# Re: tautology

```On Mon, 15 Nov 1999, Russell Standish wrote:
> >     Given the measure distribution of observation-moments, as a
> > function on observables (such as Y1 and X),
> >     p(Y1|X) = p(Y1 and X) / p(X)
> >     Not so hard, was it?
> >     [Note that here X was the observation of being Jack Mallah, and
> > Y1 was basically the observation of being old.  See previous posts on
> > this thread if you want exact details of Y1; nothing else about it is
> > relevent here I think.]
>
> ASSA doesn't give p(Y1 and X) either.```
```
Obviously, and as I've repeatedly said, some prescription for the
measure distribution is also needed.  That is true even to just get p(X).

> >     Huh?  Why should p(not Y1, and X) = 0 ?  Especially since my
> > current observations are (not Y1, and X)!!!
>
> Your current observations are [sic] p(Y3|X), where Y3 = Jacques Mallah's
> is observed to be young. Y3 is not equivalent to (not Y1). Just because
> you see yourself young does not preclude seeing yourself old at a
> later date!

Here your misunderstanding is clearly exposed.  The way I've
defined p(A), it is the effective probability of an observation-moment
with the property 'A'.
Definitions of identity, of 'me' or 'not me', are irrelevant to
finding p(A).  By definition, if my current observation is A, and A and B
are such that it is not possible for the same observation-moment to have
both, then I observe (not B).
If you want to talk about the probability that, using some
definition of identity that ties together many observation moments, "I"
will eventually observe Y1 - that will depend on the definition of
identity.  It is NOT what I have been talking about, nor do I wish to talk
about it until you understand the much more basic concept of the measure
of an observer-moment.

- - - - - - -
Jacques Mallah ([EMAIL PROTECTED])