Another one of those studies comparing political identification. The study is about extreme attachment to a Party. What about those who strongly identify with humanity with high cognitive complexity and flexibility who don’t identify with a Party? Are their nuanced arguments that account for numerous factors and their interplay ‘extreme?’ Is the Green New Deal extreme? If a living wage extreme? Is corporations paying their fair share extreme? Is addressing the climate crisis extreme? Is transitioning from fossil fuels to renewable energy extreme? I think we all know the answer to those questions.
“They also found that self-described Independents displayed greater cognitive flexibility compared to both Democrats and Republicans. Other cognitive traits, such as originality or fluency of thought, were not related to heightened political partisanship. […] The aim of this research is not to draw false equivalences between different, and sometimes opposing, ideologies.”
According to this study in Nature Human Behavior, in time frames about fairness and preventing harm triumph over those about loyalty, purity and authority. The latter might succeed temporarily, like now in the US, but the more the former frames are strongly and repeatedly reinforced the quicker the results. Let’s keep up our passionate frames, for this research supports that we will overcome the dark forces that have a temporary hold on our government. Also see Kohlberg‘s moral stages, showing that the former frames are more developed that the latter set.
“Their conclusion is that the key characteristic of opinions that gain ground is that they are supported by arguments about what is fair and what does not cause harm to others. […] Opinions based on other classical grounds used to determine right and wrong actions—loyalty, authority, purity, religion—can gain support temporarily, but over time, opinions based on these arguments lose support all over the political spectrum. The stronger the connection an opinion has to arguments about fairness and harm, the greater the probability that it will gain ground in public opinion. Also, the stronger the connection is, the faster the change will come.”
We’ve seen quite a few descriptions of an emerging paradigm known as the collaborative commons (CC). But a problem arises when we take another step by extrapolating from that data and then try to prescribe what we need to do in order to create a CC. I.e., we form a model of what the CC should be, and top down we try to implement it. Whereas the technology that enables the CC to grow organically has no apparent need of this top down imposition. To the contrary, it seems more of a capitalistic holdover instead of the middle out way the CC is naturally evolving.
Bonnita Roy has noted that “In a world as diverse in people and rich in meanings as ours, big change might come from small acts by everyone operating everywhere in the contexts that already present themselves in their ordinary lives.” It is quite the contrast from the enlightened heroes figuring it all out from their complex ivory towers which supposedly and hopefully ‘trickles down’ to the rest of us. This seems much more how the CC works in practice. Political and social revolution arises from the external socioeconomic system, the mode of production. Development is accomplished not by having a ‘higher’ model to which one must conform, but by the actual practice of operating within the emerging socioeconomic system.
Jennifer Gidley noted a similar phenomenon in that there is a difference between research that identifies postformal operations from those who enact those operations. And much of that research identifying it has itself “been framed and presented from a formal, mental-rational mode.” Plus those enacting postformal operations don’t “necessarily conceptualize it as such.” So are those that identify postformality via formal methodology really just a formal interpretation of what it might be? Especially since those enacting it disagree with some of the very premises of those identifying them?
The online discussions I engage with on meta-models is representative of this difference. It seems the abstract modeling of the development of the CC is what is operating to create it in a top-down manner. Not only that, what appears to be happening in all cases is that not only does each individual have their own thoughts and opinions on the topic, which is to be expected in diverse groups, we all end up justifying our own take over others. We all seem to be so attached to our own discoveries that we build an edifice and seek out and find supporting evidence to justify it. When confronted with different perspectives or evidence, our first inclination is to see how it fits into our own model or worldview, how we can twist and manipulate it to support our biases. What is there in common that holds us together if we are so closed to taking in new information from other perspectives, allowing them to sit in their own right, their own space, instead of trying to fit them into our own predispositions?
I’m reminded of what Said Dawlabani said, that the distributed network of the collaborative commons follows no ideologies. That it is open source, highly networked and depends on the wisdom of the crowd. I’m guessing that equally applies to our models on trying to create the CC, as we tend to idealize and attach to them. Is our ownership of our ideas more indicative of capitalism that the CC? It also seems that those who are enacting this new paradigm are doing so without need of any explicit theory or model about it. So is arguing about the correct theory even a necessary part of its enactment, as if like capitalism it too needs a top down elite model to implement it? Are our models just getting in the way and actually counter-productive to its natural evolution?
“There is not one, but at least four, hereditary systems recognized by biologists today. Eva Jablonka and Marion Lamb lay this out clearly in their 2006 book, Evolution in Four Dimensions, as they walk through the research literature on genetics, epigenetics, behavioral repertoires, and symbolic culture as four distinct pathways where traits are ‘heritable’ in appropriately defined fashion.”
“Specifically, I am thinking of three areas where significant progress has been made during the last forty years: the birth of complexity science in the early 1980’s, developments in the study of human conceptualization and cognitive linguistics since the mid-70’s, and the explosion of digital media in the age of personal computers and later via the internet.”
“Applied to meme theory, this body of tools and techniques [cognitive linguistics] demonstrates that researchers across many fields have found value in the perspective that culture can be studied as information patterns that arise in a variety of social settings routinely and with modular elements that are readily discernible in each new instance. The claim that information patterns do not replicate is contradicted by the evidence for image-schematic structures.”
New draft paper by me. Update: Published here. The abstract:
A ‘power law’ refers specifically to a statistical relationship between quantities, such that a change in one quantity has a proportional change in another. One property of this law is scale invariance, otherwise known as ‘scale-free,’ meaning the same proportion repeats at every scale in a self-similar pattern. Mathematical fractals are an example of such a power law. Power laws are taken as universal and have been applied to any and all phenomena to prove the universality of this law.
However, a recent study (Broido and Clauset, 2019) claims that “scale free networks are rare.” They conducted an extensive review of one thousand social, biological, technological and information networks using state of the art statistical methods and concluded what the title of their article states. To the contrary, “log-normal distributions fit the data as well or better than power laws.” And that scale-free structure is “not an empirically universal pattern.” Hence it should not be used to model and analyze real world structures.
Recent book by Wuppulari and Doria. F___ing Amen man. This would be a good one for discussion. From the Intro by Penrose:
“Is there a global map that can simulate every other map under some constraint? […] If two maps cannot be integrated, is this a limitation of our scientific cartography or is it the nature of the underlying territory itself that prevents us from such an attempt? […] It is safer to let the gaps remain as gaps while we let our maps remain as maps, rather than giving in to the seemingly seductive approach of trading in our understanding and intermingling maps with territory to fill in the conceptual gaps—however, much this may comfort us and appeal to our tastes!”
From the blurb at b-ok.org: This volume presents essays by pioneering thinkers including Tyler Burge, Gregory Chaitin, Daniel Dennett, Barry Mazur, Nicholas Humphrey, John Searle and Ian Stewart. Together they illuminate the Map/Territory Distinction that underlies at the foundation of the scientific method, thought and the very reality itself.
It is imperative to distinguish Map from the Territory while analyzing any subject but we often mistake map for the territory. Meaning for the Reference. Computational tool for what it computes. Representations are handy and tempting that we often end up committing the category error of over-marrying the representation with what is represented, so much so that the distinction between the former and the latter is lost. This error that has its roots in the pedagogy often generates a plethora of paradoxes/confusions which hinder the proper understanding of the subject. What are wave functions? Fields? Forces? Numbers? Sets? Classes? Operators? Functions? Alphabets and Sentences? Are they a part of our map (theory/representation)? Or do they actually belong to the territory (Reality)? Researcher, like a cartographer, clothes (or creates?) the reality by stitching multitudes of maps that simultaneously co-exist. A simple apple, for example, can be analyzed from several viewpoints beginning with evolution and biology, all the way down its microscopic quantum mechanical components. Is there a reality (or a real apple) out there apart from these maps? How do these various maps interact/intermingle with each other to produce a coherent reality that we interact with? Or do they not?
Does our brain uses its own internal maps to facilitate “physicist/mathematician” in us to construct the maps about the external territories in turn? If so, what is the nature of these internal maps? Are there meta-maps? Evolution definitely fences our perception and thereby our ability to construct maps, revealing to us only those aspects beneficial for our survival. But the question is, to what extent? Is there a way out of the metaphorical Platonic cave erected around us by the nature? While “Map is not the territory” as Alfred Korzybski remarked, join us in this journey to know more, while we inquire on the nature and the reality of the maps which try to map the reality out there.
The book also includes a foreword by Sir Roger Penrose and an afterword by Dagfinn Follesdal.
Yes, space exploration is critical but we need to do it for the right reasons. And Bezos and other futurists want it without awareness or regard for the socio-economic system that has created hell on earth. So dump the earth and take our destruction into space? How about we change our worldview and socio-economic system and do it for the right reasons? And invest most of our time, energy and money into saving this world?
“The saying ‘it’s easier to imagine the end of the world than to imagine the end of capitalism’ is very clear in Bezos’ future imaginings. He is unable to challenge the capitalist system from which he’s derived so much wealth. Thus the only positive future he can imagine involves leaving the only planet habitable to human beings. […] We don’t need space colonies; we need to get rid of billionaires and let the future be decided collectively, instead of letting a few powerful men rule the world.”
Their are alternatives to capitalism consistent with the above. As but one example see “From capitalism to the collaborative commons” in this journal issue.
Reich explains that narrative is necessary to provide a structure to belief systems. Just telling the truth is not enough without the right story. He breaks down the 4 major stories Americans have operated within: the triumphant individual; the benevolent community; the mob at the gates; the rot at the top. All four can be told with the truth or with lies. Reich provides examples and how the Dems abandoned some of these stories, while the Repugs maintained the negative versions. So how do progressives regain the truth of these four stories? Hint: Sanders, AOC and their ilk are doing exactly that.
Ideally, automation would yield a Star Trek reality of increasing leisure and quality of choice and experience. Why isn’t this our experience? An article on Medium offers insight into why this is not occurring on any significant scale.
Evolved behavioral strategies explained by the prisoner’s dilemma damn the majority of humans to a constant doubling down. We exchange the ‘leisure dividend’ (free time) granted by automation for opportunities to outcompete others.
Apparently, the sort of reciprocal social learning that could lead us to make healthy choices with our leisure opportunities depends on us and our competitors being able to mutually track our outcomes across consecutive iterations of the ‘game’. That ‘traceability’ quickly breaks down with the complexity inherent in vast numbers of competitors. When we conclude that any viable competitor may use her leisure dividend to further optimize her competitive position, rather than to pause to enjoy her life, we tend to do the same. Each assumes the other will sprint ahead and so chooses to sprint ahead. Both forfeit the opportunity to savor the leisure dividend.
The prisoner’s dilemma shows that we (most humans) would rather be in a grueling neck-and-neck race toward an invisible, receding finish line than permit the possibility a competitor may increase her lead.
Any strategy that’s so endemic must have evolutionary roots. Thoughts?
“Sometimes a good idea isn’t enough to drive social change; more important is how you communicate that idea. This is where “issue framing” comes in. In his talk, Nat Kendall-Taylor, PhD, breaks down the science of framing for philanthropy and nonprofit communications. He explores how people think about social issues and how advocates, experts, and strategic communications professionals can use an understanding of culture, storytelling, and science to communicate about social and scientific issues, shape policy, and lead change.
“Dr. Kendall-Taylor is an anthropologist and Chief Executive Officer at the FrameWorks Institute. He oversees the organization’s pioneering, research-based approach to strategic communications and message development, which uses methods from the social and behavioral sciences to measure how people understand complex socio-political issues and tests ways to reframe them to drive social change. As CEO, he leads a multi-disciplinary team of social scientists and communications professionals who investigate ways to apply innovative framing research methods to social issues and train nonprofit organizations to put the findings into practice.”