Thursday, October 29, 2015

Microfoundations and causal powers

Image: Three Mile Island control room











Begin with a causal mechanism story:



Friday, October 23, 2015

Modeling organizational recruitment


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


  • grievance level
  • risk aversiveness
  • income level
  • salience of ethnicity for identity 
  • location
  • Organization-driven properties of activation
  • content of political agenda / call to action
  • perceived effectiveness
  • real effectiveness
  • number of cadres devoted to mobilization effort


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.





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.)


Friday, October 16, 2015

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 + micoolt    (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.

Thursday, October 8, 2015

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.


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.


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.


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.

Thursday, October 1, 2015

What is a morphogenic society?


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.

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?


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.


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: