Kuhn's (1970) description of the evolution of western science can readily be interpreted through the autopoietic-synpoietic lens. In addition, application of this poietic perspective can aid understanding post-normal science ( Funtowicz and Ravetz 1992, 1993). For those less familiar with these system concepts, another digression provides a brief introduction.

Knowledge systems can be considered as self-organizing systems arising from a variety of interacting factors involved in social systems. Such factors include many influences that arise from other emergent systems (Figure 1). More specifically, as illustrated in Figure 2, key global influences include both curiosity and the need for understanding the environment we are embedded within. Local influences include (but are not restricted to) ontological and epistemological beliefs; methods, tools and instruments; and current understanding. As different river system patterns arise from different local influences, different approaches to inquiry arise from different local influences. Positivist science is one particular approach; one attractor arising from the interacting influences. A key to understanding knowledge systems, including science, from this perspective is to recognize that they are recursive, poietic systems. As illustrated in both figures, emergent results, in turn, become global-local influences. Such feedback reinforces, and potentially isolates, particular modes of inquiry.

I have indicated on Figure 2 the group of these influences that describe a paradigm - a term which typically refers to a world view or basic set of beliefs that guides action (e.g. Thompson 1989, Guba 1990, Creswell 1994). Kuhn is perhaps best know for his use of this term, although I note that my use here does not parallel Kuhn's preferred use. The term is open to a variety of interpretations (Masterman 1970, Guba 1990) and remains a somewhat problematic concept.

Kuhn's basic thesis, garnered from a combined philosophical and historical analysis, is that science progresses through cycles: "normal science" followed by revolution followed again by normal science and then again revolution. Kuhn describes "pre-paradigm" periods prior to development of normal science. This stage is observable in the behaviour characteristic of immature sciences.

These descriptions reflect the unbounded, amorphous, characteristics of synpoietic systems. As individuals chase after particular problems and issues, gradually developing methods, models, and tools for interpreting real world phenomena, however, specific communities develop. As illustrated in Figure 2, the recursive process involves these factors and leads the system toward organizational closure which is made possible through more clearly defined paradigms. Kuhn notes Aristotle's Physica, Newton's Principia and Optiks, and Lyell's Geology as examples of works that defined the paradigms for particular sciences at particular times. Each work was "sufficiently unprecedented to attract an enduring group of adherents away from competing modes of scientific activity" and "sufficiently open-ended to leave all sorts of problems for the redefined group of practitioners to resolve" (ibid. p 10). The paradigm, then provides a seed for self-production, autopoietic style. Boundaries become self-defined by the limits of the questions asked, the models and exemplars used, the criteria determining who can 'belong' to the community, and the criteria determining what knowledge is accepted and validated. This is normal science - textbook science - which is primarily a puzzle-solving activity. "Normal science, the activity in which most scientists inevitably spend almost all their time, is predicated on the assumption that the scientific community know what the world is like" (ibid. p 5). Research proceeds as scientists ask questions, make observations, interpret answers, and develop theories, all within the context of a particular paradigm and using particular examples and models. It reinforces belief in the paradigm "by extending the knowledge of those facts that the paradigm displays as particularly revealing, by increasing the extent of the match between those facts and the paradigm's predictions, and by further articulation of the paradigm itself" (ibid. p 24).

Eventually, however, anomalies arise; "normal problems" resist solution by known procedures, or equipment designed for a particular purpose produces unexpected outcomes. "When the profession can no longer evade anomalies that subvert the existing tradition of scientific practice - then begin the extraordinary investigations that lead the profession at last to a new set of commitments, a new basis for the practice of science" (ibid. p 6). Kuhn calls these "scientific revolutions." "They are the tradition-shattering complement to the tradition-bound activity of normal science" (ibid. p 6) and involve the generation of new paradigms through more synpoietic-type techniques. During the revolutionary period boundaries are opened, leaving systems organizationally ajar, able to alter the direction of questioning, to re-interpret the same information from a new perspective, and to allow new members into the community even if they hold different norms and exemplars. This reflects re-establishment of synpoietic systems.

Normal science is an autopoietic phenomenon. Its importance, values, and dangers are manifestations of its autopoietic characteristics. It is critical, however, to recognize the importance of such autopoietic science. Organizational closure allows systems to build up high levels of complex information that would be more difficult to achieve with a continually changing organization. While autopoietic systems have their limitations, they also have advantages. Kuhn's descriptions and examples emphasize the value of autopoietic research.

However, there are also concerns.

This single paragraph provides a clue as to why Funtowicz and Ravetz (e.g. 1992, 1993) chose the term post-normal science. They argue for development and application of a more synpoietic science in specific contexts such as in situations involving high risks and uncertainties. Of particular importance they advocate opening system boundaries by expanding the peer community - making the system of science organizationally ajar by encouraging inclusion of different perspectives, types of knowledge, and validation processes. It should be noted, however, that this is encouraging a different type of synpoietic science than what occurs through the evolutionary process described. Post-normal science recognizes the value of the more reductionist autopoietic normal science in the appropriate circumstances, but emphasizes that such an approach is inadequate for coping with the values, risks, and uncertainties involved in many situations.

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