In this chapter my intent is two-fold. First is to draw attention to some key human characteristics that do not appear to be commonly discussed in the systems based, environment and/or sustainability literature, but which are critical with respect to planning. Extending systems concepts into social systems without incorporating these human complexities is inadequate, although doing so makes explanation and understanding more complicated. Second is to illustrate that human social systems can be understood as poietic systems, influenced by self-organizing factors in a manner similar to that discussed above regarding physical, chemical and biological systems. Note that I am not simply suggesting self-organization provides a useful metaphor for social systems. I am suggesting that the self-organizing factors described in the preceding chapter are constitutive factors governing the generation, composition, and behaviour of human social systems.
I remind the reader, however, that this is a particular interpretation of reality based on the lenses I am describing. Through these lenses, self-organization happens. However, other lenses, presenting a different interpretation, may also be valid. The important question is the usefulness of the various perspectives for understanding any particular situation.
The increased complexity of human systems, on both individual and social levels, results from our combined mental and physical abilities. Although other species also have complex abilities including the cognitive and communicative ability necessary for social system development, "human societies are significantly different from any animal society" (Gilbert 1996, p. 7). I focus specifically on human systems, recognizing that some of the characteristics discussed may be relevant to some degree for other species.
As noted above, we cannot expect to explain or understand more specialized systems in the same manner as 'simpler,' more fundamental systems. In principle, psycho-social systems may be 'reduced' to biological interactions, which may be 'reduced' to chemical interactions, and, ultimately 'reduced,' to the fundamental laws of physics. However, as described by the evolution of complexity, systems and behaviours at each of these levels are 'special cases' of the more fundamental laws at the preceding level. Each jump in complexity therefore requires new 'special laws' for adequate explanation. The molecules in a human driving a car are not just responding to the laws of gravity and thermodynamics. They also respond to the 'laws' of metabolism, of cognition, of the road (legislated and conventional), and finally, to the personal intent of the driver. Depending on the circumstances, various combinations of these 'laws' will provide the most useful explanation of system behaviour. Potentially quite different combinations will be useful at a busy intersection in Toronto and on an icy bush road in the British Columbian 'oil patch.'
The intent here is to elucidate the 'special' considerations relevant to the self-organization of human individual and social systems. I begin by discussing the increased complexity of humans. Through application of the self-organizing factors discussed above, the consequences and implications of these complex human abilities will be discussed. I believe such application offers new insights, providing useful variations on more conventional approaches to describing social systems. The insights and variations have key implications that are especially relevant regarding planning for sustainability of the human species. The following two chapters - 4 and 5 - will consider these implications.
The last part of the second section considers the interdependence between individual and collective systems - one of the fundamental paradoxes of being human. Any understanding of human systems must recognize this interdependence - a factor highlighted by the recursive nature of these systems. I again draw attention to the importance of structural coupling as well as other key considerations relevant to understanding that arise from application of the systems concepts discussed in the previous chapter.
A number of authors discuss human, social, and cultural systems as self-organizing. The most often quoted sources within this somewhat scattered literature tend to be 'natural' rather than 'social' scientists. This literature can be loosely arranged into a few categories, although cross-fertilization occurs. A comprehensive listing of relevant literature draws away from the purpose of this thesis so I present a skeleton synopsis to provide a taste of the range of discussion. As would be expected, there are similarities and differences between my application of the self-organizing and autopoietic concepts to social systems and that of other authors.
The first category covers those authors who base their work on general systems theory. Some have followed the subsequent development and movement toward incorporating self-organizing systems theory based on Prigogine, Jantsch, Haken, etc. In a review article on "sociocybernetics," Geyer and van der Zouwen (1991) note that much of the literature appears in systems journals rather than sociology journals. Authors in this area include systems thinking sociologists (e.g. Carniero 1982, Robb 1992, 1993, deGreene 1994, Geyer and van der Zouwen 1986, 1991) as well as systems thinkers applying their understandings toward social systems (e.g. Buckley 1972, Beer 1991, Gell-Mann 1994).
A second category is work in sociology that arises from modeling and simulation. Although ultimately arising from systems theory, this work has taken a different approach, using computers to simulate complex behaviour of social systems as opposed to work in the first category which primarily relies on conceptual interpretations. It is from these types of simulation - although primarily in mathematical and computer fields - that "complexity" concepts arise. Researchers in this area include some connected to the Sante Fe Institute, such as Arthur (1992). Others include Allen (e.g. 1982, 1994), Zelney (e.g. 1977), Gilbert (1996), Nowak and Latané (see Gilbert 1996).
Another body of literature comes from application of systems methodology - a more pragmatic approach than the theoretical orientation of those noted above. Popular here is the soft systems methodology developed by Checkland (1986, Checkland and Scholes 1990). More recent developments include critical systems thinking (Midgeley 1994, 1996, Flood 1996). There are also some interesting applications in management and organization theory (e.g. Leifer 1989, Senge 1990).
The fourth, loosely described category, research in the social sciences based on autopoiesis, has been important to my research. Mingers (1995) provides a review source here. Perhaps most comprehensive is the work of Niklas Luhmann (e.g. 1986, 1997), ranked as an important German social theorist (Geyer and van der Zouwen 1991, Paterson 1997). Since Luhmann's work, however, is both 'difficult' and has rarely been translated into English, it has received little attention (Paterson 1997). Others working in this area include Zelney (e.g. 1977, 1980), Bednarz (e.g. 1988), Burghgraeve (1992), Krippendorf (1987), and Kickert (1993). A forum regarding the validity of applying autopoiesis to social systems was published in International Journal of General Systems (Fleishaker 1992),*1 and there have been at least two edited volumes covering implications of autopoiesis for a variety of system types, including social systems (Roth and Schwegler 1981, Zeleny 1980).
There is also a scattering of self-organizing systems application to be found in psychology, family therapy, cultural evolution, political science and more.
Finally, there is another body of literature I will refer to in Chapters 4 and 5 which deals with suggestions for coping with complex systems, using an approach that is based on complex systems. This approach parallels the one taken in this thesis. Literature of this type is found in such disparate disciplines as the aforementioned management and organizational theory, as well as ecology and natural resources management (e.g. Slocombe 1993, 1995, Westley 1995, Holling 1995).
Discussion in the current chapter has benefited greatly from this somewhat sparse, sporadic literature, but an equal, if not more important source has been general psychological and social literature. Since my objective has been to provide evidence for the existence of sympoietic systems in order to apply the concept to critique planning, this body of literature that has been useful. It has been valuable to be able to interpret general psychological and social research from a sympoietic systems perspective with relative ease. Key sources, in this area have been textbooks, especially Myers (1993), Smith (1993), Spencer (1993), and Tepperman and Richardson (1991). As Spencer (1993, p v) states: "a textbook writer is not expected to innovate so much as to select from and accurately report on the innovations of other scholars." I have relied on such 'reporting,' since it typically relates generally accepted understandings - peer reviewed concepts rather than unusual and individualistic ideas.
In addition to reliance on the literature, some of the discussion in this chapter appeals directly to simple and general observational evidence. For example, people think, people interact. I keep such appeals to a minimum, however, since many commonly held 'truths' do not match empirical data (see e.g. Myers 1993, Spencer 1993). Many complications arise. For example, although people do act based on conceptions of the future, the reasons for their actions are not as straightforward as 'common sense' might suggest.
I am in full agreement with the old adage, "a little knowledge is a dangerous thing." Yet to draw the essential linkages across disciplines at the depth possible here, I must count upon the little knowledge I have gained through wide, rather than detailed, reading. The corollary of cross-disciplinary work is the need to cross disciplines. I therefore emphasize that the following discussion must be recognized as illustrative rather than comprehensive.
As biophysical individuals, humans could be described using the systems concepts introduced in the preceding chapter, although such description would be as inadequate as it is for describing other biological systems. To consider human individuals and collectives, using only the characteristics described above, however, without acknowledging their increased complexity, would be particularly abstruse. Since the intricacies and implications of human complexity *2 extend far beyond what can possibly be touched on here, I simplify considerations by keeping to those I believe are most relevant to planning for sustainability.
I consider two aspects of increased complexity illustrated by the split along the evolutionary temporal continuum illustrated in Figure 2.6. First, human systems have a more complex pattern of organization on an individual biophysical level. Second, human systems participate in a new pattern of organization, the social group - an aggregate of individual systems. As with the description of river systems and Bénard cells, and noted in the description of the evolution of complexity, each jump in complexity results from the imposition of new constraints through interaction of global-local influences, positive feedback, and other self-organizing factors. Each new increase in complexity provides, in turn, the opportunity for new, more complex patterns of organization to emerge. The purpose is to explore these new organizations.
The following sections on mental abilities and social organization are areas in which direct citation is difficult - most of the discussion is very basic and covered by many authors. Nonetheless, I have benefited from the insights of several authors - perhaps more for creating particular patterns of thought than for the specifics of their research. (This too is a self-organizing process.) In particular I credit: Boulding (1957), Campbell (1982), Campbell (1985), Csányi (1989), Krippendorf (1987), Pezzey (1992), Mainzer (1994), and Myers (1993). Specific examples and insights are individually referenced, however, the general discussion can be found in these works or in the general texts noted above.
Evolution of complexity on an individual level involves generation of increasingly more complicated biophysical autopoietic systems. In humans this has led to two interconnected types of abilities. First is dexterity, which I use as a general term to refer to fine-tuned physical capabilities such as the celebrated human thumb and vocal chords. Second is mentality, which I use as a general term to refer to the sensing, thinking, feeling abilities that arise from increased potential of the human brain. Although the latter jump in complexity has significant implications and is given much credit for human achievements, it is the combination that is critical. Tool making requires intelligence and thumbs; communication is complex with memory and vocal chords; intentional action is more precise and directed with thinking and fine motor control. Having noted this important detail, however, I restrict discussion in this thesis to the mental dimension.*3
Further detail is beyond this thesis, but I believe this conceptualization allows general recognition of the interplay of factors involved in thinking, feeling, and action. Figure 3.1 in particular, provides a heuristic that emphasizes recursion and balancing elements. It precludes continued single-causal focus illustrated by proponents of biological (e.g. Dawkins 1976, Wilson 1980) or behavioural (e.g. Skinner 1977) determinism. Such a heuristic is especially useful when trying to consider the possibility of altering behaviour - a key concern in planning for sustainability.
As with the pattern of organization of other systems, that of a human psyche will be manifest in many different structures. However, these will be psychological structures as opposed to the physical ones that were discussed in the previous chapter. This difference suggests possible differences in system characteristics and behaviours. As noted regarding preceding examples, the presence of physical structures places limitations on change. Such structures must obey the basic laws of physics and other rules or laws imposed by life. These limitations are implied by the notion of structural coupling. In psychological systems, however, these limitations will not necessarily be the same. I believe, however, that structural coupling is still relevant, tempering the possibilities for unlimited change. Each psychological structure will be coupled to the particular psycho-social context it is embedded within. I will re-emphasize and expand on this notion below.
Since human systems are more complex, connections must be recognized on two levels: coupling on a psychological level to a social system and also a direct physical connection to the individual biophysical system from which it emerges (Figure 3.3). As illustrated in Figure 3.3 and as discussed in the preceding chapter, the biophysical system, in turn, is structurally coupled to its environment. A third coupling is also noted, between society and environment. I will emphasize this connection in the section on social systems below.
Considering the three-fold purpose of this thesis - to develop the concept of sympoiesis, apply it to critique planning, and suggest possible directions - I note several important human characteristics that arise from our mental capabilities. These do not represent a comprehensive account of human complexity, but rather draw attention to aspects critical for the discussion. I emphasize that these characteristics are recursively and causally connected: no particular characteristic can be considered as the cause, for they are mutually influential.
Given these characteristics, and reconsidering our position as biophysical autopoietic entities dependent on particular biophysical sympoietic systems, the touted advantage of our complex human abilities should be re-evaluated. The irony is that these abilities both reduce and enhance uncertainty with respect to the environment and our ability to respond appropriately. With regard to planning for sustainability, complex human characteristics both increase and decrease the potential for coping with uncertainty and for predicting future system states and impacts. I return to consider the implications of these complex characteristics when developing criteria for evaluating planning systems (Section 5.2.1).
To say society is a system implies that group actions have results that cannot be explained in terms of the intentions of their individual members (Spencer 1993, p 5).
Individual human actions do not occur in isolation, but within integrated networks of individuals - social systems. By social system I refer to systems composed of psychologically, socially, and/or culturally defined entities and relations, rather than biophysical ones. For example, rather than physical entities, social system components are cognitive images of physical entities, rather than biophysical individuals, components are socially defined roles held by these individuals. Such description is not without precedent. Of particular interest here is the comment by Bednarz (1988) that much of the confusion regarding the application of autopoiesis to social systems (e.g. Fleischaker 1992) is due to a lack of recognition that social system components must be identified within the social domain. In a review of sociocybernetics, Geyer and van der Zouwen (1991) note that actors and communications (conceptual, rather than biophysical elements) are two of the common components used in discussing social systems.
After making such a distinction, however, it is critical to recognize three points. First, as noted in the opening chapter, one of my basic assumptions is that psycho-socially defined entities depend on the existence of biophysical entities. Second, in many cases, psycho-socially defined entities and biophysical entities are inextricably entwined. Recognition of such interconnections is essential. For example, the ties between socially defined roles and the biophysical individuals that hold them are very tight although the roles may be held by many different individuals. When considering a small group as a system it may be difficult to separate "leader" and "member" from the specific persons holding these positions. In contrast, it is simple to speak of language as a system without reference to biophysical entities, even though the latter are essential for language to occur. Third, our interface with society, other individuals, and our environment is, at least for the most part, mediated through the physical environment. Thoughts and feelings are communicated through sound waves and subtle body language; symbolic information is recorded on paper or in computers; environmental ethics materialize through creation of protected areas, and morals through legal systems. Because of these points, I initially use this distinction to consider some human complexities and then use poietic system conceptualization as a means of integrating the social and biophysical domains. While I believe a distinction between the two is useful for understanding, their integration is imperative for coping with the difficulties that arise from their separation. We have relied too long on the latter. The critical role of individual humans as linkages between biophysical and social systems is essential to recognize, understand, and address.
While the complex aspects of human psychology noted above are important, to consider them alone (just as to consider biological aspects alone) provides a woefully incomplete and inadequate conception of humans. Social systems arise from the basic, communicative exchanges and interactions among cognitive (or at least communicative) individuals. They also occur among other species such as wolves and bees. In our species, however, due to the complexities just discussed, human social systems involve significantly more complex qualities than other species.
Consider emergence of very basic, early social systems through the recursive, self-organization process illustrated in Figure 3.4. The key global influence would have been sustenance: obtaining sufficient biophysical inputs necessary for maintaining autopoiesis of individual humans. Local influences include individual abilities (e.g. strength, speed, planning, tool-making), and landscape features (e.g. open terrain, vegetation, waterholes). These interactions generate particular structures - social groups and, in turn, generate further global influences - communication and cooperation. Further interactions lead to the generation of new structures and new global influences. The diagram should not be interpreted as suggesting a linear causal progression. Feedback influences from emerging structures actually become local influences in preceding processes. Recursion is critical. These are cybernetic systems: "effects" become "causes." For example, the need for communication arises from the development of social groups, but development of social groups depends on the possibility of communication. Figure 3.5 emphasizes this interactive process, focusing especially on knowledge systems which will be isolated as a key aspect of planning.
The emergent and recursive patterns arising from such basic elements illustrated in these diagrams seem distant from our 'progressive' modern societies, but I believe these constitutive factors are as relevant today as they ever were. We have just buried the basic factors under more obvious, daily concerns of quite a different character. Sustenance is still a global influence and the local influences mentioned are still relevant - our current western industrialized society is just on a dramatically different attractor than the original human social systems. As noted in Chapter 1, however, we still depend on six inches of topsoil and the fact that it rains. We also require cooperation and communication. In our 'advanced' society the need for the latter two have become ever greater - and more complex, but they have not eliminated the former two. This illustrates presence of the ratchet effect again. As noted regarding conceptualization of human psyches, these system descriptions make it possible to understand social systems in a different manner. They offer some new possibilities to aid understanding. The conceptualization emphasizes the underlying global influences operating in these systems, and also their recursive nature. I believe both are neglected qualities. Second, it provides some potential for considering the implications of, and possibilities for, change on many levels. Finally, it is different. As such, it provides the potential for 'seeing' new things.
I re-iterate the point noted in Section 1.2.3, that my focus in this thesis is western industrialized scientific culture. These concepts could be applied to any culture and may provide useful lenses for making cross-cultural comparisons, such as considering the different characteristics of individualist and collectivist cultures. The discussion on social systems articulated in the current chapter and in the following chapters on planning is based on western culture.
Every holon has a dual tendency to preserve and assert its individuality as a quasi autonomous whole; and to function as an integrated part of (an existing or evolving) larger whole. This polarity between the self-assertive and integrative tendencies is inherent in the concept of hierarchic order; and a universal characteristic of life. The self-assertive tendencies are the dynamic expression of holon wholeness, the integrative tendencies of its partness. (Koestler 1967, p 343)
To fully understand both individual and social systems, it is essential to consider their inter-relations. The complex individual human characteristics described in the previous section did not arise fully developed in individuals ready to participate in social systems. The characteristics evolved through recursive reinforcement involved in, and required by, social interaction. On a biophysical level, as with trees in forests, there is a mutual interdependence between individual autopoietic organisms and the sympoietic systems they are embedded within. This paradox of interdependence is still valid on a psycho-social level. As with biophysical systems, there is a mutually interdependent linkage between individual and collective.
While it would be a truism to state that ultimately all decisions are made by individuals and that all interactions with the biophysical environment occur through individual actions, it would - realistically - be quite false. Individuals are influenced by the social systems they are embedded within. Even though the psychological factors listed above are 'individual' causes they involve social influences since each individual operates within, and is structurally coupled to, a social context.
To emphasize this coupling, I draw attention to various social factors that affect individual choices described by Cialdini (1993). (See also Myers 1993.) Cialdini describes six basic categories, each "governed by a fundamental psychological principle that directs human behaviour" (1993, p. xiv). The six principles are listed in Box 3.1. Each of these principles influence individual behaviour in a manner that sometimes generates unexpected results. Cialdini describes many examples, illustrating both subtle and extreme cases. While the degree of influence will vary by situation and by individual, these influences are ubiquitous and reflect a structural coupling mechanism between an individual and their social context.
Research on the linkage between attitude and behaviour also indicates non-linear associations. The standard assumption is that our knowledge and understanding will shape our attitudes and that these, in turn, will shape our behaviours. These linkages, however, are much less straightforward (Jones 1996, Myers 1993, Smith 1993). People who start and/or continue smoking despite knowledge that it is an unhealthy habit and despite continued protestations of wanting to quit provide a ubiquitous example. The problem of addiction does not explain away those who start smoking despite knowledge of its ill effects.
Actual behaviours are a result of attitudes regarding the behaviours themselves, our perception of how others want us to behave, and our perception about our ability to behave (Myers 1993, Ajzen in Jones 1996). In addition, Myers includes recognition that behaviours can influence attitudes as well, a notion illustrated by the feedback loop in Figure 3.1. The linkage between attitude and behaviour illustrates another manner in which individuals are connected to their social context.
To consider social system behaviour, however, it is imperative to recognize the presence of emergence: systems are 'wholes that are greater than the sums of their parts.' As with other creative self-organizing systems, random elements are constrained into particular patterns and arrangements. The self-organizing factors involved generate a new set of relations among the components. This occurs whether the components are water molecules as in Bénard cells, complex molecules as in living systems, or individuals as in social systems. The resulting systems cannot be understood as composite wholes without recognizing the complexity and non-trivial nature of their components, or by statistical analysis of their parts. We must attempt to understand them by recognizing their self-organizing and recursive influences and by acknowledging the paradox of interdependence.
In the systems discussed in the previous chapter, global influences were provided by fundamental physical and biological 'laws': gravity, entropy, life. These factors are still relevant in human systems. However, as Figure 3.4 showed, in these more complex systems outcomes become influences. In addition, the role of information becomes increasingly important. It is here that the ratchet effect becomes critical, for it creates potentially ever increasing degrees of complexity in social systems.
In addition, social systems become more complex because the opportunities offered by complex human abilities can be created intentionally through social contracts. These can constrain relations among components either through 'un-written' rules that guide our interactions with others such as the social influences just described, and/or through written policies, laws, regulations, and other formally established social norms. Presence of such 'laws' does not imply that all components 'obey' them in a straightforward manner. Given the appropriate counteracting influences, even water molecules defy the pull of gravity. Clouds provide sufficient evidence. Yet even here, particular structures are created by the organizing factors involved. Gravity is one of those factors, even though it is not the over-riding influence.
To fully understand the emergent structures - in clouds or social systems - it is critical to understand all the interacting factors. Such understanding is not possible in social systems for three reasons.
As I have indicated previously, the intention in this chapter is not to fully explain the complexities of human systems, but rather to provide some indication of their degree of complexity. In addition, I wish to illustrate the potential for developing improved understanding by mapping some of these considerations onto the self-organizing and poietic systems concepts. I re-emphasize that I do not attempt to negate other perspectives but to present an alternative. I also emphasize that self-organizing and/or poietic systems concepts cannot help explain social systems without inclusion of the complex human abilities noted in this chapter.
There may be a tendency to accept these considerations as a metaphor for the processes occurring in social systems. The vision of our society moving along like a big river with hidden undercurrents, and an inexorable direction, heading into a questionable future, fits with an image drawn by many. The river is a metaphor - but it is a metaphor for the processes that are occurring in society. Self-organization happens. The characteristics I describe are system properties - they are factors and consequences relevant for any system. Recognition of our mental abilities, which are further enhanced by social interactions, complicates these characteristics and the processes generating them, but does not eliminate or negate them.
I have tended to believe sympoietic systems to be inherently better - more open, cooperative, shared rather than centralized control, adaptable - all desirable qualities to my mind.*6 I did this especially when I considered them as a metaphor for social systems. Deeper investigation into the factors governing these systems, their characteristics, and their behaviours, as well as application of these lenses to perceive the system types that actually exist in social systems corrected my initial tendency. "Better" is totally dependent on context and purpose. Each system type has both advantages and disadvantages - and the paradox of interdependence illustrates their mutual dependence on each other. The complexity of autopoietic systems is possible because they are embedded within sympoietic systems. The complexity of sympoietic systems is possible because they are formed from complex autopoietic components. Inclusion of complex human characteristics expands on these interdependencies and on the complexities. All of these factors must be incorporated into planning considerations.
To consider application of these systems concepts in more detail, I describe three examples - small group dynamics, the evolution of science from a Kuhnian perspective, and the social systems of concern to Point Pelee National Park. The examples are chosen for their diversity, familiarity, and ease of explanation. In addition, they will be of value in explaining the implications of these systems concepts for planning - the subject of the following two chapters.
Considering small groups as systems provides an example with a few advantages. Rather than an abstract concept such as 'social systems,' they provide a more tangible, observable reality that most of us have experienced. These examples are simple enough for us to grasp factors influencing their behaviour, yet complex enough to exhibit surprising behaviour. A reasonable amount of empirical research is available to aid in our understanding. In addition, recognition of the wide variety of small groups that can emerge allows for some comparison of factors generating different system attractors. Finally, due to the growth in community based planning and shared decision-making, many people - planners and participants alike - will benefit from a heuristic to aid in understanding how such groups work. However, the idealistic nature of the system concepts, and consequently, of the small group characterizations I describe must be kept in mind.
Since there are many different types of small groups, I focus the discussion by considering relatively short-term task-oriented groups, although I believe interpreting other small groups through poietic systems lenses would be interesting. Fleishaker (1992) and Mingers (1995), for example, discuss families as autopoietic systems. Mintzberg and Westley (1992) and Stacey (1995) discuss organizations with parallel ideas that may provide a fruitful synthesis.
I begin by noting the complex characteristics of small groups, followed by their self-organizing and poietic characteristics. The question is: what makes a 'small group' something more than just a collection of people? What is the difference between several unrelated people riding in an elevator, or standing in a grocery store line up, and a work group gathered together for a particular task, or a group of friends gathered for a birthday? More importantly, when such groups are cohesive and/or high functioning, what are the factors involved? Related to the purpose of testing the concept of sympoiesis, two further interconnected questions arise. Do the descriptions of small groups in the literature reflect the factors I have described to explain self-organizing and poietic systems? Can they be used to explain the fact of 'emergence' in small groups?
General references for this section include Shaw (1981), Larson and LaFasto (1989), Myers (1993), Spencer (1993), and Barker et al. (1995).
Cohesion is a key characteristic commonly used to express the level of 'small-groupness' about a collective. Shaw (1981) describes cohesion as "the resultant of all the forces acting on the members to remain in the group," including the number, strengths and interpersonal attractions within the group. These, then, represent different self-organizing influences. Barker et al. (1995) states that cohesion can be viewed as a continuum. At the high end, cohesion has a positive influence on other aspects of small group behaviour. It is interesting to note, however, that empirical evidence suggests that high effectiveness or high productivity in task completion does not necessarily correlate to high cohesiveness (Myers 1993, Barker et al. 1995). This suggests that cohesion is both an influencing factor and a result - a combination typical of recursive self-organizing systems.
Since groups are typically composed of individuals who share a common language and have relatively similar norms, redundancy is present. The increased difficulty of achieving cohesiveness in a cross-cultural group (Spencer 1993) or among different interest groups at a round-table illustrate the value of such similarities (Brunton and Howlett 1992, CORE 1992). In addition, Cialdini (1993) argues that the six principles of social influence are universal, although they carry different degrees of expression among individuals. These influences, then, also ensure a level of redundancy. As noted above, however, redundancy is another, enough-but-not-too-much characteristic: too much similarity in not an advantage, as is noted below in discussion of 'groupthink.'
The potential for emergent behaviour in a small group is augmented by the complexity of their components. Individual abilities, experiences, and personalities such as the psychological characteristics identified above will be influential. This aspect of small groups was treated more lightly than I expected in the readings. Individual members were often treated as black boxes, rather than as complex systems with internal feedback and consequent unpredictable behaviours.
In contrast to such spontaneous formation, other groups, are intentionally formed for specific tasks. With respect to such groups, researchers observing stages in their development have noted two key shifts that occur in parallel. The first is from individual concerns to group concerns, the second, from interpersonal relations to task orientation. The relative importance and duration of these shifts will be task and group specific. Figure 3.6 illustrates these and some of the other characteristics described as relevant to the effectiveness and cohesion of small groups. The effectiveness of a small group depends on maintaining a critical balance between all the various factors (Larson and LaFasto 1989, Barker et al. 1995), a description which fits with the discussion on points of tension in Chapter 2. Not all small groups 'survive,' and of those that do, only some attain high levels of cohesion, effectiveness and performance (Larson and LaFasto 1989, Barker et al. 1995).
It is important to recognize members of small groups as non-trivial systems. Each individual personality is an emergent structure arising from the factors noted in Figure 3.1 above. In addition, it is important to note holarchical issues here - individuals will likely be members of more than one small group or social system. Social influences external to the small groups may also be relevant.
To use leadership as an example, different small group attractors can be described by matching leadership style with group type (Figure 3.7). Inappropriate matching is less likely to generate emergence. Replacing one leader with another who has a different leadership style, or a person with the same expertise but a different personality, can often create difficulties associated with internal functioning of the group or with external linkages. The resulting group may struggle along as a collective, but it may not demonstrate the highly cohesive, high functioning characteristics of a 'small group.' Of course, replacing one leader with a more appropriate match may improve a groups' functioning.
As with other self-organizing systems discussed previously, the interacting influences relevant to generating a small group can be understood as a rule set describing the relations among components that establish a system as a system. Such a rule set equates to the system's pattern of organization. The various possible system structures are represented by the different attractors. These groups will be structurally coupled to their context through social influences and other factors, and will carry varying degrees of organizational closure. Hence, they can exist anywhere on the autopoietic-sympoietic continuum. The benefits and disbenefits of the respective positions will depend on the situation involved, including the reason for, and task of, the group. An emergency response team in the field must be somewhat sympoietic, prepared for unexpected organizational changes; a surgical team needs to be more autopoietic.
Another example relevant to planning and management can illustrate the differences between the autopoietic and sympoietic characteristics of small groups. Consider the differences between a small expert-driven task force and a broader based small group of representatives from various public interest groups such as a round-table. In the former situation, the group receives a 'packaged' pattern of organization - a terms of reference which outlines specific objectives, roles, tasks, and time frames. Although such a group will rely on gathering substantive information related to the task from external sources, the organizational information regarding functional relationships within the group will be self-contained. In addition, the group's interpretation of the organizational information will result in self-defined boundaries. As a group they will be developmentally focused, attempting to maintain a homeostatic balance, and will have a relatively predictable and finite trajectory - all of which are autopoietic characteristics.
In contrast, a more open process designed to generate public opinion and exchange knowledge regarding particular issues is more accurately interpreted as sympoietic. Since group members must act as representatives, information will be varied and distributed among the members and even beyond. The pattern of organization may have to change as new interest groups or new types of relevant knowledge are identified. Significance of the relationships different interest groups hold with respect to the process will depend on their perception of the issue under consideration, which will evolve as the process continues. These characteristics exhibit the dynamic balance and unpredictable nature of sympoietic systems.
The notion of 'groupthink' (Janis 1982, Myers 1993, Barker et al. 1995) illustrates the potentially negative consequences of autopoietic characteristics in inappropriate circumstances. In these groups, role definition and norms are too internalized; commitment is too high; communication, though seemingly open is actually quite closed; rather than allowing healthy conflict, agreement is total; external focus is lost; and evaluation is totally internal. Janis (1982) describes the effect these characteristics have had on high level political decisions that have later been recognized as disastrous. In such situations, group members became inward-looking to such an extreme that they were incapable of receiving important external information. Such exclusively internal focus limits the ability to adapt to changing circumstances.
These descriptions of different types of small groups illustrate application of the self-organizing and poietic systems concepts. Such discussions suggest the possibility for designing small groups to match circumstances, a consideration I will return to in Chapters 4 and 5 on planning. In addition, the characteristics themselves are particularly relevant for developing systems - especially with respect to consensus-based planning processes.
Figure 3.8 illustrates the heuristic possibilities offered by the poietic system perspective, noting positions of the last three types of small groups discussed on a continuum of autopoietic-sympoietic characteristics.
Another social system example that can readily be interpreted through the autopoietic-sympoietic lens is Kuhn's (1970) description of the progress of western science.*8 As well as providing an example of the two system types in the social domain, application of the poietic perspective aids understanding of Kuhn's interpretation of western science and also of post-normal science as articulated by Funtowicz and Ravetz (e.g. 1992, 1993). In addition, these descriptions are relevant to understanding planning because science - and other types of knowledge - play an important role in planning.
Figure 3.4 above illustrated the emergence of knowledge systems from a variety of self-organizing factors. More specifically, and simplistically, 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 (Figure 3.9). As different river system patterns arise from different local influences, different approaches to inquiry arise from different local influences.
As illustrated in Figure 3.9, science is one particular type of knowledge system that emerges; one attractor arising from the interacting influences. A key to understanding science (or other knowledge systems) from this perspective is to recognize that they are recursive, poietic systems. As illustrated in Figure 3.9, emergent results, in turn, become global-local influences. Such positive feedback reinforces, and potentially isolates, particular modes of inquiry.
I have indicated on the illustration those influences that describe a paradigm. The term typically refers to a world-view or basic set of beliefs that guides action (e.g. Thompson 1989, Guba 1990, Creswell 1994). Box 3.2 provides further comment on the contentious and ambiguous use of paradigm.
Kuhn's basic thesis, garnered from a combined philosophical and historical analysis, was that science progresses through cycles: "normal science" followed by revolution followed again by normal science and then again revolution. Kuhn described "pre-paradigm" periods prior to development of normal science. This stage is observable in the behaviour characteristic of immature sciences, noted as relevant to the current situation with respect to self-organizing systems understanding.
In the absence of a paradigm or some candidate for paradigm, all of the facts that could possibly pertain to the development of a given science are likely to seem equally relevant. As a result, early fact-gathering is a far more nearly random activity than the one that subsequent scientific development makes familiar. (Kuhn 1970, p 15)
These descriptions reflect the unbounded, amorphous, characteristics of sympoietic systems. As individuals chase after particular problems and issues, gradually developing methods, models, and tools for interpreting real world phenomena, specific communities develop. As illustrated in Figure 3.9, the recursive process involves these factors, leading the system toward organizational closure, made possible through more clearly defined paradigms. Kuhn noted 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 sympoietic-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 sympoietic 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. As described above regarding the evolution of life (Section 2.3.2), 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.
When the individual scientist can take a paradigm for granted, he need no longer, in his major works, attempt to build his field anew, starting from first principles and justifying each concept introduced. That can be left to the writer of textbooks. Given a textbook, however, the creative scientist can begin his research where it leaves off and thus concentrate exclusively upon the subtlest and most esoteric aspects of the natural phenomena that concern his group. (Kuhn 1970, p 20)
[The] restrictions, born from confidence in a paradigm, turn out to be essential to the development of science. (Kuhn 1970, p 24, and also see p 17, 20, 34)
However, there are also concerns.
A paradigm can, for that matter, even insulate the community from those socially important problems that are not reducible to the puzzle form, because they cannot be stated in terms of the conceptual and instrumental tools the paradigm supplies. Such problems can be a distraction, a lesson brilliantly illustrated by several facets of seventeenth-century Baconianism and by some of the contemporary social sciences. One of the reasons why normal science seems to progress so rapidly is that its practitioners concentrate on problems that only their own lack of ingenuity should keep them from solving. (Kuhn 1970, p 37)
This single paragraph provides a clue as to why Funtowicz and Ravetz (e.g. 1992, 1993) chose the term post-normal science.*9 They argue for development and application of a more sympoietic 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 encourages a different type of sympoietic science than what occurs through the evolutionary process described - a point I will return to in Chapter 5. Figure 3.10 illustrates how Funtowicz and Ravetz relate post-normal science to normal science. They perceive that the two can occur simultaneously, but must be applied in different situations. Post-normal science recognizes the value of the more reductionist autopoietic normal science in appropriate circumstances. The point is simply that such an approach is inadequate for coping with the values, risks, and uncertainties involved in many situations.
As noted at the beginning of this section, science is only one type of knowledge system. Some authors note the universal nature of the process of inquiry, although still primarily referring to western cultures (e.g. Wenz 1988, Bontekoe 1994). Application of Kuhn's interpretation and of the systems concepts described here to other knowledge systems would be an interesting area for future research.
I apply the systems concepts to a third and final example: the social systems influencing the geophysical system at Point Pelee National Park in southern Ontario. A more in-depth discussion of this example can be found in Dempster (1997). Here I draw on that work to provide an example that reflects some of the difficulties presented in many situations involving the interaction between natural and social systems. In addition, this conceptualization will be used in the planning chapters to demonstrate application of the systems concepts to planning. In this case, the national park represents such a small component of the landscape, so consideration of factors external to the park are especially important to understand in order to plan appropriately.
Figure 3.11 (after Bolsenga and Herdendorf 1993) illustrates the park and two key factors involved in generation of the sandspit which forms the physical basis for the park. Situated on an underwater moraine, the sandspit results from sediment deposition (Figure 3.12) caused by the moraine slowing down along-shore currents, carrying sediment loads. Such interactions could lead to a relatively static structure: solid land. At Point Pelee, however, the system is dynamic, and includes the sandspit and a marsh which forms a large part of the peninsula. At times, high lake levels and storm events cause erosion of the sand barrier (Battin and Nelson 1978, Herdendorf 1992), and when the sediment load of the current is reduced, deposition rates decrease (Parks Canada 1991). Biological components of the marsh can also have an influence, for example by stabilizing sediment with their root systems (Guntenspergen 1985, Herdendorf 1992).
There are actually many different influences generating the sandspit at Point Pelee (Figure 3.13). These can be understood by considering their effect on the two key processes generating the peninsula: erosion and deposition. When poised at a critical intermediate point, the counteracting processes create and maintain the peninsula and marsh. Figure 3.14 illustrates these interactions diagrammatically, using a representation similar to the ones used above for self-organizing systems, and indicating the point of tension from which the system emerges.
The social systems influencing the geophysical processes at Point Pelee are complex and interconnected. They involve a wide variety of interactions ranging from economic transactions, to interpersonal relations, and from family to national interests. Some aspects of these social systems have been formally codified into legal, political, educational and other institutional structures. Others are less formal, although not less influential, and include the set of underlying norms, beliefs, morals, and values shared among members of the social system.
One of the issues of concern to the park is the alteration of deposition rates as a result of shoreline protection. The full range of relevant social aspects is considerable, even when reducing considerations to cover only those relevant to creating the hardened shoreline which has a negative impact on Point Pelee National Park. The aspects presented here must, therefore, be taken as illustrative, not comprehensive. Characterization of social systems described here is gathered from a general understanding of social systems and comments specific to Point Pelee from Battin and Nelson (1978), Bolsenga and Herdendorf (1993), and Kreutzwiser (1993).
Note that, in Figure 3.16, the influence of 'regulations' is drawn with a disconnected double-headed arrow. This is to indicate that regulation and other government policies can have varying, and conflicting, effects. Kreutzwiser (1993, p 31) indicates the "regulatory complexity" involved in the area around Point Pelee. Two further illustrations conceptualizing the institutional and regulatory influences would be valuable for a more comprehensive understanding of the issues at play.
The formative influence of positive feedback must also be recognized, although it is not indicated on Figure 3.16 as it was on previous systems diagrams. In Figure 3.15, however, the role of fear is shown to involve a feedback loop: interventions can exacerbate rather that alleviate the problems. Initially triggered by high lake levels, fear encourages hazard management, which creates further erosion problems, which in turn increases the fear and subsequently increases intervention.
In addition, it is essential to realize the interconnected nature, and especially the variable weighting, among the various influences. Some influences will have a greater effect on actions. As I noted in Chapter 3, Jones (1996) draws attention to the value of attitude research for planners. She points out that it is especially relevant regarding sustainability issues and the standard informational approach used for changing behaviour. As is noted earlier, the standard assumption that our knowledge and understanding shapes our attitudes and behaviours may be made in error (Jones 1996, Myers 1993, Smith 1993). Considering the factors noted in the Point Pelee example, property owners may have an attitude which reflects a high level of environmental concern and be fully cognizant of the influence of a hardened shoreline on the sand budget of the park. Yet these factors may have little effect when storm events at high lake levels threaten to wash away their own beach. Actions of others may also have an influence. For example, an owner surrounded by others who are erecting barriers, may feel they can do 'nothing but' erect a barrier themselves despite 'knowing' that it is not in the park's best interest. They may do this either for their own protection or because of a perception that neighbours will react negatively to inaction. These, other social influences, and other factors discussed in Section 3.2.3 on the paradox of interdependence, are also relevant here.
The example of pattern generation among iron rods (Figure 2.8c) is again useful for understanding. If the plastic rod was taken as a property owner with a low level of concern for the environment (or high concern for property etc.), and if the role of social influence, positive feedback, and intentional action is recognized, the potential for a small trigger - that owner building protection - to turn into a global influence can be noted. The plastic rod encourages another to change its position, the pair, then have a wider influence, changing more and so on. This is especially relevant in human systems where 'effects' can become 'causes.' The point of tension now manifests as a 'hardened' shoreline (Kreutzwiser 1993) - an emergent property of the social system existing in the region. As illustrated in Figure 3.16, this is a change from the 'natural' level of shoreline erodability. The system is settling into a new attractor.
An additional point to recognize in this situation is that initial protection was likely put in place in ignorance of the potentially negative consequences. Feedback influences such as the fear noted above, however, mean that the ratchet effect becomes critical. Once protection is in place, it becomes hard to remove. Further, once particular behaviours and beliefs are in place, they are hard to change (Myers 1993).
*1 Unfortunately, however, the papers in this forum represent the worst cases I have read of personal invective: many authors took more space for personal attacks on other authors than for intellectual debate.
*2 I re-emphasize recognition that complexity is a somewhat subjective concept depending on our ability to comprehend whatever is being studied and the scale that is being used. I maintain, however, that if the term is to have any meaning, it must be to indicate the qualitative difference between water molecules, plants, and humans.
*3 In essence, I assume the physical potential to be non-limiting. However, there is danger in making such an assumption. Taken too far it leads to the belief in technological-fix solutions, belief that human ingenuity can overcome any biophysical limitations, including our dependence on the biophysical environment. This is not the perspective promoted in this thesis.
*4 I like Smith's text because he recognizes the need to integrate various perspectives. Each of the categories listed tends to be the purview of a different approach to psychology, with varying recognition of the importance of others. Examples include Skinner, a well know behaviouralist and Freud, a psychodynamicist.
*5 These comments have implications regarding the issue of free will - a discussion I will not enter here. I simply note that, in my view, the concepts discussed neither refute nor support either side of the issue. They may, however, recast some aspects making pursuit of this issue, within the context of these concepts, an interesting one.
*6 Such tendencies provide a classic example of the cultural, historical, and personal bias of a researcher.
*7 Some bystanders will not respond (see Myers 1993). Although I believe considering interaction of global-local influences regarding motivation would be interesting I restrict discussion to factors relevant to the group - i.e. to those who do respond.
*8 Kuhn's thesis raised considerable debate and was not accepted by all philosophers of science (see, especially, Lakatos and Musgrave 1970) and remains a somewhat contentious point amongst these scholars (e.g. Polkinghorne 1996). His critics are primarily concerned with his implication that science is irrational and subjective (Kuhn 1970 post-script, Polkinghorne 1996).
*9 A more in-depth consideration of Kuhn's description, especially noting the evolutionary nature of science, would suggest that some term indicating along-side-of-normal would perhaps be more appropriate.