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Understanding Dr. D's Equations 1.1 And 1.2

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Posted by Alan on August 3, 2002 10:45:06 UTC


Dr. Dick's presentation, which I refer to here, can be found at:

("Contents" has a capital C)

This is a bit rough as am short of time to tidy and check everything:

I have struggled with understanding equations 1.1 and 1.2. Sometimes I thought I had figured them out but then something seemed wrong. Now I think I have figured these two out. Here goes:

I asked myself: "why does Dr. Dick call "observation" a specific subset of an examined set of a set of numbers?

I drew three circles that partially overlapped each other to give a common region where they intersect.

I coloured in that region and called it "observation".

"Observation" must be "interaction".

My circles represent categories. Words are defined by the intersections, between the categories created by other words. One word might be "communication", the other might be "telephone". The third might be "long distance".

In the region of defining say "your personal specific telephone": it is partially "telephone" (not every phone is your phone);
it is partially "communication" (not all communication is by telephone;
it is partially "long distance" (not all telephone communication is long distance).

Obviously there are many more categories I could introduce to define "your phone". So I add "unknown data"; unknown categories that further might specify "your phone".

This I understand explains Dr. Dick's first adding of unknown data.

By adding "unknown data", unknown categories, we insure that whatever "your phone" is, it is exactly specified to be the region wherein all these unknown categories intersect with the known categories to give the definition "your phone".

We know have a unique data: "your phone", specified by the intersection of known categories and unknown categories.

Now Dr, Dick makes his observation of this unique data also unique.

"Observation" requires that "your phone" interact with a new category so that it can be observed to be "your phone".

New category: "Jack saw (your phone) in your house".
(Note the containment here, re: Chris Langan's CTMU). How to make this observation unique?

The category "Jack" was not specified: "Jack" might be the name of a dog, or of any of many people. The obervation involving category "Jack saw" is not necessarily uniquely defined. "Your house" might be one of several houses you own.

Dr. Dick wants to make sure that the observation is unique by definition.

There might be many categories required to intersect, (in addition to the rather broad categories "Jack saw" and "in your house"), to specify the observation of "your phone" as a UNIQUE OBSERVATION BY DEFINITION.

So unknown categories are added to the observation, that is, unknown data accompanies the interaction called "observation", to make it apparantly unique.

I contend that herein is an explanation of the two steps of "adding unknown data" that deliver Dr. Dick's equations 1.1 and 1.2.

By adding unknown categories, we have tried to specify "data" as a unique intersection of categories, as uniquely defined.

By adding unknown categories to the interaction of the apparantly unique data with a new observing (interacting) category, we have apparantly defined a unique observation. (I say "apparantly" because something still seems to be missing.)

Dr. Dick asks if some "rule" governs the interaction of observation? If there were a rule, it must mean that the category that interacts with the data, must itself be constructed of interactions. These would constitute the rule required to create the 'observing' category needed for the apparantly unique interaction with the apparantly unique data.

What is a "rule"? Dr. Dick says that the rule must reside in the unknown categories plus the (apparantly)unique remainder of the pattern (the observation).

So the rule for determining the apparantly unique observation; for defining this observation (via intersection with an 'observing' category): is just:
the category-intersection description of the observation in terms of OTHER categories (in terms of the rule) of course lies in those other categories (minus the non-other-category version of the observation).

If you want to find the 3-category overlap (2+... categories overlap = data; overlap 1+.. more categories = observation) by other means (by a rule) you will need to look at other categories (removed by calling them unknown) and the remainder of the pattern (the apparantly unique observation).

"Rule" involves other ways of defining (getting) your 3-overlap of categories (2 + unknown more = data, plus 1 + unknown more, = observation). These other ways ("rule" ways) are via remainder of the pattern (unique observation) and the intersection of the unknown "+ more" categories.

One cannot include the basic 3 in the supposed "rule" as we are seeking OTHER ways of defining this intersection of categories (data) intersecting with a new category (intersection of "observation").

Equation 1.2:

(Other categories intersection options) MINUS
(other categories MINUS 3-category intersection that specifies apparantly unique observation) = zero.


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