Social resilience refers to the adaptive capacity, of a social system of any kind – from whole societies to individuals – to deal with change within their environment while maintaining and preserving critical structure and functionality. This question of social adaptation becomes increasingly significant when social change affects important aspects of life over comparatively short periods of time. Such changes include migration, changes in age, rapid industrial development, or major shifts of the population from rural to urban living that has been characteristic of the modern era. In such times of rapid and fundamental change it is the adaptive capacity of the social system that ensures the preservation of its structure and functionality over time.
Social agents operate within some environment, they are periodically subject to change within that environment, they have to deal with this change in some way in order to ensure the preservation of their function and their capacity to do that we would call their resilience. The question we are interested in then is how do they respond to that change, what strategy does the system use and there are fundamentally really just two different approaches to dealing with change. Agents can resist it, or they can adapt to it, with most eventualities involving some combination of both.
Adaptive systems typically have a specialized sub-system for regulating their behavior called a regulatory or control system, examples of this include the human brain the board or directors within a company, a national government or a military commander among many others. Regulatory systems are designed to manage the overall maintenance of the system’s structure and functionality to ensure preservation and homeostasis. All complex adaptive systems are in some way dependent upon their environment, they are what we would call thermodynamically open systems, they require the input of energy and resources in order to maintain their dynamical state, without it, they will slowly or rapidly decay. And thus the regulatory system has to ensure that the system as a whole is and will be receiving the required input values from its environment. The regulatory system then has to know what the parameters to those input values are and direct the system towards a state that will optimize them. If we are cold and there is a fire nearby we will move towards it, if we are very poor we will be driven to make money, if our economy requires a high input of oil we will try and secure that resource. These are all examples of homeostasis, where the regulatory system monitors, controls and adjusts the system as a whole so as to maintain it within the optimal set of input values required to preserve and develop its level of structure and functionality and this is the same for all complex adaptive systems.
Once the adaptive system has defined a boundary condition and becomes locked into that condition we will get inertia the resistance to change. Resistance as a strategy means the control system trying to limit the number of possible eventualities and maintain only a limited number of responses. In order to try and reduce the number of possible eventualities to some small subset that is conducive to the system we have to try and control the environment. The farther we go down this path of resistance the more we are trying to control the environment and the more we are trying to reduce the possible input values to the system. In order to properly control a system we have to linearize it, nonlinearity is uncontrollable we have to externalize it from the system, in so doing reducing diversity, reducing redundant components and by linearizing it we can increase the coupling, all of these will give increases in short-term efficiency. This leads to long-term self-organizing criticality as the system becomes more dependent upon a narrower band of input values and any small change in those critical values can create systemic shock. The classical example of this being our current dependency on petroleum where small changes in the input value can ramify across the whole system and here again this critical state was created by path dependency, a process driven by positive feedback and negative externalities as we previously saw when we talked about carbon lock-in. But this state of inertia reduces the system’s adaptive capacity and requires the heavy maintenance of a control system in order to ensure that these critical values are not altered.
Adaptation can be defined as the capacity to generate some appropriate response given some environmental change. Adaptation is essentially the opposite of resistance and control. Both resistance and adaptation are methods for maintaining the system’s structure and function. But control does so by reducing the number of input values to the system to the required type by creating boundaries and exerting some external force to alter the environment. Whereas adaptation tries to ensure that the system has the appropriate response for any given input value. Adaptation means being open to a number of different eventualities, that is to say the condition of uncertainty, and having the capacity to reconfigure the system in response to that change, without compromising critical functions.
Whereas regulatory systems will have to expend a large amount of their resources on maintaining their whole mechanism for regulation, that is to say, the means through which they amass information, define and protect boundaries, exercise control etc. Adaptation as a strategy, in contrary, is not trying to reduce the range of input values, thus it does not need to maintain all of this apparatus, meaning it can be a much more agile strategy. This strategy of adaptation is then focused on ensuring the system has a sufficient number of states to generate the appropriate one when required and ensuring the competency of these components. Whereas resistance will try to remove all disturbances, adaptation comes with a recognition of the importance of disturbance in testing the system, in order to maintain the competency of the system’s components, because without control over its environment, the diversity and effectiveness of it constituent components is the only thing that is going to ensure its preservation. As an example, we may think about how the human body develops its adaptive capacity to antigens. The immune system develops by encountering interventions from antigens, having to develop the appropriate responses and then retaining a copy of those for future application, in so doing it uses these environmental perturbations to build up resilience over time.
Slow & Fast Variables
Because of emergence complex systems like whole societies are multi-dimensional or multi-scalar, through emergence patterns develop on different levels and those patterns have their own internal processes taking place, this means that change is occurring on many different levels, from the micro to the macro and these processes of change are taking place in parallel, with smaller processes nested within larger ones. Thus in these complex social systems, there are many processes of change taking place in parallel, these macro processes of change typically take place very slowly, within ecology these are called slow variables, micro-level processes of change happen much faster and they have fast variables associated with them. Fast variables are factors that change rapidly and that are most easily measured and manipulated by managers. Regulatory systems can try to directly influence and manage the system through fast variables, such as a central bank reducing interest rates or putting liquidity into the market in order to effect the state of the system immediately. But we typically can not use centralized regulatory systems to manage macro processes of change, these things are managed through the mechanism of evolution they take place in a distributed fashion over prolonged periods of time, there is no centralized regulatory system that can really affect these slow variables. If the macro system has self-organized into a critical state there is nothing you can do about that now. You can not now affect this macro situation and the slow variables associated with it by altering fast variables. Here again, we see path dependency and again most of this can be understood in terms of positive feedback and negative externalities. These stresses on the macro level accumulate because some regulatory system on the micro-level has learned to displace a lot of its problems to its external environment – quite simply, it pushes them beyond its boundaries, but it is really just pushing them onto the macro level, distorting the process of evolution and leading to macro level self organized-criticality, that it can not effect through its fast control variables on the micro level. The system might become increasingly competent at managing everything within its boundaries, through linearization and externalizing things it cannot manage well.
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