INTRODUCTION

The aim of this article is to introduce an exploration of our understanding of both complexity science and community, with the anticipation that they might inform each other. The work that the authors have undertaken in engaging in these two seemingly different and divergent fields has brought them to the realization that one cannot evolve through the phases of community without experiencing the patterns associated with the behaviors and phenomena of complex adaptive systems. Similarly, the authors have found that in exploring complexity science from the perspectives of nonlinearity, self-organization, and co-evolution, these features and patterns are evidenced in community-building processes. Hence, the structure of this article presents these two areas of inquiry and attempts to demonstrate through an integrated framework, built on the work of Wilber, Beck, and Cowan, just how one informs the other. The authors note the preliminary nature of this article and intend in subsequent writing to further this exploration through the questions summarized in our concluding remarks.

Our hope is that by exploring the discoveries from complexity science we will unearth new approaches to complex problems that frequently arise at different phases of the community-building process. Examples of such complex problems exist in most public and private-sector domains. Understanding more about the underlying constructs that inform us about complexity and community has the potential to assist in creating more effective approaches to the issues and dilemmas found in social and cultural systems.

COMPLEXITY

Complexity science is a child of the late twentieth century and has its roots in chaos theory, dynamical systems theory, fractal geometry, and a host of other interdisciplinary work (Capra, 1996; Maturana & Varela, 1998). Largely, it is the study of emergent phenomena (i.e., behaviors and patterns) that occur at the macro, meso, and micro levels resulting from nonlinear interactions among complex systems (also known as “complex adaptive systems” or CAS; Kelly & Allison, 1998). Principles of selforganization (autopoiesis; Maturana & Varela, 1998) and self-referential behavior underlie the emergence we “perceive” in the way CAS interact, whether functioning as individuals, teams, or organizations.

There are several other important aspects of CAS that need to be considered in order to see how complexity science might inform our understanding of community. It is widely suggested (Capra, 1996; Kelly & Allison, 1998; Lissack & Roos, 1999) that CAS do not operate close to equilibrium, are seen as operating in bounded instability (somewhere between chaos and order), and display, in the case of human CAS, a quasifractal nature.1 Insights gained from complexity science also suggest that both competition and cooperation are important elements in supporting the evolution of CAS (Nalebuff & Brandenburger, 1997). There is an ever-present tension, as CAS seek to self-cause (Juarrero, 1999) through a circular type of causality. Kelly and Allison (1998) describe the process of interlocking behavioral loops in which various closed loops of causality interconnect to support each other in “hypercycles,” which they apply to human complex adaptive systems. CAS viewed from a human perspective function through these hypercycles, as Kelly and Allison state (1998: 79), “to produce an emergent organization that retains its identity while coevolving with a rapidly changing complex environment.” They draw further on complexity science concepts such as nonlinearity, nested open systems, feedback loops, fractal structures, and co-evolution, combined with elements of complex human group behavior, such as values, processes, and strategies, as ways to describe how human CAS achieve both competitive fitness and collaborative partnership. In a way, human CAS are well equipped to respond to their environments, adapt, and coevolve with other CAS. We see the emergence of this behavior over and over again, in teams, organizations, and communities.

Taking a step further, let us explore how human CAS actually interact, construct their “reality,” and continually demonstrate emergence. Vennix (1996) describes in a simple diagrammatic fashion how we as individuals create our reality. As he outlines, individual A uses its mental model to “selectively” perceive what is occurring within its environment. A looks for confirming evidence of what A has selectively stored in A’s memory about what is coherent and safe. This is based on its history of experiencing both similar and different environments. In essence, A attempts to “make sense” of what it “sees.” Based on this sensemaking process, A in turn “behaves” in a way that “feeds back” into the environment information subsequently perceived by individual B, who in turn interprets and responds in a similar way through selective perception and memory, and so on, and so on. In this way, reality is “constructed” by A and B. Furthermore, this activity is spontaneous and cannot be determined in advance.

What we “see” in this interplay between A and B are the emergent patterns of behavior that result from their interaction. When we add more CAS (e.g., C, D, E) to the mix, more complex, nonlinear, unpredictable, and emergent behavior arises. Complexity science suggests that these behaviors are based on “simple rules” of engagement (Wolfram, 1983, 1994). The model presented by Vennix (1996) demonstrates this through the notion of a “recursive” pattern whereby A and B interact based on simple rules of perception and selective memory, which results in a specific pattern of behavior.

Imagine if you will the simple model described above playing itself out over and over again in a larger group of human complex adaptive systems. What we begin to notice is the dependence that constructing our realities has on the interaction that occurs among CAS. As we become more aware of how CAS interact, we notice the high degree of “interconnectedness” of everything that is occurring and we begin to see “relationship” as the primary informant of complex systems at work. In fact, Berger and Luckmann (1966) suggest that everyday reality is an intersubjective world shared by others.

One might suggest that life (as a process) is all about relationships, as the popular movie Mindwalk attests. In addition, we notice that there are times when these relationships appear “stable” (under control) and others when they seem unstable (chaotic). We are able to evidence that CAS operate between stability and instability; between order and chaos, far from equilibrium (Capra, 1996). This has been likened to living “at the edge of chaos.” Hence, we see the adaptive nature of human CAS as they seek coherence in relationships with other human CAS. This suggests a way of informing our understanding about community (and communitybuilding processes) through a better understanding of complexity and the way in which human CAS behave as they continually seek to self-organize.

COMMUNITY

The term “community” has its origins in the notion “of serving together,” of being “with one another in unity.”

In order to better understand some of the community models, let us consider what Arthur Koestler’s coining of the word “holon” means. Holon means “a whole system made up of other whole systems” (Wilber, 1996). It is suggested by the authors that CAS are holonic in nature, as individuals (human CAS), or as groups of human CAS such as families, clans, organizations, and communities. This notion of a holonic world2 suggests that human CAS are always “in relationship.” While human CAS are engaged in their self-organizing activities and encouraged to be so in a world that is built on trust, it is evident that the worlds in which we live are not always trustworthy and our ability as human CAS to survive requires different behaviors to be displayed. When trust is present, however, risk taking, innovation, creativity, and adaptation to change are promoted and encouraged. Critical self-reflection also becomes a norm in this environment where holons meet and interact with other holons. The works of Ackoff (1983) and Churchman (1968) suggest a more subjectivist approach to social science. Jackson (1985) suggests:

The social world is seen as being the creative construction of human beings. It is necessary therefore, to proceed by trying to subjectively understand the point of view and the intentions of the human beings who construct social systems.

Teams that work “in community” work as a complex adaptive system where all of the subsystems (i.e., holons) contribute to the larger system, but the larger system (another holon) likewise informs the subsystems.

Schaeffer (1996), who works with communication and community, says that for him, based on anthropological study, community is a state of being, “in which he cannot not be in community.”

Baskin (1998) uses the human body as a metaphor when he speaks to this “organic” nature of community. In our interpretation of this metaphor one might ask, “How could the heart or kidney ‘go on strike’ when the hand is extended to reach for a bowl of cherries … unless of course the body was sick from the point of view that it was unable to communicate with itself.” In a healthy body, all subsystems (holons) serve the larger system. Moreover, the “relationship” between the subsystems gives meaning to bodily movement, just as the relationship of the notes played on an instrument gives music through the creation of the chord (see the film Mindwalk for a fuller description of this concept).

While many beliefs and assumptions about community are as old as our history, one essence of “community,” as Jarman and Land (1995) have suggested, is a relationship in which “people yearn to live among people without fear, where trust is given and received freely, a place of belonging, where a sense of interconnectedness and unity provides the foundation for life sustaining and enhancing interactions.” From their point of view, it is possible to see that one can be “in community” with oneself, with others, and with the earth and all its creatures. Community is also seen by many as an emerging process that never stops becoming itself. It is not in the “things” that we see community; it is in the spaces (i.e., relationships) between the things that we create community.

Community can also be described as a self-sustaining system, as Goertzel and Goertzel (2001) discuss. Building on the work of Charles Saunders Peirce and his concept of numerical order in the universe, Goertzel and Goertzel (2001) describe relationship as the number three, whereby number one refers to what is, our very being, and number two refers to the concept of being relative to or of reacting to something else. As we see from this analogy, one plus one becomes three, through two. However, there are always three things: the two things being related and the relationship itself.

Goertzel and Goertzel (2001) observe that Carl Jung went further with this notion by adding a “fourth ‘ness,’” which they describe as “a pattern that emerges from the web of relationships that support and sustain each other so that the whole is greater than the sum of the parts.” As such, community, seen as this web of relationships, is in fact a self-sustaining system, exhibiting “systemic” behavior that we can observe through the lens of complexity science. From this notion of relationship in community, we can begin to inform ourselves about the “fractal,” “self-organizing,” and “emergent” nature of community. We can also begin to examine complexity-based phenomena such as strange attractors, weak signals, fitness landscapes, and coherence; more on this later.

A number of authors (Gozdz, 1995) have observed that the process of “becoming community” evolves (and coevolves) through multiple phases.

Jarman and Land (1995) have suggested that we evolve through three phases of community. First is the phase that helps us find “patterns” that support our survival (such as families). Second is the phase of “commonality,” where we find likeness (e.g., the “in” group); and finally, there is the third phase of “reciprocal sharing,” where we accept and celebrate the richness of diversity.

Peck (1987, 1994), in his four-phase model of community building, recognized the power of an extra phase of “emerging” community. He calls this phase “emptiness.” In this he recognizes that some groups not only connect through similarities, but are able to accept real differences without having to “change, fix, or convert” one another. He further suggests that in this “emptying” phase, people (CAS) not only have the highest probability of coming into community, but have the greatest opportunity to hold real diversity in the community. Peck suggests that the path from pseudo-community is through chaos, then emptiness, and finally into (real) community. Authors such as Peck (1987, 1994), Isaacs (1999), and Bohm (1996) agree that in the community-building process we must move through chaos and breakdown before we come into community. In a very “real” way, the community-building process engages us (as CAS) in a “chaotic” experience in which we must find coherence through growth toward inquiry and reflection or regression toward politeness and pseudo-community. We literally live for periods in the community-building process “at the edge of chaos.”

Table 1

Summary of phases of community terminology

Phase Jarman & Land Peck Isaacs—Container Isaacs—Field
1 Patterning Pseudo-community Instability of container Politeness
2 Chaos Instability in container Breakdown
3 Commonality Emptiness Inquiry in container Inquiry
4 Reciprocal sharing Community Creativity in container Flow
Palmer (n.d.) reminds us that community is not the same as intimacy. Rather, community is about a “capacity for connectedness.” He believes that community must embrace “even those we perceive as ‘the enemy’ …

Community is that place where the person you least want to live with always lives … and when that person moves away, someone else arises immediately to take his or her place.” Palmer suggests that a capacity for connectedness is achieved through contemplation. Contemplation is any way a person has of knowing how to overcome “the illusion of separateness” and, by doing so, touch the reality of interdependence. He cites failure, loss, and suffering as being deeply informative forms of contemplation. Thus, the capacity for connectedness arises not from any hard work of building communal structures, but from being open to inner work and resisting the forces of disconnection rampant in our culture and society.

Coming into community is “a process of becoming.” Like the nature of self-organization or autopoiesis, community forms its own identity and sense of purpose, which is very different from its initial stage of “pseudocommunity.” It might be suggested here that all complex systems, be they human or social, complex adaptive systems (ergo individuals working together in community) exhibit some degree of autopoiesis, even though the ways in which this may be accomplished vary. For the authors, being “in community” occurs when we are in a state of what might be termed balance: when our minds, bodies, and souls are serving each other’s needs in a synchronistic manner (Jaworski, 1996). Perhaps we could say that we are living in balance and in community with the earth when we, as human complex adaptive systems, connect and serve each other’s needs in a symbiotic and coherent way. The corollary to this might be that to achieve this state of balance, we must be able to live at the edge of chaos, in relationships that challenge us to be self-causing and selfreflective. Perhaps the very nature of our being “in community” is to ensure our survival and sustainability as CAS. Perhaps this is the dualistic nature of being both in competition and in cooperation; of being explorative and exploitive at the same time. Perhaps this is representative of the “life struggle” for identity and purpose that can only be achieved, or at least sought, through relationship.

When we look at the different ways people define community, it seems that an understanding of community is evolving from a study of “relationship” and all the interconnectedness that pulls us into unity. That is why the current study of complexity science (i.e., the study of coherence and emergence in complex adaptive systems) is so critical, because it informs us about community; it shows us as “human” complex adaptive systems how to “see” and work with the patterns which allow us to be “in community.” Community in this context is viewed not as a place, but as “a process of becoming.” As suggested earlier in reference to Goertzel’s work (Goertzel & Goertzel, 2001), perhaps community is a process of being in relationship that helps us to become who we are, through emergent meaning making, discovery, and inquiry.

LINKING COMPLEXITY TO COMMUNITY

Given our understanding and perceptions of how CAS work, what does this tell us about how human CAS function in community? As is implied above, a growing body of research and literature (Beck & Cowan, 1996) indicates that community has multiple definitions, because as a complex adaptive system, it has adapted and evolved across historical time and space. As the world has manifested greater and greater complex adaptive systems, community itself has demonstrated greater and greater complex behaviors. What makes the phenomenon of community even more challenging to study is that these multiple definitions and examples of community have not merely replaced one another, but coexist in the world today. Indeed, it appears probable that in the formation of every community, new meaning about community is made both from changing life conditions and from the meanings of community that have been previously held by the individual community members (i.e., human CAS).

Given the introductory context of this article, we can only give a brief overview of this evidence. However, we have selected some observations of this evolutionary process, from the practice of dialog, which has attracted interest from scientists and professionals as diverse as a physicist (David Bohm), a psychiatrist (M. Scott Peck), and an organization developer (William Isaacs).

Jaworski (1996) describes David Bohm’s fascination with dialog as a process related to “meaning flowing through” (from the Greek roots of dia and logos). Bohm (quoted by Jaworski, 1996) considered that “ordinary thought in society is incoherent—it’s going in all sorts of directions canceling each other out.” Sustained dialog, on the other hand, creates a space for coherent movement of thought, both at the conscious level and at the tacit, unspoken level. “Dialogue does not require people to agree with each other. Instead it encourages people to participate in a pool of shared meaning that leads to aligned action.” In this manner, dialog allows one person to partially experience the worldview of another, while simultaneously exploring the constructs and models of their own worldview.

Building on the work of David Bohm (1996), William Isaacs (1999; at the Dialogue Project at the MIT Center for Organizational Learning), M.

Scott Peck (1987, 1994; Founder of the Foundation for Community Encouragement), and others, it is suggested by the authors that the practice of dialog in a community-building process is a self-organizing complex adaptive process. That is to say, through the dialog process itself, we can “see” complexity in action. Through dialog, different meaning emerges that potentially leads to different behaviors.

To better examine this notion, let us refer to the concept of “fields and containers.” Isaacs (1999) refers to four fields of conversation (similar to Peck’s four phases of community discussed above), namely politeness, breakdown, inquiry, and flow. Within each of these fields, human CAS interact similarly to the way described by Vennix (1996).

In the first field, politeness, the mental models held by human CAS that are most evident are those that suggest what is “supposed to happen.” There is a “taken-for-granted” assumption about what should be and about the rules that guide this level of interaction. Human CAS do not surface what they really think and feel.

As the conversation is allowed to drift into the second field, breakdown, conversation becomes controlled and skillful. Human CAS start to say what they think. Intensity and pressure build and are held within the “facilitated” dialog process supported by a “container” that emerges from the energy of the community. (An explanation for this “container” arises from the comparison of dialog to superconductivity, where cooled electrons act more in a coherent whole than separate parts.) Bohm (1996) and Jaworski (1996) came to see that dialog can create an environment that is characterized both by high energy and high intelligence. In support of this observation, the authors can both attest, through their own experiences with dialog, to the creation of a distinct field that seems to flow from the mysterious (and elusive) power of the collective participating in dialog.

At this second stage, the elusiveness of the field may be more apparent than any sense of containment, as the CAS of the community struggles with the individual human CAS or participants. Energy seems to be projected outwards by individuals as they attempt to “heal, convert, fix, or solve” (Peck, 1987) one another. This is a stage at which the meaningmaking process and values of the individual members are at odds with the meaning-making process and values of the community of the whole. Breakdown occurs. Often, many groups do not get past this field of conversation and revert to politeness.

If they are successful, the human CAS enter a third field of conversation known as “inquiry.” This is often termed “reflective” dialog. It is when human CAS begin to explore their assumptions and mental models. Different “perspectives” are uncovered and evaluated. Finally, there is a growing appreciation that we don’t have to change others. We can agree to disagree and still be in community. The important difference between position vs. person comes into perspective. Human CAS begin to talk and listen differently. As Stephen Covey has suggested (1990), at this stage of community, members “first seek to understand, then to be understood.” In a similar way, Lissack and Roos (1999) suggest, “In [this] common sense it is critical to allow people to be themselves.”

In the fourth field of conversation outlined in Isaacs’ model, human CAS enter the field of “flow,” which is a transformation to a new “holonic” state. The primacy of the whole is (re)gained. This allows human CAS to connect in a way that truly becomes a learning community (Senge, 1995), built on an action research methodological framework (Stringer, 1996). It is a higher level of being “in community,” one that engenders a high level of trust. New possibilities come into being as people generate new rules for interaction. A new and different ecology is born, one that links the collective thoughts and awareness of each human CAS and sustains a meaning-making process that is less constrained by mental models and constructed paradigms. Synchronicity3 (a condition where meaningful coincidence emerges from the integrative tendency of both causal and acausal agencies, giving the impression of a “flow state”) arises here. It is perhaps the way human CAS were intended to be: fully self-organizing and sustainable in themselves, while maintaining an ecology of holonic sustainability. Built around this notion of sustainability are four “simple rules” or principles, namely:

  1. Allow each person to speak in their own voice.

  2. Listen deeply with discernment.

  3. Suspend one’s assumptions/mental models and need for certainty.

  4. Treat others with respect.

COMPLEXITY AND COMMUNITY IN THE INTEGRAL MODEL

As noted above in reviewing the literature on complexity and community, the authors have noticed a variety of models and definitions expressed for both domains of knowledge. We also note that the two domains share certain qualities. Complex adaptive systems and community systems both appear to be:

  • Scalable.

  • Quasi-fractal.

  • Dynamic.

  • Unpredictable.

  • Interconnected.

  • Nested.

  • Users of simple rules.

  • Subject to phase shifts.

  • Potentially affected by weak signals.

  • Field sensitive.

In noticing these commonalities, the authors find it useful to employ the four quadrant model of reality, developed by Ken Wilber (1996, 2000). This model allows us to examine both complex systems and community systems in a manner that is multi-relational, multi-scalable, and multidynamic. Wilber’s model also allows us to classify different theories of complexity and community in such a way that they inform us in an allquadrant/all-level context. As Wilber (1996) has stated, “nature cannot be reduced to its fundamental entities … the material universe is seen as a dynamic web of interrelated events.” In other words, it seems that things exist by virtue of their coherent relationships.

Integrating this view of complex relationships into a systemic metamodel (used here for purposes of organizing inquiry), Wilber has developed an informative way to track the emergence of living systems in the universe. It applies on the micro, meso, and macro levels (and is based on the work of physicist Eric Jantsch, 1980). Wilber (2000), building on Koestler’s concept of the holon, has further coined the term holarchy to explain the process by which living systems relate to each other along a continuum of development. Holarchy embodies both the concepts of hierarchy and hologram. Holarchy acknowledges that every part of the system (read whole/part) in some way represents the whole (read whole/part) system (holography). At the same time, the holographic parts (read whole/parts) are organized in a hierarchical fashion along a continuum of evolution, with the caveat that each new level of development transcends and subsumes all the levels of development or evolution below it, while emerging something new that has never before existed in time and space.

Wilber sees development occurring through the connections that each living system makes with other living systems in its environment. Wilber’s model acknowledges both the exterior (objective) and interior (subjective) life of holons (i.e., systems) and their singular/individual and collective/group existence, as in Table 2. (The appendix to this article provides definitions of the terminology in the model.)

Table 2

The integral model of reality

Interior/Subjective Exterior/Objective
Individual Intentional Bio-physical
Group Cultural Social

The four-quadrant, all-levels model has multiple developmental levels and represents a reality of emergent dynamic wholisms. Used as a “map,” it has the capacity to chart internal alignments, congruence, and the everexpanding and interconnected nature of wholeness in individuals, groups, and whole domains of specialized relationships. (See Figure 1. Note that the model shown is a subset of a larger model that includes levels of emerging life systems from microbiology and complex galactic systems.)

Fig. 1: The integral model of human evolution

Notes to Figure 1 Each level represents a holarchy, which subsumes and includes the level below it. The descriptors of each level in each quadrant are the words used by Wilber (2000) to typify that holarchical stage of development.

  • Upper left quadrant: These descriptors are adapted from the works of a number of developmental psychologists; for example, Piaget (childhood development), Maslow (needs hierarchy), Fowler (stages of faith).

  • Upper right quadrant: These descriptors are adapted from the works of brain researchers; for example, triune brain: limbic, neocortex, complex neocortex. The more advanced levels are theoretical at the moment and do not have common names, so SF1, SF2, and so on represent the more advanced structures; for example, the capacity of Generation Y to multi-channel, multi-task.

  • Lower left quadrant: These descriptors are adapted from anthropology and cultural studies; for example, Joseph Campbell’s work in exploring myth.

  • Lower right quadrant: These descriptors are adapted from social history and anthropological and organizational research; for example, Fernand Braudel, Alvin Toffler, Peter Drucker.

Beck’s model (Beck & Cowan, 1996), based on the work of psychologist Clare Graves, represents another set of studies in support of this integral framework. Beck has expanded on Graves’ bio-psycho-social research, demonstrating that an individual’s development across a lifetime transitions between “express-self systems” and “sacrifice-self systems.” When we examine Graves’ data from “sacrifice-self systems,” we start to see an emergence of “worldviews” that appear to correspond with the various definitions of community we have encountered. Beck and Cowan (1996) refer to these (color-coded) stages as Value-Memes (v-memes) and have identified key values, characteristics, and qualities of community. In Table 3 we have listed how these correspond to Wilber’s integral model and proposed how we interpret the multiple definitions of community (noted by the authors quoted above) to correspond to these v-memes.

Keeping in mind that the descriptors presented in Table 3 alternate with stages where the individual “expresses self” at ever more complex levels, the data seem to support the view that an individual’s view of community will be influenced both by their individual developmental level and the “life space” in which they (and their experience of community) exist. Beck (2000) suggests:

One of the basic assumptions within Spiral Dynamics is that complex, adaptive human intelligences form in response to the stress and strain forged by life conditions … VQ [v-meme] codes emerge whenever the older thinking patterns can no longer handle the new complexity that they have helped create.

Table 3

V-memes and emergent community

Spiral Dynamics v-meme code Integral model level Key value Characteristics Community Corresponding author(s)
Purple 8 Safety • Mystical spirits, signs• Safe clans and nests• Powerful elders• Us vs. them Respects folk ways• Honors ethnicity• Lets group be itself• Guards magic places • Joe Schaeffer• Ken Baskin
Blue 10 Truth • Only one right way• Purpose in causes• Guilt in consequences• Sacrifice in honor • Peace and quiet• Cautious and careful• Tidy and neat• Born into society • Jarman & Land
Green 12 Communitarian • Seeks inner peace• Everybody is equal• Everything is relative• Harmony in the group honor • Social safety nets• Politically correct• Open to insiders• Invests in itself • M. Scott Peck
Turquoise 14 Holistic • Scans the macro• Synergy of all life• Safe, orderly world• Restore harmony • Interconnected• Highly diversified• Not isolationist• Information rich • Parker Palmer

The writers acknowledge that all mapping systems have limitations, including the integral and spiral models. However, with full acknowledgement that these models may merely provide a form of “crosshairs” for looking at complex systems, we find the models to be useful frameworks through which to view both complexity and community. They seem to provide a framework for examining the micro and meso levels of complexity that emerge in large-scale change. Beck (2000) states:

The focus … should be on the process dynamic itself, not on any specific system, level, stage or whorl that has been activated in forming the complex, adaptive intelligences. Each of the emerging value system waves not only addresses the unique problems in the milieu that gave it birth, but also adds texture and quality to the more complex v-meme codes in the future.

Thus, the integral and spiral models also suggest the interdependent nature of differing energies in each quadrant, which give rise to tensions within, between, and across quadrants.4 These tensions arise as vectors of energetic imbalances in the relationships expressed in the model (see Figure 2). The authors suggest that the imbalances in the model may be the source of the dynamics in life conditions and hence in the spiral of emergence in living systems. The integral, spiral model seems to give us a frame of reference to notice that reality (“wholeness”) is never a fixed or finite condition, but instead is an ever dynamic, infinitely emerging state (Hamilton, 1999). Each holarchic level represents a theoretical “whole” reality at its own level of existence, with the theoretical conditions for phase state changes to emergent new levels.

Fig. 2: Relationship vectors showing examples of related theorists

The writers have noticed that the relationships expressed in the model are reflected in the work of a number of theorists (as examples show in Figure 2), each seeming to have a perspective on a different aspect of community and complex adaptive systems. For example, Schaeffer’s (1996), Peck’s (1987), and Palmer’s (n.d.) constructs encompass subjective qualities of community and account for the meaning-making processes that emerge; Baskin’s (1998) DNA model encompasses the objective qualities and accounts for the ways we enact objective, tangible realities in our lives; Vennix (1996) and Goertzel (Goertzel & Goertzel, 2001) account for qualities of being and how we construct knowing from our doing; and Jarman and Land’s (1995) model describes the process of how groups create structure and pattern. (It should be noted that extensive literature exists related to each of the quadrant domains that can be organized to reflect the developmental sequences in each quadrant. Beck and Cowan (1996) have outlined an example of such a bibliography.)

By examining and mapping each quadrant, we can learn how the interrelationships and interconnections among the four quadrants present us with a “picture” of our time and space reality, which we can share with others in the ever-changing search for meaning making in our lives, which reoccurs and renews itself at each level of evolution. In effect, the authors believe, the model provides us with a way of finding “coherence” and relevance, within quadrants, across quadrants, and between quadrants, and of understanding what is happening on all levels of complexity.

Mutually consistent relationship is another way of describing the interaction and balance between systems in the context of a whole. For example, when we examine “a community of people” for health or wholeness, it is this internal self-consistency (perhaps another way of saying coherence) that is likely to speak loudest to people’s perception as to whether or not it is a healthy community. The integral model shows how the four major quadrants that frame the way we look at ourselves as complex adaptive systems interact, interconnect, and influence each other through the tensions that exist within each quadrant and across quadrants.

This is all operating, of course, at a high level of complexity, but with an implicit drive for congruence across all quadrants. What this also describes is the “scalability” of our state of becoming, as human and social CAS (i.e., as individuals, families, teams, organizations, societies) through ever-increasing “profiles”5 seen in the multidimensional context of the model.

CONCLUSIONS ABOUT THE COMPLEXITY/COMMUNITY CONNECTION

The authors have presented what they have discerned to be significant evidence from the works of others and their own observations that community and complexity do indeed inform one another. The authors conclude that to the degree evidenced in using the integral model, complexity and community inform each other. Through this work, we have shown that the emergence of community is informed by complexity science. We can account for patterns of behaviors emanating from nonlinearity that appear in community; for example, it appears that very small differences can and do lead to significant shifts in fields of conversation evidenced in the dialog process. On the other hand, complexity is informed by community, where social construction through meaning making and evolving phases of community illustrate on a human social scale the interaction of autonomous and adaptive agents in a nonlinear way.

Questions remain, however:

  • Are complex systems always communities?

  • Are communities always complex adaptive systems?

  • How do we explore the need for a new vocabulary to provide a language for the relationship(s) between complexity and community?

  • How do we provide a language for apparently negative and new manifestations of community (e.g., cybercommunity)?

  • Is community simply behavior or behavior “in relationship”?

  • Is complexity a way of seeing behavior in community?

  • How does increased complexity relate to community?

  • What can community-building processes learn from the study of complex adaptive systems and complexity science?

  • How does the study of complexity relate to community sustainability?

These questions and many others remain open for further inquiry in subsequent articles. What is envisaged is a rich dialog concerning this topic and opportunities for meaning making in a constructivist learning context.

The authors intend to develop working definitions of complexity and community as a basis for further discussion in future articles.

Perhaps this journey of discovery into complexity and community is but another step in our struggle as human, complex adaptive systems to understand the nature of our being, our philosophical basis of existence, and our potential as a species locked in a time and space continuum. Whatever the nature of our journey, we invite you to explore with us.

APPENDIX: EXPLANATION OF THE TERMINOLOGY USED IN WILBER’S INTEGRAL MODEL OF REALITY6

  1. The intentional quadrant includes the inner life of emotional, psychological, and spiritual development. The detailed threads in this quadrant are shown in Table 4.

    Table 4

    Intentional threads

    Key intentional threads Detailed intentional threads
    Emotional (”feelings”) Love, fear, joy, etc.
    Psychological (”thinking”) Cognitive, affective, self-identity-ego development, defenses, interpersonal, artistic, concern, epistemic, visual-spatial, logico-mathematic, psycho-sexual, self-needs, space-time, object relations, kinesthetic talents
    Spiritual ( “awareness of self) deeper psyche, creativity, witnessing capacity, altruism, worldviews

  2. The biological quadrant includes all the bio-physical factors that make up our lives. Systems scientist and author James Grier Miller (1978) documented in considerable detail 19 critical threads (or subsystems) of the human body, grouped into three categories, as in Table 5.

    Table 5

    Key biological threads

    1. Sub-systems which process both matter-energy and information2. Subsystems which process matter-energy3. Subsystems which process information

  3. The cultural quadrant includes everything to do with our inner lives as collectives: our beliefs, worldviews, and the stories we tell ourselves. Wilber (1996) characterizes the qualities of the four quadrants as the beautiful (intentional), the true (bio-physical and social), and the good (cultural). The good in the cultural quadrant comes from its capacity to reflect the qualities of a living system as it relates to other living systems, as shown in Table 6.

    Table 6

    Cultural threads

    Key cultural threads Detailed cultural threads
    Identity (who we say we are) Worldviews, philosophies, religions
    Relationships (how we explain the way we relate to one another) Family customs, parenting, kin and clan relationships, community learning and politics
    Information (how we communicate our stories) Meaning, language, speaking, writing, reading, information, the arts: visual, performing (drama, music, dance), design, crafts, architecture

  4. The social quadrant includes everything that defines our ways of organizing ourselves as a population, from tribal taboos, to systems of government, to traffic rules, to energy consumption, to waste management. Miller’s taxonomy describes the social quadrant in the same 19 systems as his analysis of the bio-physical quadrant (see Table 5). Ken Wilber’s work uses the threads as shown in Table 7.

    Table 7

    Social threads

    Key social threads Detailed social threads
    Roles Division of labor
    Social relationships Marriage, friendship, kinship, work
    Civil organizations Government
    Infrastructures Water, sewage, energy, transportation, communication; technology; agricultural systems (planting, harvesting, animal husbandry)
    Industrial systems Resource extraction, manufacture, finance, marketing
    Organizational systems Feudal, federal, hierarchical, matrix, teams
    Information systems Hardware, software, communications, databases, knowledge management, networks, relationships

NOTES

  1. Kelly and Allison (1998) describe fractal structures as “those in which the nested parts of a system are shaped into the same pattern as the whole.”

  2. The term “holon” was coined by Arthur Koestler and implies a situation in which everything is both part/whole; there are essentially no parts or whole, only part/wholes or “holons.” Lissack and Roos (1999) have suggested that “the holon is a central principle of general systems theory. It is the idea that life, and the universe, and everything in between structures itself in levels, subsystems comprising systems within supersystems.” “Holonic” is a term adapted from terminology such as holographic, holarchy, holon to mean that which represents itself as holographic (based on the process of lensless photography developed by Dennis Gabor in the 1960s) in nature. Further reading concerning the concept of a holographic paradigm can be found in the works of Bohm (1996), Wilber (1996), and others.

  3. Jaworski (1996) discusses the roots of the word synchronicity from Jung’s view of meaningful coincidences; Arthur Koestler’s review of “unity in diversity”; and David Bohm’s injunction to “just go with” the flow.

  4. The authors acknowledge the work of Doug Bowie expressed in a model of leadership (Victoria, BC, Canada, August 2000), which caused them to re-examine the integral model for evidence of energies, tensions, and vectors, applicable to leaders, teams, organizations, and communities.

  5. Beck and Cowan (1996) describe the notion of “meme stacks”—as various memes are stacked or nested in us, they display themselves as a profile of our types of thinking at various stages of our evolution.

  6. Adapted from Hamilton and Stevenson, 2000.