Hey John, Thanks for taking the time to reply... JG wrote: "Please name me one of the "NLP based models that is binary" - remember, if they are not present, they do not exist." It was that last part I really meant.  Their presence is binary - e.g. 1 = present, 0 = NOT present.  (This is based on your definition of their sole evaluation criteria on p55 in Whispering). JG wrote: "Help me out here, RobMan" Hey...I only said "could be usefully applied"...not WOULD 8) JG wrote: "could we get an simple example of how "statistics could be usefully applied to the analysis of what makes a model elegant and sufficient"?" I'm actually struggling with this as part of my research project...but what I was thinking was that (once there was a shared database of commonly presented models - see my other post on Modelling Software) it would be possible to do a structural analysis across the range of models available.  e.g. looking for patterns across the sequence structures.  I've used this design by analogy approach alot in software where we look for common design patterns.  But let me get back to you with a more detailed and statistically focused example soon. JG wrote: "It is difficult enough to imagine how the NLP based models I am familiar with have non-overlapping coding vocabularies, with their application to distinct area of expertise, that represent models of distinct logical types of transactions" OK...my unstated presupposition here was that it is possible (and likely in the near future) that most models would be able to be expressed in a common form and notation. I had a good chat with Chris Collingwood about this today and the two main classes I can see is: - strategies (sequences of holding attention - which I see as the precise tool) - physiology (which I see as a very useful but more blunt tool) If you can see any other classes I've missed can you please point them out.  To me anything else seemed to be dealing with "how" this notation is presented (e.g. linearly, hierarchically, branching, etc - all addressed in detail within the UML domain). JG wrote: "but when I think about the issue of simplification - that is, the mapping from the set of exemplars of a pattern to some explicit model - I completely boggle." OK...this one is a bit more of a stretch...and may be better dealt through modelling modelling strategies...however... JG wrote: "It seems to imply that there is some measure of complexity/simplification between the process experiences being modeled and the explicit product that represents it and further that this measure is independent of the processes modeled by the various models involved. In attempting to consider what such a measure might be, I fall speechless." I think I understand the immense scope of this challenge...but I don't necessarily believe that it's impossible.  However this challenge may be best dealt with NLP Modelling in combination with a NCC modelling tool like http://www.neuromag.com/homepage.html (as one example). JG wrote: "You are certainly correct that the variables in an algebraic equation (you called them simplifications) may represent some number of real world objects but to claim that these simplifications are well defined is altogether another matter." Perhaps this was just a clumsy description.  All I really meant was that algebra is based upon a set of number systems that have been rigorously defined and analysed through mathematical proofs.  Algebra doesn't care if the apples are red or green...just how many there are.  NLP has yet to develop this kind of rigour...as far as I can see.  (NOT that I'm suggesting this is an isomorphic analogy 8) ). JG wrote: "Clearly, the manipulation of the algebraic equations is driven by a set of processes (commutative...) that are well defined but the entire artistry of scientific research depends precisely on the skill (and luck) of the person making the initial mapping between the real (sic)world objects and the variables expressed in the equation precisely as the effectiveness (learnability and efficiency) depends on the skill of the modeler in an NLP based piece of modeling in assigning explicit vocabulary to the elements in those sets of interactions they purport to model." mmm...I think the analogy falls down here...in algebra we are discussing solving a problem using variables in a formula.  With NLP modelling we are discussing eliciting enough model information to capture it in notation (back to your definition of model evaluation criteria on page 55). And that's my 0.02c... BTW: Thanks to you and Carmen for Whispering...it has really helped clean things up alot 8) roBman (NOTE: the emphasis is not on gender as most people seem to hallucinate 8) )