Thursday, August 4, 2011

Padgett, Part III: Autocatalysis in the Economy and in Persons

This is the third in a series dealing with one of the most interesting ideas I've come across in a decade: the theory outlined in John Padgett's The Emergence of Markets and Organizations. For an overview of the book and description of the network perspective, see Part I. Part II provides a concrete illustration of the approach, the emergence of the partnership structure in Renaissance Italy. This  post summarizes the chemical process (autocatalysis) that Padgett uses as a conceptual model for understanding the production of goods and people. This post begins with a description of autocatalytic networks in chemistry and then applies the concept to economic production and, finally, to the production of persons.



What does the network perspective imply? A shift from thinking about objects and actions to a focus on flows.
Human beings ... appear to us to be solid and sturdy objects. But viewed as chemistry, our bodies are just a complex set of biochemical reactions, which reproduce themselves over time, given appropriate inputs from other organisms. Our self-image of temporal continuity notwithstanding, we are not the coherently bounded objects that we think we are, but a chemical process that renews itself for a while. From the chemical perspective, life itself can be defined as an interacting ensemble of chemicals that reproduces itself, in the face of turnover of its parts.

Organizational actors are no different. The production and distribution of goods by firms are only half of what is accomplished in markets. Firms are also produced and transformed by the goods and people passing through them. Social structures should be viewed more as vortexes in the flow of social life than as architectural buildings. In organisms, social or biological, rules of action and patterns of interaction persist and reproduce in the face of continual turnover in component parts, be these cells, molecules, principals or agents. In the flow of people through organizations, the collectivity is not renegotiated anew. Rather, within constraints, component parts are transformed and molded into ongoing streams of action.

What is an Autocatalytic Network?

The simplest self-replicating molecular system consists of just one kind of molecule that makes copies of itself. Chemists call this kind of molecule autocatalytic—it literally brings about its own transformation. In the right chemical environment, with the right combination of smaller chemical compounds to act as food, a single autocatalytic molecule will increase in a geometrical expansion. They are able to do this because they are self-complementary. Complementary molecules fit snugly together because of their matching shapes and the arrangement of their chemical bonds. The base pairs of DNA are probably the most famous complementary pairs of molecules. 

An autocatalytic network refers not to a single self-replicating molecule but, rather, a network of several interlinked chemical processes that, taken together, are self-replicating. The best known example of an autocatalytic network is the citric acid cycle (Krebs Cycle) involved in cellular metabolism. The key elements of this process, diagrammed below, include:
  1. A positive feedback cycle of chemical reactions A->B->C->D->A in which the endproduct in the chain becomes the input into the process. In the citric acid cycle, oxaloacetate (chemical A) is combined with a two-carbon acetyl group from acetyl-CoA to produce chemical B and, following a further series of chemical transformations, until at the end of each cycle, the four-carbon oxaloacetate has been regenerated, and the cycle continues
  2. The network cycle is a network of transformation, not a network of transmission. Chemical's aren't transported from one location to another like a sack of potatos but, rather, modified at each step in the process.


Every cycle requires two kinds of input: energy (typically chemical energy) and feedstocks of building-block molecules, such as carbon dioxide, ammonia, and water. The goal in metabolism is to capture as much energy as possible and use it to make new molecules that can reinforce the cycle. The cycle must consist of a sequence of progressively larger molecules. Each molecule in the cycle combines with carbon dioxide or water or some other small molecule to make the next molecule in the cycle. The largest should be able to split into two smaller molecules, both of which are also in the cycle. By constantly building up to a larger molecule that splits in two, the number of cycles keeps doubling, and the system grows.
Abstracted from its chemical origins, autocatalysis can be defined as a set of nodes and transformations in which all nodes can be re-created through transformations among other nodes in the set. In the original biological context, nodes are chemicals, and transformations are chemical reactions.
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Given autocatalysis, reproduction can be sustained even in the face of turnover in network components: Destroy a segment of the network, and the autocatalytic network often (not always) can reconstruct its deleted segment. Self-repair is a key dynamic feature of autocatalytic sets. Autocatalysis, in other words, is the network equivalent to organic life itself. In this context, the origin-of-life problem is finding prebiotic experimental conditions under which an initial random set of chemicals can self-organize and reproduce itself into an autocatalytic set.


Autocatalytic Networks as Economic Production

Padgett then extends this concept to the realm of economic production. The result is an emphasis on production rules and product exchanges. Economies in this biochemical view are more like ecological food webs, or Leontief input-output supply and consumption chains, or an economy wide cradle-to-grave analysis, than they are like neoclassical markets.
There, products are like chemicals, and production rules are like chemical reactions. Actors are holding bins for production rules, through which products flow and are transformed. Economic “life” is the self-organization, through differential reproduction, of technological webs of production rules and product exchanges. These wend themselves through multiple surviving heterogeneous firms, thereby making those firms.
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This chemical perspective can be applied to the analysis of co-evolution of products and firms through the following analogy: Skills, like chemical reactions, are rules that transform products into other products. Products, like chemicals, are transformed by skills. Firms, like organisms, are containers of skills that transform products. Trade, like food, passes transformed products around through exchange networks, renewing skills and thereby firms in the process. In the macroeconomic aggregate, product inputs flow into, and outputs flow out of, this trading network of firms and skills. Economic ‘life’ exists if an autocatalytic network of interlinked skills and products can emerge and renew itself, in the face of continual turnover and ‘death’ in its component skills and products.
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(M)ultiple, overlapping production networks emerge spontaneously, without requiring any intervention by the experimenter. The emergence of multiple, differentiated yet partially overlapping domains of activity (the planes of figure 1), in other words, is not as hard to explain as one might think. “Domains” are sets of production rules and products that are autocatalytic. “Overlapping domains” means that some rules and products are shared. Multiple overlapping domains emerge in autocatalytic models because shared rules and products create synergistic feedbacks – both positive for stimulation and negative for regulation – between individual autocatalytic production networks. Because of such synergistic feedbacks, multiple networks that self-organize are more reproductively resilient than any one network alone.
Note the implications for understanding change:
Actor innovation or novelty is a new partition of production rules or communication protocols into organizations or people. Organizational selection occurs whenever a new partition is reproducible through product and informational feedback with other interacting organizations of rules and protocols. Organizational novelty that survives without disturbing other partitions we label an organizational innovation. Organizational novelty that tips into disrupting other partitions, which collectively find their own (modified) autocatalysis, we label a systemic invention.

Autocatalytic Networks and the Production of Persons
Padgett's conception of persons is rather unusual. Rather than render them in traditional sociological terms -- as corporeal entities with agency and embedded in structure, Padgett's autocatalytic view emphasizes production rules and communication protocols. Biological organisms are not fixed entities; they are autocatalytic networks of chemical transformations, which continually reconstruct both themselves and their physical containers.
A (social) person is the entire repertoire or set of production rules and communication protocols contained within the human being. A role is the subset of those rules and protocols used in the domain in which that person participates. Careers are sequences of roles that a person moves through in the course of his or her history of experiences within that domain. Biographies are sequences of persons that a human being moves through in the course of his or her life, in multiple domains. Relational exchange is the passage of products between rules (contained within roles). But constitutive ties or partnerships, be they economic, political or kinship, enable the passage of rules, both production and communication, between persons. Hence biographies and careers are the structured iteration of constitutive ties. To fix this idea, refer again back to figure 1. If figure 1 is a snapshot of a multiple-network system in cross-section, then careers and biographies are the temporal links that connect a series of such snapshots together into a movie.
Here is a nice illustration of the differences between the two autocatalytic levels (individual and organizational).
As one illustration of these two levels of analysis, think of science as a production network of ideas created by and flowing between theories and evidentiary procedures as production rules. Autocatalysis at this production level means whether the flow of ideas generated by the theories and evidentiary procedures is sufficient to reproduce the use of those theories and procedures. The community of scientists, at the next level of analysis, is a communication network of people who discuss and do science. Autocatalysis at this actor level entails the recruitment and transformation of sufficient people into the community to reproduce its array of scientists, in the face of turnover in personnel. Science and scientists co-evolve. To be sure, science has to work in both its internal and its external selection environments to survive. But since there are many sciences that can work, communities of scientists built around their science regulate and steer (without dictating) the development of science. Because of co-evolution between science and scientists, the evolutionary trajectory of science is neither infinitely plastic and malleable, nor predetermined and teleological. Scientific trajectories are a fan of possible futures, just like biological evolution itself.
In sum, Padgett deploys a distinctive view of traditional "social objects" -- organizations, individuals, governments, etc.
In this book, we take as our mantra: in the short run, actors create relations; in the long run, relations create actors. In the short run, all objects – physical, biological or social – appear fixed, atomic. But in the long run, on different time scales, all objects evolve, that is, they emerge, transform and disappear. To understand the genesis of objects, we argue, requires a relational and historical turn of mind. Namely, on longer time frames, transformational relations come first, and actors congeal out of iterations of such constitutive relations. If actors – organizations, people or states – are not to be assumed as given, then one must search for some deeper transformational dynamic out of which they emerge. In any application domain, without a theory of the dynamics of object construction, the scientific problem of where novelty comes from remains insolvable.
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The rub is that people die. This means that highly developed persons, upon whom the system depends, disappear. And that near empty persons come in to take their place. This implies that biographies and careers have to be structured to keep production autocatalysis going in spite of these routine disruptions. We find in our cases that uncovering the patterns of how people flow through the organizations they create, reconstructing each other through learning as they meet, is revealing for understanding both the mechanics of network reproduction (“regime stability”) and the mechanics of network tipping (“organizational invention”). The challenge is to discover how patterns of biographical and career intersection produce these observed effects.

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