RE: Seely's Views 2

From: Glenn Morton <glennmorton@entouch.net>
Date: Fri Sep 03 2004 - 17:59:05 EDT

> -----Original Message-----
> From: Roger G. Olson [mailto:rogero@SAINTJOE.EDU]
> Sent: Friday, September 03, 2004 4:03 PM

>
> I kinda see your point, Glenn -- but how could Genesis 1:1 be
> read in an allegorical way, if in fact Genesis 1-11 is "true"
> allegory rather than all literal history? Isn't Genesis 1:1
> compatible with allegory? After all, it doesn't state WHEN
> "the beginning" was relative to the present.
> It doesn't say HOW God created the "heavens" (what's that,
> BTW?) and the earth. How else would God have stated this information?
>
> Anyhoo,... can't a text combine aspects of history and
> allegory? Why does it have to be all or nothing?
>
> The problems that the historists have start in Genesis 1:2.
> That's where the proverbial coprolite hits the alluvial fan.

I think you meant the allegorical fan. :-)

As to a mixture, I am re-reading Shannon's paper which started
information theory (just having had a debate on the issue.) He has a
part of the paper which is directly applicable to this issue of what is
and is not to be taken allegorically and what is and what isn't to be
taken as history.

God is supposedly trying to communicate with mankind. That makes God the
source function in information theory. He uses the channel of a written
book or a story about the creation of the universe. Now, here is what
Shannon says:

        “If a noisy channel is fed by a source there are two statistical
processes at work: the source and the noise. Thus there are a number of
entropies that can be calculated. First there is the entropy H(x) of the
source or of the input to the channel (these will be equal if the
transmitter is non-singular). The entropy of the output of the channel,
i.e., the received signal, will be denoted by H(y). In the noiseless
case H(y) = H(x). The joint entorpy of input and output will by H(xy).
Finally there are two conditional entropies Hx(y) and Hy(x), the entropy
of the output when the input is known and conversely. Among these
quantities we have the relations

H(x,y) = H(x) + Hx(y)= H(y) + Hy(x).

All of these entropies can be measured on a per-second or per-symbol
basis.
        “If the channel is noisy it is not in general possible to
reconstruct the original message or the transmitted signal with
certainty by any operation on the received signal E.” C. E. Shannon, " A
Mathematical theory of Communication" The Bell System Technical Journal,
27(1948):3:379-423, p. 19, 20 at
http://cm.bell-labs.com/cm/ms/what/shannonday/shannon1948.pdf

He then talks about a 1000 bit per second transmission channel. Which
has a 1/100 error rate--e.g. a 0 is received as a 1 or a 1 is received
as a zero.

        “Evidently the proper correction to apply to the amount of
information transmitted is the amount of this information which is
missing in the received signal, or alternatively the uncertainty when we
have received a signal of what was actually sent. From our previous
discussion o fentropy as a measure of uncertainty it seems reasonable to
use the conditional entropy of the message, knowing the received signal,
as a measure of this missing information. This is indeed the proper
definition, as we shall see later. Following this idea the rate of
actual transmission, R, would be obtained by subtracting from the rae of
production (i.e., the entropy of the source) the average rate of
conditional entropy.

R = H(x)- Hy(x)

“The conditional entropy Hy(x) will, for convenience, be called the
equivocation. It measures the averatge ambiguity of the received signal.
    “In the example considered above, if a 0 is received the a
posteriori probability taht a 0 was transmitted is .99, and that a 1 was
transmitted is 0.1. These figures are reversed if a 1 is received. Hence

Hy(x)= -[.99log.99+0.01log0.01]
     =.081 bits/symbol
or 81 bits per second. We may say that the system is transmitting at a
rate of 1000-81=919 bits per second. In the extreme case where a 0 is
equally likely to be received as a 0 or 1 and similarly for 1, the
aposteriori probabiltieis are ,1/2 and

Hy(x) = -[1/2log1/2 +1/2log1/2]
           = 1 bit per symbol

or 1000 bits per second. The rate of transmission is then 0 as it should
be.”
C. E. Shannon, " A Mathematical theory of Communication" The Bell System
Technical Journal, 27(1948):3:379-423, p. 20 at
http://cm.bell-labs.com/cm/ms/what/shannonday/shannon1948.pdf

Now if we have a situation in the God-communicates-to-humans-system a
case where we have every single part that we can't tell whether it is
meant to be taken as historically true or historically false, then we
are in the situation at the last case. The probability for each part is
1/2 true and 1/2 false. Then Hy(x) equals 1 bit per symbol or the rate
of transmission of the divinely inspired message is zero.

That is what is wrong with the allegorical and mixture approach.
Communication becomes impossible and I will cite the noisy channel
theorem of Shannon! (How is that for applying science to theology?) It
is clear that christians of various stripes see various things as true
and various things as 'allegorical'. Bultmann, [sic?] I think felt that
even Jesus as the Christ was allegorical. Jesus was a man and the Spirit
of God abandoned the poor fellow on the cross. Because of this, if the
story is simply given a 50-50 chance of being right, there is no
communication at all by God. All is random.

In geophysics we would call this the case where the signal to noise
ratio is 1. I try to record a seismic signal from reflections off of
rock layers. But if the wind is blowing strong enough in some places,
the tree roots act as a seismic signal. When that signal is as great as
my seismic source, the signal to noise ratio is 1. Half the samples we
record in that situation are correct. Half are false. We don't know
which is which. We can't unscramble truth from fiction.

Making the Bible have a signal to noise ratio of 1 we won't be able to
separate truth from fiction.
Received on Fri Sep 3 18:35:11 2004

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