Cognitive Type as an Expansive Model
May 14, 2016 14:18:53 GMT -5 by Auburn
Alerith, sitbone, and 4 more like this
Post by Auburn on May 14, 2016 14:18:53 GMT -5
Article: cognitivetype.com/how-to-approach-incoming-data/
Addendum/Note...
After spending some time outside of myself, I remember now what I meant to say a long time ago but never did. I hope I can clarify here.
One of the things that's bugged me about CT, and which I've found hideous about it, is that I sometimes find myself conflicted with the data, and tempted to squeeze things into a best-fit typing at the omission of some extraneous data. Admittedly, I still find CT to have a lot less of this effect than mainstream typology -- where confirmation bias has no methodology for filtration.
But I realize now that this has happened because of a conflict between the compartmentalization and delineation of Judgment, and the organic and chaotic flux of perception.
I am a judgment type and I tend to want to formulate a concise mathematical architecture that can account for everything. Think of it like building up a grammar structure for a language. But no matter how neatly things fit on paper, in practice there are a lot of exceptions... the same way languages have a lot of rule-breaking.
I believe this is because reality is.... simultaneously fractal and chaotic. The most complex organic systems like genetics, physics or language have this same combination of being elegantly algorithmic but filled with exceptions. And the only/best way to study these topics is with a methodology that is open-ended.... but which still seeks for structure.
~ State of Things ~
The problem with typology at present is that it is a closed system. Every model out there is trying to approximate a phenomenon, but the lack of actual, dynamic input makes it capable of staying crystalline and static.
So you either have people who believe in the fractal wholeheartedly, or those who rebel and take the "chaotic" opinion and say "typology is bs because we're all different and can't be accounted for with a simple model".
The thing is, both of them have a point, but those who believe everything is up for grabs and we're all just different individuals with differences that don't ever cluster into parallels or patterns, are being overly simplistic in their own chaotic stance. And those who go the algorithmic route are too dead-set on their structure.
The balance, and the balance all proper fields of study have, is in seeking to expand our awareness of the structure of things (and developing a working structure) even though we can never definitively assert it to be 100% right.
Now that the book is out, the original argument is made -- primarily for the purpose of being broken down and relativized. But at least this way, a channel has been opened toward a field of study with the capacity to evolve/grow in a transformative way via real and endless data. Or so is my hope.
Addendum/Note...
After spending some time outside of myself, I remember now what I meant to say a long time ago but never did. I hope I can clarify here.
One of the things that's bugged me about CT, and which I've found hideous about it, is that I sometimes find myself conflicted with the data, and tempted to squeeze things into a best-fit typing at the omission of some extraneous data. Admittedly, I still find CT to have a lot less of this effect than mainstream typology -- where confirmation bias has no methodology for filtration.
But I realize now that this has happened because of a conflict between the compartmentalization and delineation of Judgment, and the organic and chaotic flux of perception.
I am a judgment type and I tend to want to formulate a concise mathematical architecture that can account for everything. Think of it like building up a grammar structure for a language. But no matter how neatly things fit on paper, in practice there are a lot of exceptions... the same way languages have a lot of rule-breaking.
I believe this is because reality is.... simultaneously fractal and chaotic. The most complex organic systems like genetics, physics or language have this same combination of being elegantly algorithmic but filled with exceptions. And the only/best way to study these topics is with a methodology that is open-ended.... but which still seeks for structure.
~ State of Things ~
The problem with typology at present is that it is a closed system. Every model out there is trying to approximate a phenomenon, but the lack of actual, dynamic input makes it capable of staying crystalline and static.
So you either have people who believe in the fractal wholeheartedly, or those who rebel and take the "chaotic" opinion and say "typology is bs because we're all different and can't be accounted for with a simple model".
The thing is, both of them have a point, but those who believe everything is up for grabs and we're all just different individuals with differences that don't ever cluster into parallels or patterns, are being overly simplistic in their own chaotic stance. And those who go the algorithmic route are too dead-set on their structure.
The balance, and the balance all proper fields of study have, is in seeking to expand our awareness of the structure of things (and developing a working structure) even though we can never definitively assert it to be 100% right.
Now that the book is out, the original argument is made -- primarily for the purpose of being broken down and relativized. But at least this way, a channel has been opened toward a field of study with the capacity to evolve/grow in a transformative way via real and endless data. Or so is my hope.
