Very bad definition, suggesting that you don’t know what it means. I fail to be surprised.
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Why don’t you try to improve it?
Sure. But can we agree that you don’t know?
A nested hierarchy is a group of sets, each pair of which has one of two relationships: either one is a proper subset of the other or the two are disjunct. I suppose it is also necessary that every set but one be a proper subset of some other set.
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We can agree that I did not try to make a strict mathematical definition for FG and I agree your understanding is superior to mine. Can we agree that life approximates the strict mathematical definition of a nested hierarchy? Here is chat GBT’s take.
A nested hierarchy refers to a hierarchical structure where each level contains subordinate or nested elements within it. It is a system of organization where objects or concepts are grouped and organized based on their relationships and levels of abstraction. Each level of the hierarchy represents a broader or more general category, while the nested elements within each level represent more specific or detailed subcategories.
A commonly used example of a nested hierarchy is the biological classification system known as Linnaean taxonomy. In this system, organisms are classified into a hierarchical structure consisting of several levels, including kingdom, phylum, class, order, family, genus, and species. Each level encompasses a more specific subset of organisms within the broader category above it.
Nested hierarchies are also prevalent in computer programming, particularly in data structures. For instance, a tree data structure is a type of nested hierarchy where each node can have child nodes that further branch out. This structure is used in various applications like file systems, organization charts, and database indexing.
Overall, a nested hierarchy provides a systematic way to categorize and organize information or objects by their relationships and levels of abstraction, allowing for easier navigation, classification, and understanding.
The other example here in bold is a product of design.
We can agree that your attempted definition was pretty much useless and showed that you have no real idea what “nested hierarchy” means. I don’t care what “chat GBT” or even “Chat GPT” says, and neither should you. Still, it did better than you did, so that’s something.
Sure. You can make up a tree structure. But that’s just the equivalent of a tree diagram. It’s not a tree structure that emerges from the data. Whole different thing. Don’t rely on AI for an understanding of anything. Hey, if you can’t understand what other people are saying, what makes you think you can understand what AI is saying? AI doesn’t even understand what it’s saying.
So, what we see is that you don’t understand anything about nested hierarchy except that you can recognize the words when you see them.
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How is it not a tree structure that emerges from the data?
Because it’s just defined to be a tree structure. The geological eons, eras, periods, and ages form a nested hierarchy too, but that’s just because they’re defined that way. They don’t emerge from hierarchically structured data like the tree of life does. Just because you can find the word hierarchy mentioned here and there doesn’t make any sort of point for you.
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Was the original classification system (Linnaean taxonomy) the same as the geological nested hierarchy?
Is your claim “emerge from hierarchically structured data” based on phylogenetic analysis?
It is not clear that a nested hierarchy from data structures is not “emerging from hierarchically structured data”.
No.
No.
It is clear. I could try to explain all this, but it doesn’t seem worth the effort.
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This is why I don’t bother with colewd. He’s either massively ignorant or deliberately pretending to be.
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Maybe you could define what “emerging from hierarchically structured data” means? Do you think this was true during the time of the original classification system?
It means that the individual data points, the homologous characters, mutually define a nested hierarchy. A set based on character A has a nested hierarchical relationship with a set based on character B, C, D, etc.
Yes.
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Thanks
Why don’t you think this can occur in computer data structures?
It’s always possible, but the examples I know of consist of sets of structs, each with a pointer to two other structs, with the pointers set so that the structs form a tree. This is merely a formal representation of a tree but has nothing to do with any data. Perhaps you know of something else, but since you don’t know what a nested hierarchy is it would seem difficult for you to recognize one.
Can occur =/= is likely to occur consistently as a byproduct of a design-process centered around functionality.
Of course nesting structure can occur by chance in any kind of data whether designed or not, but there is a question of how often (out of how many times you design something would you expect a nested hierarchy?), how consistent it is (does different and independent parts of the data converge on the same or very similar hierarchy?), and how much of the data (is it only a tiny portion with a few pieces, or enormous amounts of data?) would conform to such a pattern.
There is no a priori reason why design should produce a nested hierarchy at any appreciable frequency, that it should be consistent among different subsets of the data, nor that any significant portion of a large amount of data would form the hierarchy, as a byproduct of designing for function.
Nested hierarchies are expected from branching genealogical processes, so if some sort of algorithmic implementation of a branching genealogical process is part of the design process, there could very well be a nested hierarchy forming in some of the data. But then it would also be true to say that data is forming a nested hierarchy because it really does share common descent.
All of this has been explained to you before. Many, many, times.
Maybe there are no conditions you can think of.
Living organisms share many of the same functions (ATP generation, reproduction etc. and many of the same components (genes, organelles etc). Why wouldn’t a nested pattern as John described consistently form from different designs given these constrains?
While a branching pattern of descent may form a nested pattern there is no guarantee that it will form the pattern we are observing.
That is why what we observe is a remarkable confirmation of branching descent.
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Please, explain. What is this “the pattern we are observing” if it is anything other than or beyond “a nested pattern”? What other properties does it have that are not consistent with a descent model? What other properties does the descent model predict that “the pattern we are observing” does not have? What is the actual difference between expectation and reality, assuming descent, and which alternative, in your opinion, provides a better match against the data collected until some point along with more accurate predictions at said point of data collected past said point?
You can’t seem to think of any either.
Of course, we actually know why there are no such conditions. It’s that there are many more ways for the data to fail to conform to a nested hierarchy, than there are for it to conform. There are many more possible patterns in the data than nested hierarchies. That means to get a nested hierarchy something must push the data in that direction. Merely sharing similar parts doesn’t do that.
Because merely sharing parts can produce many other patterns than nested hierarchies. That would leave parts-sharing to produce nested hierarchies as an accidental byproduct, which is a priori much less likely than not producing a nested hierarchy. So we would expect there not to be a nested hierarchy merely from similar parts-sharing.
Nobody says the particular tree we do have is a guarantee of a process of common descent. But it doesn’t have to be, any more than any particular mountain—such as the Matterhorn—has to be a guarantee of the process of tectonic plate collision leading to mountain range formation.
Any particular tree of life, as any particular mountain, any particular grain of sand, or the shape of any particular river at some moment in time, will be contingent on previous historical circumstances. Nevertheless, we expect trees from common descent, mountains from plate tectonics, and so on.
The pattern also follows a dependency graph at the gene level. The data fits a dependency graph better than a tree according to Winston Ewerts paper.
http://dx.doi.org/10.5048/BIO-C.2018.3
Large divergence in gene patterns and chromosome counts.
It should predict the genes follow the tree but convergent evolution is an exception to this.
My expectation with a common descent model for deer would be that the gene patterns and chromosome counts would be almost the same among species.
The better explanation is separate origins for most deer species.
I would not expect much change in genetic makeup based on what we know about reproduction. What we see today should be very close to the original design.