It is Official- My systems thinking/policy book has a release date of Nov 2014- Pre-order print or ebook @ Amazon and Springer website http://lnkd.in/bun2Dvs. @mbattlefisher- Just in time for holiday giving or course book selection!
The Complexity Explorer project, being developed by the Sante Fe Institute, has included my Social Networks and Health course syllabus in its depository of course syllabi that offer instruction on complex systems science. Though I have since worked on some revisions, this is the second organization that has highlighted my course. The syllabus was first selected for the KaiserEDU course depository (since taken offline). I am working on integrating my new forthcoming book more prominently in the new syllabus.
Founded by Jon Wilkins, formerly associated with the Sante Fe Institute, the Ronin Institute is flipping and transforming the nature of academia. The Ronin Institute houses established researchers of various disciplines that reside mostly outside of academic institutions. I do not need to stress that there are a large number of could-be researchers who do not make it or do not care to be a part of the traditional university system. The popular code for what we do is ‘fractional’ research. Fractional or not, we are a group of strong researchers that kick butt and have bonded together to have a collective voice while adding to scientific knowledge.
Some press about the Ronin Institute:
2. http://www.bostonglobe.com/ideas/2012/05/26/new-idea-for-unemployed-academics/UUZOGe1KNWvUXDl7Yae1IL/story.html- We ain’t wayward! We are Ronins!
Steven Johnson (2010), the popular author of “Where Good Ideas Come From- The Natural History of Innovation”, wrote that innovation is structure based. A cornerstone of Johnson’s (2010) book is this idea of an informal, liquid network in which ideas collide. Johnson (2010) visualized the liquid network as the Hogarth’s painting “Humours of an Election”. Ideas generate from informal meetings not that company annual retreat in Florida ac-cording to Johnson (2010). The closer the people’s ideas are in space and time, the better the chance for the ideas to collide with a few new (idea) bonds formed along the way. Johnson’s use of network would better be labeled as idea management rather than being complexity driven. But for policy to be able to account for the long-term implications of idea management, ethical deliberation drives the complexity of organization. The included table compares the offerings of the liquid network of Johnson (2010) to the social networks for idea management. Collision unfortunately lacks the formality and accountability afforded by the structural relationships of social networks. Broadening idea generation beyond a “bump” illustrates the immensity of the effect of the social and political reach of policy.
People connect within a social space. According to Alba and Kadushin (1976), the measure of proximity is concerned with pairs of individuals and how “distant” they are. Traditionally, proximity is all what diffusion of social commodities, often defined by information sharing, as a flow (Alba and Kadushin 1976). In a liquid network of Johnson’s conceptualization, ideas bump into each other due to the act of discourse as an event. First, there must be connections to other people and the environment supports the development of ties. Johnson concurs. There are the things colliding in a network which in Johnson’s (2010) case is the idea. Discourse turns that “private solid state to a (public) liquid network” (Johnson 2010). In what Johnson (2010) called the state of adapting exaptation, people can informally engage due to the “bump factor” of these chance meetings (Johnson 2010). To Johnson (2010), innovations linger in a “slow hunch” countering the eureka moment. The power of leverage points values the ability to find a small change that can make a huge impact. This is not the same as the epiphany. Systems that undulate slowly can be most frustrating to the urgency placed on having policies work.
The liquid network is mildly bound enough to be a network but not enough to strangle innovation with rigidness. Ideas are innovative because of the people that offer them with their skills and prestige. Some ideas are drowned out or flatly ignored. Connecting the ideas as a structure is often descriptive. Which idea (or person with the idea) was most connected? Which idea structurally demonstrated power in the network of ideas? Then this whole idea of playing with private ideas within a public space by basing it on the structure of the irrational agents is the more interesting, and fruitful question to pose.
Johnson (2010) proposed that platforms, or orchestrated spaces, may foster innovation. Within these platforms, liquid networks which do not restrict movement within an organization and their innovation ideas may be better supported to thrive. The ideas take on a fluid state without outside restriction. Does the event become more consequential than the interaction supported by the event? Networks are systems in which the nodes (the things that are connected) are connected by ties. When one is interested in reasons for why people affiliate over an idea, two mode networks could be employed (Borgatti and Everett 1997). The people would be agents (set 1 mode) while the IDEAS serve as a “series of events” (set 2 mode) that they are sharing. In a two-mode network, both the idea and agent indicates the elements of the network. The idea becomes an element to be weighted with the agents and chance meetings. So there is a tie be-tween the agent and the event. The tie formation could be due to “bump factor”:
1) to accept the chance meeting and
2) engage in the innovating chance meeting.
Both nodes engage in it since Johnson (2010) is basing adapting exaptation on engagement not its possibility. But a concern with approaching such two-mode networks, which mode takes the primary position? For instance, Johnson (2010) does not divorce the person from the idea and but for his paradigm the idea is element of focus. The idea is the primary node. The idea comes from the person (secondary node). The argument would also be made that if innovation is viewed as a dynamic, social experiment, the person as the primary mode may say more about why that idea even came to be in the first place. While the platform may be nature be useful in revisiting existing resources such as ideas in a liquid network, the problem often uncovered in policy is the lack of new ideas and continued reliance on existing ideas that may lead to attribution errors. To Johnson (2010), the ideas are used as bonding agents. Two-mode networks deal with the nature of affiliation. The idea is no longer just assumed but is now used as a means to investigate the structure in which ideas are embedded within the ties connecting the author of the idea (see Smith and Christakis 2008). The approach of Johnson (2010) had ideas brought “together” by its messengers as one frame. I do not believe that Johnson (2010) is marginalizing the person behind the idea of the liquid network. By stressing the network, the structure at two mode levels appears to capture the reality of how innovation in a liquid network more likely occurs.
To Johnson (2010) removing boundaries to the liquid network leads to chaos. This may be wise as any chaotic system does not return back to original state before the spiraling began. This chaos could hamper innovation by changing the new starting point and disrupting the momentum started in creating the innovative (see Feigenbaum 1983). As Johnson (2010) was intending avoiding chaos for a malleable liquid state, there is no history of events connected with a state of chaos. When things are chaotic, the past matters far less, only the energies running amok are important. What significance might this hold for developing innovation? Unlike chaotic systems, complexity is tied to its history of events upon which the system was built (see Buchanan 2000).
What is applicable to policymakers under liquid networks, according to Johnson, is less promising. In offering the example of Howard Dean’s Presidential Campaign “supernova”, Johnson (2010) admitted that “political leadership involves some elements (decision making and oratory) that aren’t best outsourced to a liquid network.” So how do policymakers innovate and think creatively under political stressors? Using Wasserman and Faust (1994) taxonomy, two-mode networks have three possible purposes under Johnson’s (2010) liquid networks:
(1) The affiliation is the tie of the person/ideas (node) to the informal chance meetings (event).
(2) The “bump factor” (if it supports interaction) may make interaction, therefore innovation, more likely.
(3) In order to framing the adapting exaptation realistically, the measurement of homophily is required.
The two mode network is difficult to interpret, let alone analyze. But how ever said that policymaking was easy? People tend to clique around policy issues, perhaps based on the process of idea generation or even bunch out due to personal access due to co-location. Two modes capture this bunching up as cliques that overlap, perhaps by party affiliation or side of a legislative issue. But the point of this methods tale is not the complicated analysis but that that coming together to work policy out that on the surface can be deceivingly simplistic. This is a great example of how the mental model of a liquid network does not apply neatly to policymaking but still has a place in the discussion. Unlike the informal liquid network, the innovation required by policy must translate into proper strictures under governance. The chaos of a liquid network must be operationally linked to the structural nature of complexity. But this fact does not mean that networks, whether liquid or mathematically understood, are not useful in discerning policy. While the informal ideas that are eventually brought to the policy table may utilize adapting exaptation, the policymaking process strips away the lacquer of casualness.
Alba R, Kadushin C (1976) The intersection of social circles- a new measure of social prox-imity in networks. Socio Meth Res 5(1): 77-101
Borgatti S, Everett M (1997) Network analysis of 2-mode data. Soc Network 19: 243-269
Buchanan M (2000) Ubiquity- The Science of History…Or Why the World is Simplier Than We Think. Weidenfeld & Nichols, London
Feigenbaum M J (1983) Universal behavior in nonlinear systems. Physica 7: 16-39
Johnson S (2010) Where Good Ideas Come from. Riverhead-Penguin, New York
Smith K, Christakis N (2008). Social Networks and Health. Annual Review of Sociology 34: 405-429
Social policies are, more often than not, framed with the traditionalist rationalization of human intentionality. Be that as it may, policy tenders the protocols that are then acted up-on publically to bring social impact. Of course, a well-intended health policy must take into account on courses of action as well as funding priorities and constraints. I argue that socially based complexity puts into question the probability of purely rational public action. Social elements activated or retarded in a public policy can shift burden from one part of a healthcare system to another. In its most simple explanation, increased positive screening for disease within the safety net can lead to the probable increased usage of acute care treatment for individuals requiring more complicated care. While some level of desired social and health satisfaction may be experienced in the short term by shifting policy priorities, it is also probable that no tangible value is achieved toward to the overarching desire to elicit system wide impact. Will the positive changes last? I purport that living an illness with a public further complicates policy issues of keeping anything that is personally health related purely private.
According to network theory, naming a network is powerful. According to Trotter (1999), the existence of a boundary is defined by the rules of exit and entry. However, complex systems call for more intricate examinations of such boundaries. Unnamed groups are often identified by the observer and the boundaries are often most not agreed upon by the group members (Kadushin 2012). How might this idea work for special interests groups in making cohesion? According to Kadushin (2012), “a collectivity is structurally cohesive to the extent that the social relations of its members hold it together.” Further there are two mechanisms that support and disrupt this happy state of togetherness. First, if a “disruptive force” acts upon the group, will the network survive? Second, complexity is bound also to the health of its network. Like a game of Ker Plunk, disruption in a complex system occurs when one or more people are removed from the group (Kadushin 2012). The cohesion may or may not be able to survive. Then the process of community starts all over again with new set of actors and new structural relationships.
I do not recall an ICD code for attending family barbeques or activating one’s “social network” for staying healthy. Health care is not directly rewarded for healthy patients’ visits to Disneyland and the strength of the social support ties that keep patients well. More often than not, healthy patients demand less utilization of an already expensive and taxed health care system. Patients have social networks of confidantes of differing yields and compositions, but each member by association has the ability to persuade and dissuade if they wish. Often this network is an 800-pound gorilla in the examining room. This gorilla is a relative that has diabetes and complains of diabetic neuropathy while carefully sectioning the pecan pie with a surgeon’s precision. The sorority sister is a helpful “gorilla” that caresses your hand as you await medical results.
Failure is picking up a socially expected square peg after the innovative oval one fails to fit a conventional hole. If you really “need” the oval to work (and the world is not yet with the program), check out the board again. If there is no oval hole, darn it and chuck that board. Find a reamer and create your own or perhaps ask for a refund with no return shipping. Failure is the incessant attempt to satisfy others by hiding that socially acceptable square peg behind your back and asking for a few more days (in dog years) to work it out. Whittling that square peg with that dull pocket knife into a misshapen imposter of an oval peg serves no god. That imposter peg is not flush to the side of the hole. It is surrounded by slight flashes of open space. That open space created around the non-flush peg should extract with a slight tug. Trust me, that tug will be less taxing than the linear process that got that wrong peg there in the first place. Policy has little tolerance for misshapen pegs that bring with them unintended effects. Use a policy that works until it does not or admit that it never worked at all. Then make it work without the attribution errors gumming up the machinery. What works may not be the most apparent or popular choice.
At its simplest denominator, a citizen is by principle afforded the right of being included in a group’s decisions. But there is a special place for those who serve as policy experts. Sure, we could discuss until we are blue in the face how much a weight a vote in a representative democracy really holds. When I think of my job of being a citizen of any group, I am accountable in some manner to the group if I am not gerrymandered out of the process. Not unlike the idiom “we are in this together”, this cannot be truer in terms of health burden. The solidarity means that all of us have culpability in the collectives’ improving health. But each of our investment in this solidarity differs in our (re)actions, invocations and values. This knowledge should, in theory, affect the role that each of us plays in bettering health out-comes. But can and will citizenship overcome the medical reality that years of collective neglect have brought? How do we get people to give a darn and become a card-carrying Norma Rae? Those in policy hold a special role that should not be understated. A policy has the power to guide and mold the direction of societal movements or evade an unfortunate set-back. We are accountable but that job responsibility came with the rocky terrain. Necessary insights are gained from this systems approach. What is called for is the acknowledgement of the ligand and substrate nature of the two. In that regard, often a slanted pairwise comparison of objectivity to systems demonstrates the bias toward linearity. It is time for systems thinking to no longer be relegated to the kids’ table, peering around the corner and straining and wishing to bring its expertise to policy discussions.
Kadushin C (2012) Understanding Social Networks. Oxford, New York
Trotter R (1999) Friends, Relatives and Relevant Others: Conducting Ethnographic Network Studies. In: Schensul J, LeCompte, M, Trotter R, Cromley E, Singer M (eds.) Mapping social networks, spatial data and hidden populations. AltaMira Press. Lanham, MD
Let us begin with the pressing policy issue of HIV risk taking behavior among homelessness teens to take home this point of social bond (de)construction. In the work of Rice et al.’s (2012) study of HIV risk behavior, homeless adolescents were located within the core (that dense ball of spaghetti in the middle of the network graph), were more likely to be female and were more likely to have been homeless for at least 2 years. The longer the teen, particularly for the young woman, is outside of the family unit, the teens form strong, compact ties with a new “family”. Surprisingly, being on the outside of this tight “family” that is found in the periphery of the network was protective against HIV risk taking. Highly connected, dense core are great for galvanizing information within that group. But a dense group may be more difficult to infiltrate. If the dense ball of teens are passing misinformation and reinforcing risky HIV behaviors, it is best to go your own way. But where can a young person go with such marginalized circumstances?
If the public policy being developed pertains directly to HIV risk taking reduction, perhaps targeting the core network to diminish risk could be a first step. But in the work of being connected to other people, the low risk teens may help each other or could transfer into the high risk group. But policymakers must remain mindful of what systemic changes can flow from targeting that portion of the network. People come and go into each other’s lives. Policy must be mindful that the longer the teen is outside of a traditional household, human connections will be made with the people that they have the most contact with. Could the teens in periphery have formed cliques that supported less risk taking? This may help these teens. Keep the periphery teens supported in their low-risk behavior. In the world of networks, there is something called homophily (birds of a feather). This means more than living in the same place. Above that shared space, the teens are ties together by something stronger: love, support, shared values, shared behaviors (see Feld & Carter, 1998; Kadushin, 2012). In other world, people live by forming bonds wherever they land.
If the policy lumps the new cliques (core and periphery) together, network membership can change over time. Teens that tie together two completely separate networks are called bridges. By theory, the networks would not have connected if not for this new bridge. Often the bridge has enough prestige and power to convince two divergent groups to join forces (Granovetter, 1973). Will the new members from the outside possess adequate social currency to offset the peer influence of the core members? Thus we have complexity. Can one policy that is meant to affect teens as if they share the same life chances and social embeddedness work? Most likely answer is no. While there may be an overarching goal set up the policy, parse out how different attributes of the teens may affect how the proposed policy works.
The longer a teen is away, it becomes more likely that their family will be in the same dire social straits and may not be protective in navigating good social choices and decisions. But the longer a teen is away, human nature requires connection and closeness, a family broadly defined. Being on the outside (periphery) of the homeless core protects against HIV risk-taking. Let us not forget a social purgatory between the instability of homelessness and the perceived caustic environment that the teen desperately calls to escape. The peripherals may be at risk in other ways that may lead to a greater risk of HIV risk taking once the teen is in the core. But if that teen has the ability to persuade those at risk, there is a possibility that the low risk taking of a strong teen could start to cascade low risk attitudes and values. But there is also a possibility that the teen will become enveloped and become high risk himself. It may be too much to ask of that teen to work to overhaul the collectively held value of higher risk sexual practices (Long et. al., 2013).
So in using the research on social networks, I propose systemic factors that should be accounted when attacking HIV among homeless teens:
1. Every homeless teen is not the same and each with present a different set of connections.
2. Being deeply connected in the homeless culture may place these teens at higher risk for unsafe sexual behaviors.
3. Targeting low risk teens on the periphery will require a different intervention to support the low risk behavior.
4. While there may be opportunities to use low-risk teens as “bridges” to the high-risk teens, this should only be done with extreme care and oversight. The bridge is more susceptible to falling into the activities of the core and may suffer from burn-out for the heightened sense that change is on that teen’s shoulders.
5. Watch the movement of teens from the core to periphery (and back again). This movement brings a whole new set of structural realities both for the teen as well as the network.
Social networks are powerful and are often underutilized in uncovering the underlying structure of health policies. But the policy work that we should hold dear must account for the power to combatting ecological gaps and failures, such as the personal and societal failing of just one homeless teen.
Feld, S. & Carter, W. (1998). “Foci of Activities as Changing Contexts for Friendship.” In
Placing Friendship in Context, eds. Rebecca G. Adams and Graham Allan. Cambridge,
UK: Cambridge University Press.
Granovetter, M. (1973). The strength of weak ties. American Journal of Psychology. 78 (9),
Kadushin, C. (2012). Understanding Social Networks. New York: Oxford.
Long, J., Cunningham, F. & Braithwaite, J. (2013). Bridges, brokers and boundary spanners in collaborative networks: a systematic review BMC Health Services Research 2013, 13:158
Rice, E., Barman-Adhikari, A., Milburn, N. & Monro, W. (2012) Position-Specific HIV Risk in a Large Network of Homeless Youths. American Journal Of Public Health. 102(1), 141-147.
NOTE: This white paper is a revision of a blog written by the author. An early version was originally posted on the Orgcomplexity Blog (Orgcomplexity.wordpress.com) on February 28, 2013.
Invitations for submissions for
Arts, Humanities, and Complex Networks
— 5th Leonardo satellite symposium at NetSci2014
taking place in Berkeley at the Clark Kerr Campus of the University of California,
on Tuesday, June 3, 2014.
Deadline for submission: March 28, 2014.
TO SEE PAPERS PRESENTED AT LAST FOUR CONFERENCES SEE
I have actually been approached as to why I have not posted on Orgcomplexity as much in recent months.
There is actually a very good reason.
I am ready to announce that my single-authored book that brings systems thinking to health policy and ethics is under contract with Springer. It will be a part of the inaugural SpringerBriefs series in Public Health Ethics. I will keep everyone updated with the publication details in the next few months. The target for publication is mid-2014.
Thank you for supporting Orgcomplexity and I hope that you will continue to follow my book progress over the coming months.
All the best,
Registration is now open for SBP14, the 2014 International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction.
SBP14 will be held at the UCDC Center, downtown Washington DC, USA April 1 – 4, 2014.
Link to the main conference pages, http://sbp-conference.org/
*** Please note that early registration deadline is March 8, 2014. ***
Link directly to registration page, http://sbp-conference.org/registration/
SOME EXCITING ITEMS ON THE PROGRAM!
SBP 2014 CHALLENGE – see: http://sbp-conference.org/challenge/
The SBP Challenge aims to demonstrate the real-world and interdisciplinary impact of social computing. The challenge will engage the social computing research community in solving a relevant, interesting, and challenging research problem that will advance the theory, methodology, and/or application of social computing.
TUTORIALS – see: http://sbp-conference.org/tutorial/
Morning and afternoon tutorials are offered on Tuesday, April 1 (included with registration fee):
(1) Modeling a Mobile World
Wendy J. Nilsen, PhD, Health Scientist Administrator, Office of Behavioral and Social Sciences Research/NIH
Stephen Intille, PhD, Associate Professor, College of Computer and Information Science & Dept. of Health Sciences, Bouvé College of Health Sciences, Northeastern University
Donna Spruijt-Metz, MFA, Ph.D, Director, Mobile and Connected Health Program, Center for Economic and Social Research, Associate Professor, Departments of Preventive Medicine and Psychology, University of Southern California
Misha Pavel, PhD, College of Computer and Information Science, Bouvé College of Health Sciences, Northeastern University
(2) Introduction to social data analysis combining R and Python
Presenter: Dr. Jose Manuel MAGALLANES, Center for Social Complexity, George Mason University, and Departamento de Ciencias Sociales, Pontificia Universidad Católica del Perú
(1) Multiscale Strategic Interaction with vmStrat Models
Presenter: Dr. David Sallach, Associate Director, Center for Complex Adaptive Agent Systems Simulation (CAS), Argonne National Laboratory; Senior Fellow, Computation Institute, The University of Chicago
(2) Charting Collections of Connections in Social Media: Creating Maps and Measures with NodeXL
Dr. Marc A. Smith, Chief Social Scientist, Connected Action Consulting Group
For a full description of tutorials, see: http://sbp-conference.org/tutorial/