| Topic: | Re:Re:Re:Re:Continued :Habermas and NLP |
| Posted by: | Ryan Nagy |
| Date/Time: | 31/07/2003 06:44:35 |
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Doug - Thanks for your response. Your thinking is a bit clearer in this post. You wrote: "We shouldn't be embarrassed to take note that changing a simple submodality can have a profound effect. And when we observe such a linear sequence, it is just fine to use language that represents it as such." Your example is actually an example of a non-linear change. There is not a 1-to-1 relationship between the change in a submodality and the change in behavior If the work is successful, at some point in the change process the person/system reorganizes into a new state/behavior which is markedly different from the previous one. The submodality change could be considered what those who study dynamic systems call a "control parameter." Subtle changes may or may not occur as you "scale" or slowly change the submodality, but at some critical point the system reoganizes into a new state/behavior. A common example is horse locomotion. Horses only have three modes of locomotion: walking, trotting and galloping. Within certain speeds (speed is the control parameter) the mode stays stable. For instance, a horse can walk faster and faster until at a certain speed it re-organizes into trotting. Trotting is an entirely different mode than walking - the timing, muscle activation patterns, spatial coordination (ect.) is different from those of walking as trotting is different from galloping. In other words, trotting is not walking speeded up, they are two fundamentally different ways of moving. The key point is this: As one variable (speed) is increased linearly, you get not only an increase in speed but (bang) a non-linear re-organization of how the system acts to produce that speed. Also, as you reduce the control parameter, the system does not have to go back through previous states, i.e. the horse can go from galloping to walking without having to trot in between. (there are countless examples of this process - the horse example is simply a decent, easy to follow metaphor). "Clearly NLPa is full of "whys"... NLPm includes "whys" in certain aspects of its articulation, but explicitly excludes 'whys' in other aspects. " This is another example of perfectly "true" yet irrelevant nonsense. What exactly is your point? Are you doing NLP or NLP modelling to find out why the model is succesful? Is knowing "why" going to help you teach the skill to another? Let's put it another way: Is your (or my) hallucination of "why" a result occurs a critical distinction in duplicating or transfering whatever skill you are modeling? "...you are clear when I am speaking linearly... linearity is nothing to be ashamed of, right?" Linearity is a necessary and useful part of our lives (and Models). Who said otherwise? |