for - quote / insight - decreased resiliency due to tight network of elites - From Complex Regions to Complex Worlds Crawford Stanley Holling - 2004 - creative alternatives - liminal spaces - rapid whole system change

quote / insight - decreased resiliency due to tight network of elites - (see quote below) - The front-loop phase is more predictable, - with higher degrees of certainty. - In both the natural and social worlds, - it maximizes production and accumulation. - We have been in that mode since World War II. - The consequence of this is not only an accumulation and concentration of wealth, - but also the emergence of greater vulnerability because of - the increasing number of interconnections that link that wealth, and - those who control it, - in efforts to sustain it. - Little time and few resources are available for alternatives that explore different visions or opportunities. - Emergence and novelty is inhibited. - This growing connectedness leads to increasing rigidity in its goal to retain control, - and the system becomes ever more tightly bound together. - This reduces resilience and the capacity of the system to absorb change, - thus increasing the threat of abrupt change. - We can recognize the need for change but become politically stifled in our capacity to act effectively.

to - quote - we are now in a back-loop of a planetary adaptive cycle - From Complex Regions to Complex Worlds - Crawford Stanley Holling - 2004 - https://hyp.is/FTRDoJFuEe-rsvdKeYjr0g/www.ecologyandsociety.org/vol9/iss1/art11/main.html?ref=ageoftransformation.org

comment - These ideas are quite important for those change actors working to emerge creative alternatives - liminal spaces - rapid whole system change

Google translation:

The sheer quantity exceeds the possibilities of book publication, the complex, multidimensional structure of a networked information base cannot be reproduced in print, and finally the dynamic of a constantly growing and constantly correcting material does not fit into the rigid rhythm of book production, in which each expanded and corrected new edition is associated with an incalculable amount of effort. A book publication could only offer a snapshot of such a database, reduced to a specific perspective. This too can be very useful from time to time, but it does not solve the problem of publishing the entire material.

While the writing criticism of "dumping out one's zettelkasten" into a paper, journal article, chapter, book, etc. has been reasonably frequent in the 20th century, often as a means of attempting to create a linear book-bound context in a local neighborhood of ideas, are there other more complex networks of ideas which we're not communicating because they don't neatly fit into linear narrative forms? Is it possible that there is a non-linear form(s) based on network theory in which more complex ideas ought to better be embedded for understanding?

Some of Niklas Luhmann's writing may show some of this complexity and local or even regional circularity, but perhaps it's a necessary means of communication to get these ideas across as they can't be placed into linear forms.

One can analogize this to Lie groups and algebras in which our reading and thinking experiences are limited only to local regions which appear on smaller scales to be Euclidean, when, in fact, looking at larger portions of the region become dramatically non-Euclidean. How are we to appropriately relate these more complex ideas?

What are the second and third order effects of this phenomenon?

An example of this sort of non-linear examination can be seen in attempting to translate the complexity inherent in the Wb (Wörterbuch der ägyptischen Sprache) into a simple, linear dictionary of the Egyptian language. While the simplicity can be handy on one level, the complexity of transforming the entirety of the complexity of the network of potential meanings is tremendously difficult.

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Very nice review. Please note the reference [94] (Pantazatos et al.) is misplaced because they did not argue that spatial biases cannot entirely explain the putative links between CGE and functional segregation. Instead, they argued there was insufficient evidence in the original Richiardi et al. study linking elevated CGE with resting state functional networks, and that spatial biases may in fact entirely account for their findings. To describe the debate/exchange more accurately, I would suggest replacing the below sentence

“While spatial biases may contribute to these findings, as nodes belonging to the same module tend to be anatomically colocalized [7,8], they cannot explain these effects entirely [94,95].”

with the below paragraph:

“Spatial biases may contribute to these findings, as nodes belonging to the same module tend to be anatomically colocalized [7,8]. Pantazatos et al. argued that these findings are entirely explained by spatial biases [94]. They showed that elevated CGE, as defined in the original Richiardi et al. study, falls monotonically as longer distance edges are removed. Moreover, they showed that 1,000 sets of randomly spaced modules all have significantly high CGE when using the same null distribution defined in the original Richiardi et al. analyses. Therefore, elevated CGE is not specifically related to functional segregation as defined by resting state functional networks, which is in direct contradiction to the main conclusion of the original Richiardi et al. study. Since randomly placed modules do not align (spatially) with any distributed pattern of functional segregation, the finding of elevated CGE may instead be attributed entirely to anatomical colocalization of the nodes within each module. In their rebuttal to [94], Richiardi et al. argue spatial biases cannot explain their findings entirely [95]. However, the authors do not offer an explanation for significantly high CGE observed for randomly spaced sets of modules, other than to note that nodes tend to be closer on average compared to when modules are defined by resting state fMRI. Future work is required to dissociate the effects of spatially proximity on relationships between CGE and spatially distributed functional networks.”