FEATURED AUTHOR - After graduating from Duke University, Glen Dawson owned and operated a flexible packaging manufacturing plant for 23 years. Then, he sold the factory and went back to school to get his Master's degree in biostatistics from Boston University. When he moved to North Carolina, he opened an after-school learning academy for advanced math students in grades 2 through 12. After growing the academy from 30 to 430 students, he sold it to Art of Problem Solving. Since retiring from Art of Problem…
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Recent comments: User reviews
This is a non-scientific book which pretends to be scientific. One indication of this is the total lack of citations. The author reasons in the book that it describes a fundamental model and hence does not need citations. This might be correct if he would just develop the model. Yet, perhaps 80% of the book are examples that try to apply the model (in a quite repetitive way) to "reality" - or what the author thinks is reality.
All these examples use "data" out of thin air. For some of them one could say that the data is self-evident (as we all own a brain and can check on ourselves), on others it is not. This is, e.g., the case for all comparisons to animal brains. Just to name one: the model is applied to an elephant which has a big brain, but (apparently) isn't very intelligent and has an 'elephant-memory'.
Do elephants really have a good memory? Folklore says so - but folklore is often wrong. This is where a citation would be needed. (Actually, from memory, it is also not the mass or size of a brain that make up complexity/intelligence, but the amount of neurons - and would you bet an elephant has more neurons? All this the author would have found out had he bothered to check the literature)
The reasoning that this book would be the first to define clear terms and hence is incompatible with previous publications is just a lame excuse - many interesting and intelligent experiments were done whose results can/should, no MUST be cited - instead of the popular method of "making things up". And such experiments/observations are clearly independent of the terminology used.
The book goes on and comes to some trivial as well as some abstruse conclusions from applying the model to the random made-up data.
Sentences like "Let's summarize the European spirit." give you a hint at the type of unjustified generalizations you have to suffer on reading (I wouldn't be too sure that there is a definite general "European spirit" that could be spoken of in any scientific way)
Quote from the Gutenberg project pages:
"In fact, Project Gutenberg approves about 99% of all [...]eBooks [...]"
The book was obviously "published with Gutenberg", because publishing it in this form in any peer-reviewed way would only yield the answer "unsuitable for publishing"
The model itself might be interesting - although there is never a rationale given, why a new layer, e.g. a ZM models had to be introduced (and why is the simplest "image" model an M-model?! why not an I-model? - The naming is also done without rationale or reason), but the way it is applied to rather random made-up claims is certainly not suitable.
I.