“Mapping Across” with Process Submodalities

One way to greatly speed up this process of transformation is to use a classic NLP process called “mapping across” [6, 7] in which the process distinctions of judgement are transformed into preference, one by one, until you have transformed the whole experience. For example, let’s assume that your experience was described by the differences between judgement and preference listed previously on page (add in page #). You could start by adding in a second image of what you prefer alongside what you judge as “bad,” and then step into that image so that you are no longer separate from what you judged. Then you could change the “You” statements of judging to the “I” statements of preferring, and allow the still, black and white image to become a color movie, etc., etc.

In actual practice you will find that changing some of these process elements also changes others, and that the ones that are most powerful in transforming experience differ somewhat from one person to another. Adding in the second image may spontaneously cause the narrow focus to widen into a panorama, and the feeling of hard closedness to soften and open up. Stepping into a still image may automatically change it into a colorful movie with sound, etc. These more powerful changes are called driver submodalities because they drive or influence others.

Once you have discovered the drivers that work best for you, it becomes even easier to change a judgement into a preference, since you only have to change a few of them in order to complete the shift. Changing these process elements is a very powerful change in itself, and at the same time it also enriches the content details of the experience. For instance, when you shift from a still picture to a movie, there is more information in the movie, and the information continues to change as you view it. When you shift from a narrow focus to a broad panorama, there is literally more to see in your image, and you can view what you don’t like in a much larger and more detailed context.

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