How Does P>S>I Score Its Viewers' Work?
Several people have asked me about the "viewer profiles" that I keep. First, a word of explanation about what they are and how they are used, then a lengthy and boring explanation of how they are figured.
It dawned on me many years back that different viewers have different strengths and weaknesses in the remote viewing arena. One, for example, always seems to get the color right, while another will be an ace when it comes to shapes and sizes. It seems logical, then, to look at the tasking which comes in and assign to that task the most proficient viewer for that task. In actual practice, tasking comes in and I break it up into its component questions, then I task each question to the viewer who is most proficient in the area which will answer that type of question.
Also, if you keep track of a viewer's strengths and weaknesses, you know the areas in which more/less training is needed, and can customize training and proficiency practice sessions to suit the needs of the individual viewer.
However, to do this requires a lot more than just having a monitor or analyst think back on a viewer's past results and say, "You know, Joe Smith is really good at that - let's give him the task." That is nothing more than a personal value judgement. In order to know exactly what a viewer's strengths and weaknesses are, you have to have to collect a LOT of data, organize and keep it properly, and then do a LOT of analytic work on it. What develops is then no longer a personal value judgement, but an exact VIEWER PROFILE.
There are certain requirements:
First, you must have feedback in order to judge each perception correctly. I agree with Ingo Swann that, if you don't have feedback, you may be doing a lot of amazing stuff, but you aren't doing Controlled Remote Viewing.
Second, you must have a "non-waffled" scoring system. If, for example, the viewer says,
There is an object: Object #1 | __Y__ |
...which is red | __N__ |
...which is moving | __?__ |
It is against a background | __Y__ |
...which is plain | __Y__ |
...which is single-colored | __Y__ |