egypt or Tunisia during the Arab Spring. The "qualitative" theories of contention that have been developed probably shed more light on the dynamics of contention than the simulations do at this point in their development.

Social conflict and group mobilization

source: Du Shiyu and Qi Jiayan, "Multi-agent Modeling and Simulation on Group Polarization Behavior in Web 2.0"

An earlier post drew attention to the fact that there are sometimes powerful forces leading to the disintegration of previously peaceful populations of people into violent opposition across groups (link). A population concentrated in a geographical space (city, region) almost always represents a variety of sources of differentiation across groups: racial differences, economic differences, and cultural and religious differences, to mention several important ones. And virtually any sources of group identity and group wellbeing can potentially be a source of conflict and opposition within the population. So the earlier post asked the question, what are the factors that lead these latent conflicts to break out into active conflict? What leads individuals within a group to begin to mobilize together with the goal of resisting or attacking members of other groups?

Several factors are evident. First, there are multiple kinds of agents in play, both individual and collective. The cohesion-fission results are the complex consequence of the agency and strategies of these many agents and their strategic interactions. And there are agents working to secure cohesion at the same time as other agents work to bring about conflict across groups. Second, there are multiple sources of collective grievance that may serve to provide the raw materials for mobilization -- fields over which groups have different levels of access to outcomes that they want to control. And third, there are a variety of structural factors that appear to be relevant to the dynamic processes of mobilization that may occur. Let's look at each of these.

Agents

Leaders. Leaders sometimes have an interest in using inter-group conflict as a basis for mobilization of supporters around them, for the purpose of extending their power and the resources they control. (This is often referred to as "political entrepreneurship.") Political leaders can provoke polarization by giving particular salience to one set of group characteristics over another. Lies, distortions, and emotional exhortation can provoke rank-and-file followers to increase their emotional level of commitment to the program of this group or that. The history of BJP in India as a provoker of Hindu-Muslim antagonism is a case in point (Atul Kohli, Democracy and Discontent: India's Growing Crisis of Governability). (A good illustration is Sam Popkin's "Political entrepreneurs and peasant movements in Vietnam" in Michael Taylor, Rationality and Revolution.) Here is Popkin's description:

This chapter examines the mobilization of peasants during the Vietnamese revolution. It shows how, out of the rational choices of myriad individual, peasant society can be restructured and new institutions constructed. It shows in particular how peasant organizers, starting with limited material resources and using only their organizational skills, can "bootstrap" their organizations into existence and so "build something from nothing". Through small interventions in the patterns of daily life these political and religious organizers, here called political entrepreneurs, build institutions which generate a "revolutionary surplus" or profit, and financed by this surplus they then use their local bases to recruit people to a national struggle. (9) 

Organizations. Organizations have the ability to communicate with their members; they can supply resources to support mobilization (lease buses to transport demonstrators to the capital city); and they can educate and indoctrinate followers into a particular social world view. There is a wide range of organizations that are relevant to mobilization in a social environment:

• Community-based organizations
• Youth and student organizations
• Gangs and criminal organizations
• Business and industry
• Religious organizations and leaders

Organizations also have the opportunity of building a high degree of emotional adherence in their members. Michael Mann emphasizes each of these avenues of influence in his analysis of fascist paramilitary organizations in the 1930s (link). 

Ordinary rank-and-file actors. Most people at any given time are not actively engaged in protest or militant activity. So the success or failure of efforts to polarize a population depend on the ability of leaders and organizations to activate these ordinary actors.

Grievances

Now turn to the grievances that may lead actors to mobilize for action against another group. The primary source of conflict among groups within Marxist theory is property. Class conflict is the primary social conflict. But much social conflict seems to arise from non-material factors --

• Material conflict of interest across communities (property, wealth, income, jobs)
• Cultural and religious conflict of practice
• Conflict over political power within the state over resources
• Kinship relations and conflicts across kinship groups

So there is a wide range of potential causes for polarization. However, at most times and places these potential grievances remain latent rather than expressed. Leaders and organizations can extend efforts towards mobilizing the emotions and adherence of members of society for solidarity around one or another set of grievances.

Influences on the spread of conflictual mobilization

Proximity. The spatial distribution of people across a region influences the ease with which they communicate with each other. Neighbors are more likely to be influenced in their beliefs and motives for action than are strangers from widely separated parts of the city. C. K. Lee points out the impact that dormitory-style living arrangements had for workers in "sunset" industries in China; rumors and calls to action flowed easily through the residential buildings (Against the Law: Labor Protests in China's Rustbelt and Sunbelt).

Social networks of affiliation. Social networks create communications pathways; they also create differentiated networks of trust. The fact that Suneel's brother-in-law Atul attends the same temple as Suneel gives Suneel elevated grounds for trusting and relying upon Atul when it comes to learning current information and in responding to calls for action conveyed by Atul.

Incidents. Mobilization within a subcommunity is often triggered by an instigating incident -- a traffic accident, an incidence of police brutality, an ethnic slur, a rumor of bad behavior by a member of another subcommunity. The police raid on the blind pig in Detroit in 1967 unleashed a cycle of mobilization and counter-mobilization within Detroit's population and the state and federal governments.

Tools

Broadcast media. As was evident in the Rwanda genocide (link), control of radio or television stations is a major advantage for organizations and leaders who are seeking to mobilize their followers for a given kind of action.

Direct face-to-face mobilization. Organizations like labor unions, community-based organizations, and industry associations often have substantial personnel on the ground -- cadres -- who serve to communicate with and motivate the rank-and-file members and potential adherents. One important example is the GOTV efforts that various organizations are able to mount in times of elections. Another is the visibility and influence in urban neighborhoods that the Black Panthers created in the 1960s through their food programs.

Social media. It is widely believed, especially since the rapid mobilizations associated with the Arab Spring, that social media like Twitter, Facebook, and Instagram can serve as effective pathways of mobilization and activization. (link)

We still haven't gotten to a clear answer to the question: under what conditions does a community begin to fission into conflicting components? But this analysis of the elements of the situation sheds some light on the facilitating or inhibiting factors that are relevant to such a process of fissioning. When leaders and organizations emerge who have a political interest in creating division (not an uncommon situation); when genuine underlying tensions exist (pertaining to resources or identity markers); and when features of proximity, interrelatedness, and weakness of policing permit the spread of divisive messages of faction; then fissioning is increasingly like.

What is a morphogenic society?

diagram: Erik Olin Wright, The Value Controversy and Social Research (link)

Margaret Archer's research collaboration on topics concerning the theory of morphogenesis continues with the publication of the third volume in the Social Morphogenesis series, Generative Mechanisms Transforming the Social Order. (The first two volumes have been treated in earlier posts; link, link.) Like the earlier volumes, this volume offers a highly stimulating treatment of issues that are prominent in the branch of the critical realism research community that Archer has defined. The focus here is upon the idea of "generative mechanisms," which allows for a very interesting set of connections to other segments of the philosophy of social science field. Contributors to this volume include Phil Gorski, Colin Wight, Pierpaolo Donati, Wolfgang Hofkirchner, Emmanuel Lazega, Andrea Maccarini, Doug Porpora, Tony Lawson, and Ismael Al-Amoudi and John Latsis, as well as Archer herself.

Archer puts the guiding question of the research collaboration in these terms:

We are seeking a causal explanation of what could ... lead the social formation of late modernity to change into a one that is very different in kind precisely in terms of its relational organization. (1-2)

In other words, it is change in the relational structure of modern society that is the object here; and the search for generative mechanisms is a search for the processes internal to late modernity that bring this structural change about. Put in these terms, the objective is reminiscent of Marx's goal in Capital: to discover the internal dynamics within the capitalist mode of production that were likely to lead to fundamental structural change within the mode of production and the birth of a successor mode of production. Here is a typical formulation, offered in the preface to the first edition of Capital: "Intrinsically, it is not a question of the higher or lower degree of development of the social antagonisms that result from the natural laws of capitalist production. It is a question of these laws themselves, of these tendencies working with iron necessity towards inevitable results. The country that is more developed industrially only shows, to the less developed, the image of its own future." Marx believes the key mechanism driving change within capitalism is the "social antagonisms" of the defining property system. And he believes that this mechanism will lead ultimately to fundamental change in the structure of the mode of production. Where Archer refers to a system of social relations, Marx refers to the system of relations of property and power. But both seem to be asking the same kind of question: what are the causes of fundamental structural change in a society?

Archer and her collaborators continue to employ what they call the "S-A-C" framework: structure-action-culture. The fundamental idea here is that social processes and the mechanisms of social transformation almost always involve each of the axes of this framework. So it is important to pay attention to the structured environments in which social action takes place; the embodied schemata of action in which actors act and interact; and the elements of culture and value that refract action within contingent structures. This way of framing the social world and its dynamics has the consequence of discouraging reductionist and single-factor accounts of change. Rather, morphogenetic mechanisms are heterogeneous.

A key question for this programme of research is that of the meaning of "morphogenic" society. What precisely is a morphogenic society? The contrast between morphogenesis and morphostasis is a reasonably clear one.  Borrowing from Walter Buckley, Archer defines morphogenesis as "those processes which tend to elaborate or change a system's given form, structure or state" (1). Analogously, morphostasis can be defined as "those processes which tend to stabilize and recreate a system's given form, structure or state". As Archer and many of her collaborators emphasize, both dynamic processes of change and corrective processes of stability require social explanation, and both kinds of processes are underway in virtually any social order. Moreover, it is possible to identify concrete social mechanisms that contribute to both higher-level characteristics: mechanisms that bring about systemic change and mechanisms that tend to reinforce existing structures.

So morphogenesis and morphostasis are reasonably clear as analytical concepts. But what is a morphogenic society? One possible reading is that a morphogenic society is one in which the change-driving (morphogenetic) characteristics of the society are substantially more dominant than the stability-enhancing (morphostatic) characteristics; so a morphogenic society is one that tends to undergo rapid and non-convergent change. Archer doesn't give a definition of the meaning of this concept in this volume (though the second volume of this series is also primarily focused on the idea of a morphogenic society). But Andrea Maccarini provides a brief and useable definition in his contribution to the current volume.

I will use the word ‘morphogenetic’ to refer to the intrinsic tendency of all human societies to generate and change (social) forms, while I call ‘morphogenic’ the specific societal syndrome characterized by the situational logic of opportunity, stemming from ‘unbound morphogenesis’ (signifying one unfettered from morphostasis) and leading to a wholly novel societal formation. (159)

This definition is consistent with the reading offered here. A morphogenic society is one that is largely characterized by morphogenetic mechanisms with a relative lack of morphostatic mechanisms, with the result that this society experiences large structural change and does not converge upon a subsequent stable (morphostatic) eqilibrium.

What is the medium-term result of a complex system like society which undergoes constant and non-convergent change? This is a critical and difficult question. Once again, Maccarini is the researcher who addresses it most directly:

The issue concerning the social quality of a morphogenic societal formation – the crucial question about what social life will be like if the MS finally becomes our social universe – must remain as uncertain as all statements about the future do. But the practical answer is already unfolding before our eyes. (172)

He hypothesizes a process of social change that leads to heterogeneity and change but also permits of a degree of local stability:

The march toward a societal formation we can call ‘morphogenic’ can be conceived of as a stepwise process, whereby mechanisms produce emergent properties and entities, and these gradually coalesce to generate new ‘environments’, i.e. ‘parts’ or ‘islands’ of society (organizational sectors, inter-institutional complexes, regions, etc.) that are in tune with the morphogenic logic. The scale of such innovations tends to increase, as well as do further links among them, and the eventual outcome would be a whole ‘society’ in which all the main processes finally work according to that logic. The argument I am presenting builds a gradual path to the characterization of a whole societal formation, and could be outlined as follows. (165)

I'm not sure this description is coherent, however, with the idea of a morphogenic society. The problem is that it envisions an eventual equilibrium -- a new set of social arrangements that maintain their characteristics over time. These are new "environments ... that are in tune with the morphogenic logic." But this implies a new form of stasis -- structural stability over time -- and therefore a society that is no longer "morphogenic". There is a suggestion in Maccarini's argument that she is aware of this tension, and she highlights the idea that the new emergent formations are not exactly forms of "morphostasis". Instead, to capture the idea that these new stabilities are contingent and subject to future change she refers to them as enclaves and vortices (167) -- temporary and local forms of stability within a larger process of change. Vortices may persist even under environments that embody a great deal of turbulence.

This implies a worldview that is indeed different from both Heraclitean flux (or liquid modernity; link) and Platonic stability -- a view of the social world in which persistence is bounded and embedded within larger fields of change. She writes:

Such studies allow us to model morphogenetic / morphostatic cycles, comprising gradual change, catastrophes and sudden collapses, social de-generation and re-generation. In other words, they describe and model the possible ‘rhythm’ of social morphogenesis within particular time spans, characterized by given conditions and structures, in concrete case studies. The pivotal concept of the whole argument is that of turbulence. (167)

These topics just scratch the surface of Generative Mechanisms Transforming the Social Order, and a subsequent post will pick up several other important threads of the research presented here.

Marx on peasant consciousness

One of Marx's more important pieces of political writing is the The Eighteenth Brumaire of Louis Bonaparte (1851) (pdf). Here is his analysis of the causes of the specific nature of peasant political consciousness leading to the election of Napoleon III:

The small-holding peasants form an enormous mass whose members live in similar conditions but without entering into manifold relations with each other. Their mode of production isolates them from one another instead of bringing them into mutual intercourse. The isolation is furthered by France‘s poor means of communication and the poverty of the peasants. Their field of production, the small holding, permits no division of labor in its cultivation, no application of science, and therefore no multifariousness of development, no diversity of talent, no wealth of social relationships. Each individual peasant family is almost self-sufficient, directly produces most of its consumer needs, and thus acquires its means of life more through an exchange with nature than in intercourse with society. A small holding, the peasant and his family; beside it another small holding, another peasant and another family. A few score of these constitute a village, and a few score villages constitute a department. Thus the great mass of the French nation is formed by the simple addition of homologous magnitudes, much as potatoes in a sack form a sack of potatoes. Insofar as millions of families live under conditions of existence that separate their mode of life, their interests, and their culture from those of the other classes, and put them in hostile opposition to the latter, they form a class. Insofar as there is merely a local interconnection among these small-holding peasants, and the identity of their interests forms no community, no national bond, and no political organization among them, they do not constitute a class. They are therefore incapable of asserting their class interest in their own name, whether through a parliament or a convention. They cannot represent themselves, they must be represented. Their representative must at the same time appear as their master, as an authority over them, an unlimited governmental power which protects them from the other classes and sends them rain and sunshine from above. The political influence of the small-holding peasants, therefore, finds its final expression in the executive power which subordinates society to itself.

This a particularly interesting analysis of the social psychology of group solidarity, and one that has contemporary significance as well. It sheds a lot of light on how Marx thinks about the formation of class consciousness -- even as it significantly misunderstands the agency of rural people.

What are the limitations of the French peasantry, according to Marx here? They are isolated, burdened, unsophisticated, primitive, apolitical, and ignorant of the larger forces around them. Therefore, Marx says, they cannot constitute a unified and purposive political force. (The photo of a battalion of Vietnam Minh troops in Indochina just a century later refutes this conception.)

From this description we can draw several positive ideas about the foundations of collective solidarity. Here are the elements that Marx takes to be crucial in the formation of collective consciousness in this passage:

1. The group needs to possess "manifold relations" to each other.
2. There needs to be effective communication and transportation across space, not just local interaction.
3. There needs to be a degree of economic interdependence.
4. There need to be shared material conditions in the system of production.
5. There needs to be an astute appreciation of the social and economic environment.
6. There needs to be organization and leadership to help articulate a shared political consciousness and agenda. 

And Marx seems to have something like a necessary and sufficient relation in mind between these conditions and the emergence of collective consciousness: these conditions are jointly sufficient and individually necessary for collective consciousness in an extended group.

There are several crucial ideas here that survive into current thinking about solidarity and mobilization. So Marx's thinking about collective consciousness was prescient. It is interesting to consider where his thoughts about collective solidarity came from. How did he come to have insightful ideas about the social psychology of mobilization and solidarity in the first place? This isn't a topic that had a history of advanced theory and thinking in 1851.

Two sources seem likely. First is the tradition of French socialist thought in which Marx was immersed in the 1840s. French socialist thinkers were in fact interested in the question of how a revolutionary spirit came to be among a group of people. And second is Marx's own experience of working people in Paris in 1843-45. He writes of his own observations of working people in the Economic and Philosophic Manuscripts in 1844:

When communist artisans associate with one another, theory, propaganda, etc., is their first end. But at the same time, as a result of this association, they acquire a new need – the need for society – and what appears as a means becomes an end. In this practical process the most splendid results are to be observed whenever French socialist workers are seen together. Such things as smoking, drinking, eating, etc., are no longer means of contact or means that bring them together. Association, society and conversation, which again has association as its end, are enough for them; the brotherhood of man is no mere phrase with them, but a fact of life, and the nobility of man shines upon us from their work-hardened bodies.

Here Marx gives as much importance to the substantive relations of friendship and everyday association as he does to shared material interests in the formation of the class consciousness of French workers.

Marx's misunderstanding of the political capacity and consciousness of peasant communities has been noted by many scholars of rural revolutions. James Scott once opened a public lecture on the revolutions of the twentieth century by saying that his lecture would only treat the peasant revolutions of the century. But he then paused and laughed, and said, this isn't much of a limitation, because they were all peasant revolutions! Marx's assumption that only urban workers were capable of revolutionary consciousness was a serious misreading of the coming century of anti-capitalist and anti-colonial struggles. (Here is an earlier post on Scott's studies of peasant politics. Scott's accounts can be found in Weapons of the Weak: Everyday Forms of Peasant Resistance and The Moral Economy of the Peasant: Rebellion and Subsistence in Southeast Asia. Eric Wolf's Peasant Wars of the Twentieth Century picks up similar themes.)

Also interesting in the Eighteenth Brumaire is Engels' statement on the law of history as class struggle in his preface to the third edition of the book:

In addition, however, there was still another circumstance. It was precisely Marx who had first discovered the great law of motion of history, the law according to which all historical struggles, whether they proceed in the political, religious, philosophical or some other ideological domain, are in fact only the more or less clear expression of struggles of social classes, and that the existence and thereby the collisions, too, between these classes are in turn conditioned by the degree of development of their economic position, by the mode of their production and of their exchange determined by it. This law, which has the same significance for history as the law of the transformation of energy has for natural science -- this law gave him here, too, the key to an understanding of the history of the Second French Republic. He put his law to the test on these historical events, and even after thirty-three years we must still say that it has stood the test brilliantly.

Engels plainly endorses the idea of laws of motion of society and the idea of class conflict as the primary motor of historical change. "History is a history of class struggle." There is not much room for contingency or conjunctural causation here! But this is a dimension of Marxist theory that is plainly incorrect. Far better is to understand history in a more multi-factoral way in which contingency, conjunction, and agency all play a role.

Durkheim's nightmare

So here is Paris today ... thousands of anonymous strangers on Boulevard Saint-Germain at 5 pm, no sense of common bond or shared identity, a void of powerful values, lives of bleak consumerism. Anomie writ large. No friends, no community, no ceremony, no shared rituals. No eye contact on the street, no presumption of common cause. A Tom Waits world. It is Durkheim's nightmare about modernity.

Or is it? It is a city, to be sure, unlike a village. So the anonymity quotient is very high. But is it really a place of rampant anomie and hermetic individual dissatisfaction? Or is it instead a location for many thousands of micro-communities--religious, civic, ethnic, occupational? Is it a place with dense networks of friends, associates, and family, more intimately connected by cell phones than the village ever was through chance meetings at the market or the church? Is it in fact a powerful environment for human flourishing and social deepening?

In fact, it appears that the latter is the case for a large number of Parisians.

This may seem like a point that Durkheim anticipated through his distinction between mechanical and organic solidarity. But Durkheim's emphasis with the latter concept was on economic interdependency -- the division of labor -- rather than a recognition of the possibility of manifold micro-social relationships constituting a patchwork social world.

We might say that rather than anomie, the key shortcoming of modern cities like Paris -- or New York, Chicago, or London -- is social inequality and dramatically reduced opportunities for the bottom half of the income ladder. The people captured in the photo above have something in common beyond their cell phones -- they are mostly employed and affluent. But that profile of affluence is representative only of a fraction of the city's residents -- as documented by the excellent Observatoire des inégalités (http://www.inegalites.fr/). Just take the RER or Metro to the banlieue that surround the city to see the sharp separation of social worlds that Paris encompasses (http://jia.sipa.columbia.edu/paris-banlieue-peripheries-inequity/).

So it seems that the conception of the modern city implicit in Durkheim's thought is seriously wrong. The city is a different kind of locus for social interaction and individual life than the traditional town or village. But it is not inherently toxic for that reason. What is toxic is rather the dimension brought out by Marx -- the tendency of modern capitalist society to sharpen the separation between have's and have-nots.

It is not entirely an accident that I'm brought to think of Durkheim, since he spent much of his career less than a kilometer up Boule St.-Germain from this intersection. Ironically, Marx was here too in 1843.

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.)

A survey of agent-based models

Federico Bianchi and Flaminio Squazzoni have published a very useful survey of the development and uses of agent-based models in the social sciences over the past twenty-five years in WIREs Comput Stat 2015 (link). The article is a very useful reference and discussion for anyone interested in the applicability of ABM within sociology.

Here is their general definition of an ABM:

Agent-based models (ABMs) are computer simulations of social interaction between heterogeneous agents (e.g., individuals, firms, or states), embedded in social structures (e.g., social networks, spatial neighborhoods, or institutional scaffolds). These are built to observe and analyze the emergence of aggregate outcomes. By manipulating behavioral or interaction model parameters, whether guided by empirical evidence or theory, micro-generative mechanisms can be explored that can account for macro-scale system behavior, that is, an existing time series of aggregate data or certain stylized facts. (284)

This definition highlights several important features of the ABM approach:

• unlike traditional rational choice theory and microeconomics, it considers heterogeneous agents
• it explicitly attempts to represent concrete particulars of the social environment within which agents act
• it is a micro to macro strategy, deriving macro outcomes from micro activities
• it permits a substantial degree of "experimentation" in the form of modification of base assumptions
• it is possible to provide empirical evidence to validate or invalidate the ABM simulation of a given aggregate outcome 

Bianchi and Squazzoni note that the primary areas of application of agent-based models in social-science research include a relatively limited range of topics. The first of these topics included uncoordinated cooperation, reciprocity, and altruism. Robert Axelrod's work on repeated prisoners' dilemmas represents a key example of modeling efforts in this area (link).

A peculiar form of altruism is punishment: imposition of a cost on non-cooperators by other actors. Without punishment the exploitation strategy generally extinguishes the cooperation strategy in a range of situations. A "reciprocator" is an actor who is open to cooperation but who punishes previous non-cooperators on the next interaction. Bianchi and Squazzoni spend time describing an ABM developed by Bowles and Gintis (link) to evaluate the three strategies of Selfish, Reciprocator, and Cooperator, and a derived Shirking rate in a hypothetical and heterogeneous population of hunter-gatherers. Here is Bowles and Gintis' hypothesis:

The hypothesis we explore is that cooperation is maintained because many humans have a predisposition to punish those who violate group-beneficial norms, even when this reduces their fitness relative to other group members. Compelling evidence for the existence and importance of such altruistic punishment comes from controlled laboratory experiments, particularly the study of public goods, common pool resource, ultimatum, and other games.

And here is their central finding, according to Bianchi and Squazzoni:

They found that the robustness of cooperation depended on the coexistence of these behaviors at a group level and that strong reciprocators were functional in keeping the level of cheating under control in each group (see the shirking rate as a measure of resources lost by the group due to cheating in Figure 1). This was due to the fact that the higher the number of cooperators in a group without reciprocators, the higher the chance that the group disbanded due to high payoffs for shirking. (288)

Here is the graph of the incidence of the three strategies over the first 3000 periods of the simulation published in the Bowles and Gintis article:

 

This graph represents the relative frequency of the three types of hunter-gatherers in the population, along with a calculated shirking rate for each period. The Selfish profile remains the most frequent (between 40% and 50%, but Reciprocators and Cooperators reach relatively stable levels of frequency as well (between 30% and 40%, and between 20% and 30%). As Bowles and Gintis argue, it is the robust presence of Reciprocators that keeps the Selfish group in check; the willingness of Reciprocators to punish Selfish actors keeps the latter group from rising to full domination.

In this simulation the frequencies of Selfish and Shirking begin high (>85%) and quickly decline to a relatively stable rate. After 1000 iterations the three strategies attain relatively stable frequencies, with Selfish at about 38%, Reciprocator at 37%, Cooperator at 25%, and a shirking rate at about 11%.

It is tempting to read the study as representing a population that reaches a rough equilibrium. However, it is possible that the appearance of equilibrium conveyed by the graph above is deceptive. Other areas of complex phenomena raise the possibility that this is not a longterm equilibrium, but rather that some future combination of percentages of the three strategies may set off a chaotic redistribution of success rates. This is the key characteristic of a chaotic system: small fluctuations in parameters can lead to major deviations in outcomes.

Also interesting in Bianchi and Squazzoni's review is their treatment of efforts to use ABMs to model the diffusion of cultural and normative attitudes (293ff.). Attitudes are treated as local "contagion" factors, and the goal of the simulation is to model how different adjacencies influence the pattern of spread of the cultural features.

Agents interacted with neighbors with a probability dependent on the number of identical cultural features they shared. A mechanism of interpersonal influence was added to align one randomly selected dissimilar cultural feature of an agent to that of the partner, after interaction. (294ff.)

Social network characteristics have been incorporated into ABMs in this area.

Bianchi and Squazzoni also consider ABMs in the topic areas of collective behavior and social inequality. They draw a number of useful conclusions about the potential role that ABMs can play in sociology, including especially the importance of considering heterogeneous agents:

At a substantive level, these examples show that exploring the fundamental heterogeneity of individual behavior is of paramount importance to understand the emergence of social patterns. Cross-fertilization between experimental and computational research is a useful process. It shows us that by conflating the concept of rationality with that of self-interest, as in standard game theory and economics, we cannot account for the subtle social nuances that characterize individual behavior in social contexts. (298)

And they believe -- perhaps unexpectedly -- that the experience of building ABMs in a range of sociological contexts underlines the importance of institutions, norms, and social context:

Moreover, these ABM studies can help us to understand the importance of social contexts even when looking at individual behavior in a more micro-oriented perspective. The role of social influence and the fact that we are embedded in complex social networks have implications for the type of information we access and the types of behavior we are exposed to. (301)

This is a useful contribution for sociologists, as a foundation for a third alternative between statistical studies of sociological phenomena and high-level deductive theories of those phenomena. ABMs have the potential of allowing us to derive large social patterns from well chosen and empirically validated behavioral assumptions about actors.

I mentioned the common finding in complexity studies that even fairly simple systems possess the capacity for sudden instability. Here is a simulation of a three-body gravitational system which illustrates periods of relative stability and then abrupt destabilization.

Three-body problem 3D from Daniel Piker on Vimeo.

ABMs permit us to model populations of interactive adaptive agents, and often the simulation produces important and representative patterns at the aggregate level. Here is an interesting predator-prey simulation on YouTube using an ABM approach by SSmithy87:

The author makes a key point at 2:15: the pattern of variation of predator and prey presented in the simulation is a well-known characteristic of predator-prey populations. (Red is predator and blue is prey.)

But the equations representing this relationship were not built into the model; instead, this characteristic pattern is generated by the model based on the simple behavioral assumptions made about prey and predators. This is a vivid demonstration of the novelty and importance of ABM simulations.

Range of reactions to realism about the social world

My recent post on realism in the social realm generated quite a bit of commentary, which I'd like to address here.

Brad Delong offered an incredulous response -- he seems to think that any form of scientific realism is ridiculous (link). He refers to the predictive success of Ptolemy's epicycles, and then says, "But just because your theory is good does not mean that the entities in your theory are "really there", whatever that might mean...." I responded on Twitter: "Delong doesn't like scientific realism -- really? Electrons, photons, curvature of space - all convenient fictions?" The position of instrumentalism is intellectually untenable, in my opinion -- the idea that scientific theories are just convenient computational devices for summarizing a range of observations. It is hard to see why we would have confidence in any complex technology depending on electricity, light, gravity, the properties of metals and semiconductors, if we didn't think that our scientific theories of these things were approximately true of real things in the world. So general rejection of scientific realism seems irrational to me. But the whole point of the post was that this reasoning doesn't extend over to the social sciences very easily; if we are to be realists about social entities, it needs to be on a different basis than the overall success of theories like Keynsianism, Marxism, or Parsonian sociology. They just aren't that successful!

There were quite a few comments (71) when Mark Thoma reposted this piece on economistsview. A number of the commentators were particularly interested in the question of the realism of economic knowledge. Daniel Hausman addresses the question of realism in economics in his article on the philosophy of economics in the Stanford Encyclopedia of Philosophy (link):

Economic methodologists have paid little attention to debates within philosophy of science between realists and anti-realists (van Fraassen 1980, Boyd 1984), because economic theories rarely postulate the existence of unobservable entities or properties, apart from variants of “everyday unobservables,” such as beliefs and desires. Methodologists have, on the other hand, vigorously debated the goals of economics, but those who argue that the ultimate goals are predictive (such as Milton Friedman) do so because of their interest in policy, not because they seek to avoid or resolve epistemological and semantic puzzles concerning references to unobservables.

Examples of economic concepts that commentators seemed to think could be interpreted realistically include concepts such as "economic disparity".  But this isn't a particularly arcane or unobservable theoretical concept. There is a lot of back-and-forth on the meaning of investment in Keynes's theory -- is it a well-defined concept? Is it a concept that can be understood realistically? The question of whether economics consists of a body of theory that might be interpreted realistically is a complicated one. Many technical economic concepts seem not to be referential; instead, they seem to be abstract concepts summarizing the results of large numbers of interactions by economic agents.

The most famous discussion of realism in economics is that offered by Milton Friedman in relation to the idea of economic rationality (Essays in Positive Economics); he doubts that economists need to assume that real economic actors do so on the basis of economic rationality. Rather, according to Friedman this is just a simplifying assumption to allow us to summarize a vast range of behavior. This is a hard position to accept, though; if agents are not making calculating choices about costs and benefits, then why should we expect a market to work in the ways our theories say it should? (Here is a good critique by Bruce Caldwell of Friedman's instrumentalism; link.)

And what about the concept of a market itself? Can we understand this concept realistically? Do markets really exist? Maybe the most we can say is something like this: there are many social settings where stuff is produced and exchanged. When exchange is solely or primarily governed by the individual self-interest of the buyers and sellers, we can say that a market exists. But we must also be careful to add that there are many different institutional and social settings where this condition is satisfied, so there is great variation across the particular "market settings" of different societies and communities. As a result, we need to be careful not to reify the concept of a market across all settings.

Michiel van Ingen made a different sort of point about my observations about social realism in his comment offered on Facebook. He thinks I am too easy on the natural sciences.

This piece strikes me as problematic. First, because physics is by no means as successful at prediction as it seems to suggest. A lot of physics is explanatorily quite powerful, but - like any other scientific discipline - can only predict in systemically closed systems. Contrasting physics with sociology and political science because the latter 'do not consist of unified deductive systems whose empirical success depends upon a derivation of distant observational consequences' is therefore unnecessarily dualistic. In addition, I'm not sure why the 'inference to the best explanation' element should be tied to predictive success as closely as it is in this piece. Inference to the best explanation is, by its very definition, perfectly applicable to EXPLANATION. And this applies across the sciences, whether 'natural' or 'social', though of course there is a significant difference between those sciences in which experimentation is plausible and helpful, and those in which it is not. This is not, by the way, the same as saying that natural sciences are experimental and social ones aren't. There are plenty of natural sciences which are largely non-experimental as well. And lest we forget, the hypothetico-deductive form of explanation DOES NOT WORK IN THE NATURAL SCIENCES EITHER!

This critique comes from the general idea that the natural sciences need a bit of debunking, in that various areas of natural science fail to live up to the positivist ideal of a precise predictive system of laws. That is fair enough; there are areas of imprecision and uncertainty in the natural sciences. But, as I responded to Delong above, the fact remains that we have a very good understanding of much of the physical realities and mechanisms that generate the phenomena we live with. Here is the response I offered Michiel:

Thank you, Michiel, for responding so thoughtfully. Your comments and qualifications about the natural sciences are correct, of course, in a number of ways. But really, I think we post-positivists need to recognize that the core areas of fundamental and classical physics, electromagnetic theory, gravitation theory, and chemistry including molecular biology, are remarkably successful in unifying, predicting, and explaining the phenomena within these domains. They are successful because extensive and mathematicized theories have been developed and extended, empirically tested, refined, and deployed to help account for new phenomena. And these theories, as big chunks, make assertions about the way nature works. This is where realism comes in: the chunks of theories about the nature of the atom, electromagnetic forces, gravitation, etc., can be understood to be approximately true of nature because otherwise we would have no way to account for the remarkable ability of these theories to handle new phenomena.

So I haven't been persuaded to change my mind about social realism as a result of these various comments. The grounds for realism about social processes, structures, and powers are different for many social sciences than for many natural sciences. We can probe quite a bit of the social world through mid-level and piecemeal research methods -- which means that we can learn quite a bit about the nature of the social world through these methods. Here is the key finding:

So it seems that we can justify being realists about class, field, habitus, market, coalition, ideology, organization, value system, ethnic identity, institution, and charisma, without relying at all on the hypothetico-deductive model of scientific knowledge upon which the "inference to the best explanation" argument depends. We can look at sociology and political science as loose ensembles of empirically informed theories and models of meso-level social processes and mechanisms, each of which is to a large degree independently verifiable. And this implies that social realism should be focused on mid-level social mechanisms and processes that can be identified in the domains of social phenomena that we have studied rather than sweeping concepts of social structures and entities.

(Sometimes social media debates give the impression of a nineteenth-century parliamentary shouting match -- which is why the Daumier drawing came to mind!)