The Margaret t-shirt series


My wife, Maggie--who is a member of the art and science factory team--is known by friends and family for her humorous turn of a phrase or otherwise funny quips. A common response made by others to her is, "You have to put that on a t-shirt!" So we did. Or, at least, we are now starting to do so.

Our first t-shirt is "the stupidity is killing me," which is our laugh-out-loud reaction to the increasing inability of people to come together to discuss, address or solve even the simplists of problems; or, alternatively, the failure of people to act in a civilized, caring manner. Is it asking too much?



I recently ran across some very interesting art work by James Moss, who describes himself as an "Artist/Educator - integrating science and spirit through the interconnected phenomena of emergent complexity, self-organization, self-similarity, and consciousness, to reveal a larger unifying fractal paradigm underlying individual and cosmic evolution."

What I like about his work is his attempt to transfer the pictoral representation of mathematical dynamical systems--fractals, etc--onto the canvas, rather than simply generating them via computer. Paint always has the element of time involved, because it simply takes time to paint, and so the images always come across richer and more interesting--at least that is my bias.

To check out his work, go to his blog, Metamorphoptics


Complexity Theory, Managerial Science and the Problems of Definitions

This post continues my discussion about the challenges associated with how one goes about testing the validity and utility of the particular definition of a complex social system one uses.

I ran across an excellent article in the journal Educational Management, Administration and Leadership by Keith Morrison, titled Complexity Theory, School Leadership and Management: Questions for Theory and Practice [2010, 38(3):374-393]. Morrison has written extensively about the utility of complexity science for the field of education, primarily in terms of leadership issues.

What makes the article so good is that it rigorously deconstructs how the management literature fails to effectively distinguish between the metaphorical versus prescriptive versus descriptive use of the term complex system. Too often (and I personally think almost always) scholars in the management and leadership literature (particularly in the field of education) write about a phenonomena such as autopoiesis as if they can move back and forth between their various uses of the term. For example, in the same argument they will treat autopoeisis as something that is real, something you can cause to happen, or just a really cool way to see things. Or, one finds these scholars saying such things as "Principals needs to teach their faculty to think of their schools as complex, self-organizing systems, because schools are alive and autopoietic, so that they can create a nonlinear learning environment." What does such a sentence mean? Can a school be alive? Can you create a nonlinear working environment? What would such an environment be--one where lots of work leads to little change; or little work leads to sudden great change?

The above sentence is the type of conflated intellectual sloppiness that Morrison addresses in his article. I hihgly recommend reading it.


making definitions of complexity clear

This post continues my discussion about (1) the need for researchers to be clear about the definition of complexity they use and (2) to make sure that they test or demonstrate that the system they are studying actually meets the criteria of their definition.

As I have said in previous postings, I am not advocating a strict realist definition of complexity, such that the definitions researchers use and then test have to reveal the fundamental reality of the object they are studying as complex. One can use complexity as a metaphor (as in the case of postmodern complexity), as a proactive concept (as in the case of the leadership literature) or as a empirically useful way of describing something (as in the case of the natural and artificial sciences). What I am saying, however, is that one's definition should be rigorously applied.

My second and related point is that we need rigor in our definitions to bring together the otherwise disparate areas of study in complexity science. Synthesis in complexity science will not come through the construction of a singular definition. Instead, synthesis will come from researchers empirically, proactively, or metaphorically demonstrating that the definitions they use form a gestalt--a whole that is greater than its parts. And, it should be clear to readers and fellow researchers how the components of one's definition go together.

As a final point, researchers need to be careful that they do not move in and out of empirical to proactive to metaphor in their definitions. To me, this type of intellectual slippage is one of the major ways that scholars in the social sciences and humanities get into trouble with their usage of complexity science.

For example, a scholar will empirically demonstrate how a particular system of study is self-organizing. With this success, the scholar will proceed to make a whole bunch of additional definitional assumptions that the proof of self-organization means the system is also agent-based, network-like in structure, and nonlinear (one of the most misused mathematical terms by social scientists and humanities scholars). The term nonlinear, for example, is almost always used in a metaphorical way by social scientists and humanities scholars, to suggest that a social system is messy, not easily managed or controlled or not easily understood via statistical method. In actuality, nonlinear means that the system or, more specifically, the equation or equations used to understand a system are such that their output is not directly proportional to their input. In other words, when the term 'nonlinear' is used in a realist sense, it means that the system being studied and the factors of which it is comprised cannot be written as a linear combination. Furthermore, as a system, these equations are therefore usually impossible to solve, except through computational methods that provide proximate solutions; and the problems are often unstable, that is chaotic, operating near chaos, etc. So, if the researcher has empirically demonstrated that a system is self-organizing but uses the term nonlinear in a metaphorical manner (which may be close to its correct usage but not quite), then the researcher is really causing definitional confusion through a lack of rigor and clarity. For such a researcher to proceed to response to critics (who are rightfully confused) by arguing that the lack of clarity in his or her work is a function of studying complexity--when it is really a failure in the usage of some of the components in her or his definition--is to perpetuate rather than solve the problem they are working so hard to address.


Defining and Test Complex Social Systems

As regular readers of this blog know, I am currently working on a community health study with my colleague, Galen Buckwalter, wherein we are testing to see if the complex system definition used by current researchers has any degree of cohesion and if this definition, in its totality, applies to the typical community of study. I am also working on a study of public school systems with my brother, John Castellani, who is at Johns Hopkins, to see if and how best a public school system can be conceptualized as a complex social system.

In my literature review, I came across the following article. In the 2010, Volume 70Issue 10 edition of Social Science and Medicine, Keshavarz, Nutbeam, Rowling and Khavarpour published their empirical article, “Schools as Social Complex Adaptive Systems: A New Way to Understand the Challenges of Introducing the Health Promoting Schools Concept."

The article fits with my recent discussions about definitions because the goal of the article is to determine the “relevance and usefulness of the concept of ‘complex adaptive systems’ as an approach to better understanding ways in which health promoting school interventions could be introduced and sustained” (p. 1468).

To arrive at their definition of a complex social system, they reviewed the literature. For them, a complex social system—which they call social complex adaptive system—is comprised of a key set of characteristics, which they list on page 1468 of the article. I will not review these characteristics here. Suffice to say, they did what I have been talking about: they outlined a definition and proceeded to use empirical data to determine if their system of study (a school system) meets the criteria of their definition. They used two data sources: public school reports and qualitative interviews.

Using this data, they went through each component of their definition to see if it provided them an empirically relevant and useful way of thinking about their educational system of study. Related, their ultimate goal was to see if the utility of each component lent itself to an improved way of understanding how health promotion programs should be implemented. In other words, if schools can be adequately framed as complex systems, then what does each component of their definition add to their understanding of how health promotion should be effectively accomplished.

In addition to their attempt to empirically examine the utility of their definition, toward the end of their article they outline many of the issues I have been discussing lately. On pages 1472-1473, they state:

"Utilising complex adaptive theory to guide enquiry into a discrete phenomenon (such as a health promoting school) is a challenging task, in part due to the complexity of the theory itself, and in part because of the continuing uncertainty on a clear definition of complex adaptive systems (Rickles et al., 2007; Wallis, 2008). While there has been a recognition of complexity, and steady increase in the use of complexity theory in the study of health care and public health interventions (Keshavarz, Huges, & Khavarpour, 2005; Resnicow & Page, 2008; Shiell et al., 2008) there has been relatively little critical analysis of the concept, and no single and clear account of the components of complex adaptive systems theory and how these components relate to each other (Dooley, 1997; Rickles et al., 2007; Wallis, 2008). Furthermore, as Chu et al. (2003) argue there are few experimental studies that test complexity theories, and there exists even less research into practice informed by the insights that might be provided by complexity science. Correspondingly, application of a complex adaptive systems framework to a social system requires considerable caution, but suggests the need for continued exploration."

What makes the article by Keshavarz, Nutbeam, Rowling and Khavarpour even more important to read is that it was followed by a Commentary by Tamsin Haggis, who provided her own very sympathetic yet useful and critical reading of their article. In turn, the first authors were allowed to published their response to Haggis' critique.

Rather than make a case for which argument I think wins out in the end, I recommend others go read the articles and decide for themselves. Actually, I think both sides have some important points to make, and it is not really a matter of who wins, but how their arguments work together to help make some important advances.


Complexity Art at the SF MOMA

Over the past year I have been making an argument for the emergence of a movement i call, for the lack of a better term, complexity art.  This movement is not a singularity and the artists working in or near or along side its central ideas are by no means confined to it.  Nonetheless, the term, for me, points to something taking place in the current globalized art world.

Having said that, I recently wrote a brief description for one of the artists (Damon Soule) that i see involved in this work, who recently had a book signing at the San Francisco MOMA.  The reviewer of their work kindly mentioned my notion of complexity art.  CLICK HERE TO READ THE ARTICLE


SACS Toolkit and Baltimore County School System

My brother and I are at the International Sociological Association, presenting our paper on the SACS Toolkit and its application to the study of Baltimore County Public Schools as a complex system. The conference is in Goteborg, Sweden with the RC51 (Sociocybernetics) gang. If you want a copy of our paper, go to my Center for Complexity in Health Website. It will be uploaded by Thursday, the 15th.



How Should Complex Systems Be Tested?

This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems. This is the fifth post on this topic since then.

The argument I am making is that researchers need to do some sort of complete (holistic) test of their topic, to: (1) make sure that the definition of a complex system they are using applies; and(2) make sure that their topic fits this definition.

The question I want to address here is how should such holistic testing be done?

Again, this will take a bit of blogging, but it seems to me that testing can be thought of at two basic levels.

1. Deep/Thorough Testing: The first and most rigorous level would require one or more studies devoted to a sort of deep or thorough testing to determine if one's definition of a complex system applies to a give topic and, related, if that topic can be validly and reliably called a complex system.

This first type of testing is the focus of the community health science study I am doing with my colleague, Galen Buckwlater. For the last couple years, researchers have been explicitly or implicitly treating communities and their health as if these things are complex social systems. Our research question is: is such an assumption valid and reliable? In other words, can one assume that the commonly used definition of a complex system applies to the study of communities and their health and, conversely, can communities and their health be called a complex system?

To conduct this type of test, we did the following. (A) First, we reviewed the literature to determine what the common definition of a complex system is that researchers use. (B) Next, we found a case study that represented the average community researchers typically study and collected data on it. (C) Then, we took each descriptor from the common definition of health and ran a series of tests. For example, a commonly held assumption is that communities are self-organizing. To determine if this is true, we examined if the conception of self-organizing used by these researchers to determine exactly what they mean by this concept. Then, we empirically tested this concept of self-organization to see if our community actually engaged in this behavior. In total, we ran ten individual testsn on the commonly used definition of complex system used in the community health science literature. It was a tremendous amount of work. And, in the process we used a wide arsenal of techniques, including hierarchical regression, curvilinear regression, correlation, k-means cluter analysis, the self-organizing map neural net algorithm, network analysis, qualitative case-based comparative method and computational (agent-based) modeling.

One can think of this first type of testing as helping a field along by increasing the rigor of its concepts and its knowledge of the type of complex system it it studying.

2. Shallow/Preliminary Testing. The second type of testing is what we might expect all researchers to do before and during the process of modeling a particular topic as a complex system. In this case, one would begin by explicitly outlining the particular definition of a complex system one is using. Then, one would conduct some type of preliminary tests to determine if one's topic is, indeed, a complex system.

The testing in this second case is likewise rigorous but it is more background work. Also, it is something that takes place before and during the model building process. The quality of one's results is something that is reported in the methods section of a study.

I have used this type of testing in a couple studies we have done. The first one was my research with Fred Hafferty on medical professionalism and the second was the book on sociology and complexity science that I wrote with Fred as well. In both instances we articulated the definition of a complex system we were using and tested to see if our topic fit it reasonably well.

This second type of testing involves the development of what we call a meta-model, and it is one of the first steps in the SACS Toolkit modeling process--this is the new method Fred and I developed for studying complex systems. SACS stands for sociology and complexity science. For more about our method, see our BOOK

Developing a meta-model (a model of one's model) allows researchers to determine, right from the beginning, if their definition of a complex system is rigorous and if their topic is (empirically speaking) a complex system. In addition to the development of a meta-model, the SACS Toolkit has a total of nine built-in procedures that researchers are expected to use to explore their definition and topic in complex systems terms. My brother John and I are writing a paper on how the SACS Toolkit does this and will be presenting it this summer in Sweden at the International Sociological Association Meetings. I should be done with the paper in the next couple weeks and will post it on here. I also plan to blog more about the SACS Toolkit so that readers can get a better sense of the method.


Complexity Definitions Need to Best Tested as a Whole

This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems. This is the fourth post on this topic since then.

Okay, I am getting a bit closer to what I am trying to say about testing. When I say definitions needs to be empirically grounded and tested I mean that the entire definition, as a whole, needs to be empirically grounded and tested. To date, most empirical inquiry in the complexity sciences focuses on parts of the complexity science definition. Researchers study networks or they study dynamics or they study emergence, autopoiesis, self-organization (a.k.a swarm behavior) and so forth. Two things are held as true in these studies. First, that the things being studied are actually complex systems. Second, that the part of the complexity science definition the researcher is studying naturally integrates into the larger complex systems scheme of things. My questions is, how do you know both of these things are true about the topic one is studying?

One way I think researchers can be sure is to do a complete (holistic) test of their topic, (1) to make sure that the definition of a complex system they are using applies and (2) to make sure that their topic fits this definition. For example, if researchers assume that a complex system is self-organizing, emergent, comprised of a large network of interacting agents and open-ended, then these researchers should have a series of tests to validate if this definition (in its entirety) applies to the topic they are studying. Alternatively, such a complete set of tests makes sure that the topic these researchers are studying is actually a complex system, or at least the type of complex system they seek to study.

Operationalizing metaphor

This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems.

I my last two posts I've argued that one should have a way to determine empirically if the topic one is studying is actually a complex system. Related, I've argued that the definitions complexity scientists use to identify a topic as a complex system should likewise be empirically grounded and tested. In this post, I want to comment further why I think doing such things is important.

Two words: operationalizing metaphor. I have read far too many articles and books in the last couple years that are little more than undisciplined, metaphorical labyrinths verging on the same sort of nonsense that took place at the high point of the postmodern movement in the 1990s. I've read articles talking about turning one's business firm or one's educational system into a self-organizing, emergent, agent-based network in order to optimize profits or learning, as if one could make a social system self-organize. Is that not contradictory? How does one make a system self-organize, given that a self-organizing system is one where there is no guiding external force controlling the systems's organization? Or, how about pushing one's business to the edge of chaos in order to profit from its nonlinear dynamics? What does something like this mean? Do these writers really understand what nonlinear (which, last I looked is a mathematical term) means? Related, what is nonlinear management? Or, how about talking about any and all social change as if they were the product of tipping points? When I hear such discussions I am reminded of the first time I heard a politician talk about "deconstructing" some political process to get to the bottom of things. Worse, when I hear such complexity science nonsense, I fear the next Sokal Hoax. Remember how the physicist, Alan Sokal, submitted his completely nonsensical postmodern text to the periodical, Social Text, and got it accepted, only to reveal later that the entire text was garbage. Sokal's hoax was done with complete seriousness. He was not trying to say that postmodernism was useless. Instead, he felt that postmodernism had some important things to offer, but only by increasing its rigor. I'm not saying that some of the complexity science literature has reached this point. But, it is close. If complexity science is going to make important inroads into mainstreet science, many of its new practitioners need to be more empirically rigorous and discerning in the definitions they use and the topics they call complex systems.

Is what you are studying a complex system?

This post extends a conversation I began on 19 May 2010, titled testing the validity of complex systems.

My basic argument is that we simply too often assume that any topic we are studying is a complex system simply because we say so--regardless of the definition we are using.

Now I know that the definition of a complex system is encyclopedic, such that many definitions exist. And, of course, I am not arguing for a single standard by which all topics should be judged worthy of being called a complex system.

But, I am arguing that, regardless of the definition researchers use, they should have some way of testing their topic to see if and how it acts like a complex system.

For example, pretend one assumes that complex systems have the following characteristcs: they are self-organizing, emergent, operating near chaos, and agent-based. Definition in hand, one then goes out to study a local community, a formal organization or some social network. Before one begins, however, shouldn't there be some set of preliminary tests done; some sort of way to determine if what one is studying is actually self-organizing, emergent, etc? Related, what would one look for to determine if such characteristics exist? What tests would one use? What methods would be relevant to conduct these tests? And, what if one finds that one or more of these characteristics is lacking, or only exists in a modified form? What then?

Again, I am not saying that one test or definition fits all. But, I am saying that the definitions complexity scientst use to identify, model and study various topics as complex systems should have a bit more empirical rior. These definitions should be tested and held up to empirical validity and reliability. One should be able to talk intelligently about what one means when one is calling something a complex system.


testing the validity of complex systems

I could be wrong here, and I am not entirely sure about the argument I am making, but it seems to me that much of the work being done in complexity science has yet to reach a point where topics are tested to see if and how they function as complex systems. There is lots of work on the network structure and dynamics of various systems; there is lots of agent-based modeling, and some of this work has gotten along enough to do both agent-based modeling and network analysis. Then there are various forays into emergence, self-organization, autopoiesis, swarm behavior, dynamics, chaos, evolution, and measurments of complexity. But, there is yet to be any sort of criteria set by which researchers can go out and determine if and how some topic of study is and acts like a complex system.

I am not setting up a straw person here. I know our field is very new; in fact, in some ways there is no complexity science; there are, instead, the complexity sciences. I know there are multiple definitions of what a complex system is; and i know we work in a broad range of fields, making any sort of singular statement both impossible and, at least from my perspective, unncessary. we can accept that complexity is an encyclopedic term and leave it at that.

So, for sake of discussion, let's just focus on the social sciences. In the social sciences, there does not seem to be much research actually applying the full force of complexity science to the study of a topic. Researchers do not seem to often take a topic, apply some criteria or empirical tests to see if it functions like a complex system, and then proceed on to examine the topic in complex systems terms.
Instead, it just seems that most topics are assumed to be complex systems, and some aspect of them is studied, say their network structure or the role agent-based interaction plays in their emergence.

My colleague, Galen Buckwalter and I are working on a paper now that does just the sort of thing we are talking about. Our work is in community health science. We are trying to take a topic and say, "okay, we think this community can be studied as a complex system; we think it acts like a complex system, and we have all these methodological tools that we can use to explore the empirical validity of our conjectures, so, let's proceed, in litmus test fashion, to determine if and how our community acts like a complex system."

Why do we think this is important? Well, I guess I will need to blog on it a bit, but for now I think the main answer is that, without some type of empirical and methodological rigor established (start with a, then move to b, etc), it becomes impossible to pull together the arsenal of tools, theories and concepts complexity scientists have created over the last three decades to get the most out of studying any given topic in the social sciences in complex systems terms. That is all for now, but i will try to say more and say it better.

Michelangelo and Complexity Part 2

Okay, so a few of my personal art critics asked me to push the painting you see above a bit further. To see the older version, click here The argument was that I needed to develop the network more, to make it stand out. I think it was a very good recommendation and I like this version of the painting much better. So, here is it.


Homage to Michelangelo and Complexity

Michelangelo and Da Vinci's work are a major source of inspiration for my artistic and scientific work in complexity. Their Renaissance attitude is, in many ways, what complexity science, with its multi-disciplinarity and systems perspective is all about.

In the painting I have posted here I had a very specific goal. I wanted to do a painting in the manner of Michelangelo: a painting that focused on the human body and that celebrated the mathematical and scientific dimensions of art. However, I wanted to create a painting that fit with my own 20th century attitudes.

So, the first step was to determine how I wanted to approach the body. I stayed away from the over-muscular work of Michelangelo, opting instead for a more realistic portrait. I also wanted to have the person pose in a somewhat more humble and less grandiose manner--something that honored the dignity of humans but without going overboard. In the complex, global society in which we live, humility and a recognition of one's deep interconnectedness to the world, at least for me, is an important ethical position. I wanted to reflect that in the painting.

The second step was to incorporate a Zen Buddhist perspective into the painting. For me, the symbolism I primarily focused on revolves around the sky, clouds, and the circle, which have a lot to do with systems thinking, holism, interconnectedness, meditation and bodhichitta.

The final step was to incorporate some of the latest developments in complexity science and mathematics, namely networks and fractals. Math and science were an important part of Renaissance painting, and they are likewise important in my own work. In a fractal-like manner, there are levels of scale in the painting: there are large circles, which suggest a larger network that cannot be entirely seen; then there is the specific network structure surrounding the figure.

So far, reaction to the painting has been mixed. That is understandable because I struggled with the painting myself. I would like to continue exploring this type of painting, working next with more than one person or playing off of different poses that Michelangelo used in his own work.


Complexity in Health Group

It has been a while since my last post. My research colleagues and I have been busy creating a new research center for studying health and health care via the tools of complexity science. It is called, appropriately enough, the Complexity in Health Group. Much thanks to Michael Ball and Kenny Carvalho for their incredible viking work.

CHECK OUT THE SITE: cch.ashtabula.kent.edu


The Complexity in Health Group (CHG) promotes the application of complexity science to the study of health and health care through a cross-disciplinary program of teaching, training and research. The CHG’s application of complexity science includes complex systems thinking, computational modeling, network analysis, data mining, and qualitative and historical approaches to complexity. The CHG is specifically committed to collaborating with health care centers and practitioners in Ashtabula County, Ohio; and to students and faculty at Kent State University. The CHG is affiliated with the Robert S. Morrison Health and Science Building, Kent State University at Ashtabula. Other affiliations we are working on include Kent State University’s College of Public Health and the Kent-Summa Institute for Clinical and Translational Research.

The Group will have several foci:

• Becoming a leading international research center in the application of complexity science to the study of health and health care;
• Generating revenue for our campus through extramural funding;
• Fostering interdisciplinary research with faculty at the Ashtabula campus, as well as Kent State University and other universities;
• Developing our undergraduate student population’s skills in science, technology and mathematics in application to health and health care, particularly public health;
• Developing collaborative research relations with local health agencies and businesses to promote the public health of Ashtabula County.

The current topics of the CHG are:

• Studying how communities, as complex systems, impact residential health, particularly in disadvantaged communities;
• Developing new tools for measuring and teaching medical students, residents, and clinical faculty about the challenges of medical professionalism in today’s complex health care system, both nationally and globally;
• Using network analysis to research how medical learning environments shape nurses and physicians;
• Studying how public educational systems impact the health and wellbeing of children.
• Developing the SACS Toolkit, a new method for studying health and health care from a complexity science perspective.


Westside Market, Cleveland Ohio, Complexity Photo

Balcony View of the Westside Market, Cleveland Ohio, 1971 & 2010

This photomontage highlights how Cleveland’s past is part of our present moment and how, in many ways, our city’s past remains alive for us, if we only take a moment to look. The focus of this montage is one of Cleveland’s most important landmarks, the Westside Market. Located at the corner of West 25th Street and Lorain Avenue, Cleveland’s Westside Market has been in business since 1840.


Description of the Photomontage
The photos in this montage were taken at two different points in time. The black and white photos were taken circa 1970, courtesy of the Cleveland Public Library. The color photographs were taken in 2010 by the artist.

Some things stay the same: Much of the Westside Market, despite the many years, remains the same: fans on walls, posters, light fixtures, etc. What is odd about these remains is that, while some are very important, others continue for no apparent reason. It is as if somebody forgot about them or nobody ever thought to take them down. In the far left side of the picture, for example, is a really old fan. Why is it there? Does it still work? It begs the question about how history comes to us; perhaps, sometimes, as remains or leftovers from the past; things people forgot about or were too busy to clean up. Funny! Then there are those things that remain because of the important value they hold: the architecture, style of the booths, etc. Perhaps the best example is the old steer’s head on the butcher’s booth in the lower left side of the picture—it is still there, some 40 years later.

And then things change: History is not just the study of the past; it is also the study of how things have changed. Much has changed at the Westside Market over the last 40 years. For example, looking at the montage, it appears that the only booth from the 1970s that is still operating today is Fernengels—see the middle right side of the photograph. Other changes can be found in the montage as well: clothing styles, eyewear, hats, the types of produce sold in the booths, etc. If one had enough time, a rather interesting anthropology of Cleveland’s culture could be constructed from this montage.

Similarities and differences aside, the people in these photographs all seem to be enjoying the same thing: the food! Food is such an important part of our lives, and places like the Westside Market struggle to keep the “open-market” approach going—not an easy task in a world full of suburban-based, giant-sized, high-convenience food stores. It is great to see the Market still thriving after all these years! Long live the traditions of Cleveland.


The Increasing Complexities of Professionalism

My colleague, Fred Hafferty, and I have been working for the past five years to articulate a grounded theoretical frame for understanding medical professionalism, primarily by applying the tools of complexity science. Our work, to date, has been mixed methods--historical, qualitative, numerical, networks.

We finally published a somewhat comprehensive overview of what we mean when we say "medical professionalism is a complex system."

Click here for a summary of our article "The Increasing Complexities of Medical Professionalism"
The article is our second major statement on professionalism from a complexity science perspective.
The first, published in 2006, can be found here:
"The Complexities of Professionalism: A Preliminary Investigation?

There is still lots of work to do and, in part, many of our ideas are tentative and somewhat vague. But, we at least have a reasonably solid grasp of the point we are trying to make.

The article was published in the February 2010 Edition of Academic Medicine, which is a special edition for the Flexner Centenary. (Click here to learn more about Flexner)


Dad/Son Inside/Outside Summer/Winter

Here is another assemblage photomontage. The photos are by my nephew, Kevin Rusnak, and by me.


21st Century Dinner Party—Cathy’s House

The following photo is part of my new series of work.
In what follows, I provide a series of powerpoint slides that explain what is going on in this photo. Just click on the slide to enlarge and read it.

Slide 1

Slide 2

Slide 3

Slide 4

Slide 5

Slide 6

Slide 7

Slide 8

Slide 9


Cesar Hidalgo: Complexity Art and Science

If you spend any time regularly visiting Barabasi's website, you have seen the incredible work he has done with Cesar Hidalgo--as the above picture shows.

Cesar Hidalgo is a Research Fellow at Harvard University's Center for International Development. His doctoral work is in physics at Notre Dame, where Barabasi worked before moving to Northeastern University.

In terms of research, Hidalgo has done some absolutely incredible stuff, applying the new science of networks to the study of global economy and (working with colleagues, particularly, Gonzalez) mobility within networks.

In terms of global economy, you need to see the supporting website for his work with Barabasi and colleague on the product spaces of various nation-states. CLICK HERE

In terms of his work with Barabasi and Gonzalez on mobility patterns within networks, CLICK HERE.

What I also find fascinating about Hidalgo's work is that he approaches networks as objects of art--something I obviously take rather seriously, as my recent posts have shown. To see some of Hidalgo's network art, CLICK HERE.

Much is made of the C.P. Snow's two cultures--art and science. However, if you spend any time looking at the networks created by Barabasi, Hidalgo and colleagues, it is clear that the boundaries between art and science need not be so rigid. Looking at their networks is an act of both science and art. They are both intellectually incredible and artistically brilliant!