Re: ALLOS and Jn. 1:1c/Was Anarthrous Subject

Paul S. Dixon (dixonps@juno.com)
Sat, 06 Sep 1997 04:19:27 EDT

On Sat, 06 Sep 1997 01:32:32 "Stephen C. Carlson"
<scarlson@mindspring.com> writes:
>At 12:42 9/5/97 EDT, Paul S. Dixon wrote:

>>Now, I did argue from the literary context,
>>arguing that in 50 of 53 occurrences of the pre-copulative anarthrous
>>predicate nominative in John's Gospel the nuance was qualitativeness
>(myTh.M. thesis).
>
>Fifty out of fifty-three occurrences is 94%. And this observation is
>the apparent basis for the following conclusion in Dixon's thesis,
>available on the Web:
>
> "Third, this thesis demonstrates that the statistical probability
> of QEOS being qualitative, rather than definite or indefinite, is
> quite high, 94%."
>
>This conclusion does not follow from the observation, because it does
>not consider how likely the noun QEOS itself can be definite,
indefinite,
>or qualitative.

It does follow. The parameters or factors of this statistical
probability problem are given only as: pre-copulative anarthrous
predicate nominatives in the Gospel of John. Now, it was determined that
94% of those are qualitative. So, given a pre-copulative anathrous
predicate nominative in the Gospel of John we can say the statistical
probability that it is anarthrous is quite high, about 94% (technically,
we should not include the sample as part of this here; thus 49 of 52, but
still 94%).

Sure, if you consider other factors, then the probability might change.
But, this does not affect the validity of my findings.

>Fortunately, the Rev. Thomas Bayes (d. 1761) realized,
>in a theorem that now bears his name, that in considering how new
>information affects prior probabilities, one must look at the relative
>probabilities.

Again, your argument misses the boat here. I was under no obligation to
consider the additional factors you note, for my only criteria were:
precopulative anarthrous pred. nominatives in the Gospel of John.

>The word QEOS is definite with some prior probability, P(D), which may
>be estimated from examining the literature. We are interested in
>assessing the probability that this word is definite given the new
information >that it is (A)narthrous and (P)recedes the verb, or in a
mathematical notation,
>P(D|AP).

At this point, of course, I am assuming your position (which I already
rejected - see above) for the sake of argument.

The information you cite here is not new information. It was included in
my parameters.

>
>According to Bayes Theorem, then,
> P(D|AP) = P(D)P(AP|D) : P(D')P(AP|D'). (1)
>In other words, we must consider the relative probability of QEOS
>being definite when anarthrous and preceding the verb versus being
>non-definite when anarathrous and preceding the verb.
>

Again, this is not new stuff to be considered as factors; rather, it is
precisely what was determined.

>We can estimate P(AP|D), the probability that QEOS will be anarthrous
>and preceding the verb, when definite. Paul's thesis at the web site
>states:
>
> "Our conclusions show that when John wished to express a definite
> predicate nominative, he usually wrote it after the verb with the
> article, 66 of 77 occurrences or 86% probability."
>
>Therefore, we estimate that a definite QEOS should precede the verb
>with 100%-86% = 14% probability. By Colwell's rule, all 14% is
anarthrous.

Oops, another blunder. Colwell's rule does not say that all definite
pre-copulative predicate nominatives are anarthrous. His probability, as
I recall, was closer to 70-80%, but certainly not all.

But, it gets worse. Why are you assuming definiteness here as "new
information" to be considered? Definiteness, or the probability of it,
is what you are trying to determine. This is assuming your conclusion.
Sorry.

>For the estimate of P(AP|D'), the probability that QEOS will be
>anarthrous and preceding the verb, when non-definite, we will use
another
>observation in his thesis:
>
> "When he wished to express a qualitative predicate nominative with
> the verb, he usually wrote it before the verb without the article,
> 50 of 63 occurrences or 80% probability."
>
You are doing the same thing here. You cannot assume what you are trying
to prove or determine. I think I've responded enough.

Paul Dixon