I'm listening to a podcast from Complexity by the Santa Fe Institute entitled "Mirta Galesic on Social Learning & Decision-making" in which Galesic, SFI Professor & Cowan Chair in Human Social Dynamics, discusses her work into "how simple cognitive mechanisms interact with social and physical environments to produce complex social phenomena…and how we can understand and cope with the uncertainty and complexity inherent in many everyday decisions". I think I can draw some important points about rhizo narratology from both her discussion and a couple of her scholarly articles.
Galesic does not address narrative directly; rather, she explores how people work within and through social networks to address issues in their lives. Along the way, she addresses how the beliefs and behaviors of people spread through a social system, informing and perturbing it. Throughout her discussions, she assumes that social systems are complex, self-organizing entities that both inform and outform to create their own identities within their ecosystems. This works very well for my concept of rhizo narratology which posits that narratives are linguistic entities that inform and perturb the complex social systems within which they find echoing expression. Stories encode how a social system sees itself, how it chooses to behave and believe, and how it engages its ecosystems, including other social networks. My reading of Galesic and her co-researchers allows me to express this view of the function of narratives more succinctly than I have until now, but I think I can glean some more nuggets from her discussions. As always, keep in mind that I make no claim that Galesic would approve of any of my ideas about rhizo narratology. Rather, I use her ideas to spark my own.
First, I like Galesic's use of the trade-off between exploitation and exploration to frame how beliefs and behaviors propagate through a social system – or in my case how narratives propagate. This trade-off refers to the dilemma of how to allocate resources between trying new things (exploration) and sticking with what is known to work (exploitation). In their article "Social learning strategies modify the effect of network structure on group performance", Barkoczi and Galesic argue that the balance between exploration and exploitation is crucial for group performance, and that any given balance emerges from the dynamic interactions of the social learning strategies used by individuals, the structure of the network in which they are embedded, and the relative complexity of the task they are addressing. They say:
We show that efficient networks outperform inefficient networks when individuals rely on conformity by copying the most frequent solution among their contacts. However, inefficient networks are superior when individuals follow the best member by copying the group member with the highest payoff. In addition, groups relying on conformity based on a small sample of others excel at complex tasks, while groups following the best member achieve greatest performance for simple tasks.
I can easily adapt their insights to rhizo narratology: Efficient networks outperform inefficient networks when individuals rely on conformity by echoing the best, usually most frequent stories among their contacts. This makes great intuitive sense to me. As I understand it, efficient social networks are composed of people who share significant characteristics: language, organizations, practices and rituals, dress, goals, worldviews, and so forth. Such homogeneous networks present fewer barriers to the propagation of memes such as stories that embody the group's worldviews. Of course, Evangelicals are an efficient network, but so are neurosurgeons, Starbucks baristas, Cobol programmers, feminists, army platoons, and Man City futbol players. We humans form many efficient networks to harness the power of various groups to play and work, and most of us belong to several or many such networks. Stories circulate quickly within these efficient networks, and because the stories resonate within a group that we choose and identify with, we tend to accept them and retell them. Stories tend not to circulate within a group unless they echo and reinforce the views of the group.
I tend to dismiss this efficient network behavior as an echo chamber, but Barkoczi and Galesic remind me that when a group is addressing a simple problem, a problem with one or very few known, optimum resolutions, then this efficiency makes great sense and works very much in favor of the group. The group can respond quickly to a problem and move on about its business. A group can use its accepted stories to frame an issue and respond appropriately from its point of view. However, this efficiency is undermined when the group mistakes a complicated or complex problem for a simple problem. People are prone to frame an issue as simple rather than as complicated or complex, and groups may be more prone to this behavior.
In her interview with SFI host Michael Garfield, Galesic notes that people are not as biased as we commonly believe, especially about those people in their own social networks. She says:
People are not that biased when it comes to judging their immediate friends. They have a lot of useful information about their friends. And pretty accurate. The biases show up when people are asked about other populations that they don't know so well, and they can be mostly explained by the structure of their own personal social networks. The more biased your social networks are, the more biased your estimates will be about the general population. … these kind of biases of judgements of the broader population can be explained by the structure of [the] social network and not by some cognitive deficits or motivational bias, [by] some desire to be better than others or some idea that everybody's like me or some cognitive deficits that people … are too stupid to understand how other people live. It's really determined by the context of memory — by the content of one's memory, which comes from one social circle.
If she is correct, then I must correct my own tendency to assume and to say that people who follow Donald Trump must be stupid, cognitively deficient in some way, or blinded by some false rhetoric or story. Their simplistic bias toward Trump and away from correct-thinking progressives (my group, of course) is more likely a function of their social networks rather than of their personal intellectual disabilities.
Just as my biases are. Ouch.
Our biases of judgement often follow not from any personal mental defects, then, though such defects do exist, but from the memories we form and rely on within our social networks. Our social networks help us identify which features of our landscapes are significant and how and why – think informal and formal education here – and we usually learn and remember those features within the frame of some narrative, even if it's a narrative as simple as how to get from the house to the food store and back (instructions on GPS) or as complex as how to make a successful life as a young black woman in rural Georgia (The Color Purple). Our social networks give us the stories that we live by, and most of us accept those stories whole cloth. Even if we eventually challenge and abandon our earlier family, school, and church stories, we spend much of our lives working through and within those stories to make sense of our lives.
Our biases are often directed toward those outside our own groups. Galesic says, "People are not that biased when it comes to judging their immediate friends." Proximity has its privileges, and we tend to have rich, nuanced knowledge about those we most interact with. We do not have that same rich network of memories about other people outside our networks. Moreover, we have stories about those people which simplify them into more easily managed and addressed stereotypes that gloss over the paucity of our information about them. And we all do this to some extent, especially when an issue requires an immediate response. In times of crisis, we tend to reduce an issue to a simple binary: fight or flight, good or bad, buy or sell. This can work to our advantage, but in complex human social networks, it can just as often land us in hot water.
Barkoczi and Galesic note that inefficient networks – those composed of diverse heterogeneous agents – are more effective for addressing complex issues with no single, known resolution as inefficient networks are more likely to contain individuals with diverse information and strategies, which can lead to more creative effective solutions. This leads me to believe that inefficient, heterogeneous networks propagate a wider range of stories that are less widely accepted by the people within the network. The advantage of a greater variety of stories is that the heterogeneous social network is able to address a greater number of complex issues than can a homogeneous social network.
However, Barkoczi and Galesic note that this relative advantage of inefficient networks depends on the social learning strategy used by the agents within the network. If individuals are using a conformity strategy, then efficient networks are more effective because they allow individuals to copy the solutions of others quickly and easily. Thus, efficient, homogeneous networks tend to have fewer stories that address simpler issues, and as a result, those networks can act more quickly and decisively than can heterogeneous, inefficient networks.
I'm disturbed, however, by Barkoczi and Galesic's distinction between simple and complex issues. They define simple tasks and complex tasks based on the number of optimal solutions. A simple task is one that has a single optimal solution, while a complex task has multiple optimal solutions, including one global optimum and several local optima. I prefer the more nuanced understanding of Dave Snowden's Cynefin framework which categorizes issues from simple with one optimal approach and resolution, through complicated, then complex, and finally chaotic issues with no optimal approaches or resolutions.
I am troubled by the tendency in society to reduce all issues to the simple domain, often a simple binary: us/them, good/evil, right/wrong, male/female, black/white, and countless others. Popular self-help often advises us to simplify life, to lead a simple life. I understand this drive, as complexity implies a constant tension: intellectual, emotional, social, technological, physical, and so on. Complexity can be exhausting; yet, I believe life to be complex. To my mind, simple systems are the rare exception to the complicated, complex, and chaotic domains. Without constant attention and maintenance, any simple domain will give way to the complicated, complex, and chaotic domains.
It seems to me, then, that stories arise and propagate easily throughout efficient, homogeneous networks, such as Evangelicals, because those networks have few barriers to stories that echo and reinforce their beliefs and because Evangelicals tend to echo the stories that their fellow Evangelicals believe. Evangelicals tend to a simple, binary view of life: good and bad, us and them, saved and sinner, holy and profane, Heaven and Hell. This makes them very efficient and coherent. They are able to respond to most socio-political issues quickly and forcefully, unlike progressives who must muddle through a fragmented world-view. The right stories told well can spread quickly through Evangelical circles. However, Evangelicals are more susceptible to misreading a complex situation and to misapplying a simplistic response.
Obviously, I will need to find evidence to support these ideas, but I think that I can do it.
Finally, it's been months since I last posted to this blog, and I apologize to those who have followed it until now. I have been writing lots of fiction since the summer and fall of 2023, and I've been applying many of the lessons about rhizo narratology to my stories. I won't publish my stories on this blog as that can interfere with publishing them in other venues, but I will begin to discuss the stories in terms of rhizo narratology.
