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Associative Remote Viewing for Profit: Evaluating the Importance of the Judge and the Investment Instrument
Author(s) -
John G. Kruth
Publication year - 2021
Publication title -
journal of scientific exploration
Language(s) - English
Resource type - Journals
ISSN - 0892-3310
DOI - 10.31275/20211395
Subject(s) - profit (economics) , investment (military) , stock (firearms) , return on investment , psychology , finance , actuarial science , business , economics , law , microeconomics , political science , engineering , mechanical engineering , politics
This study examined the importance of the judge and the particular investment selection in the associative remote viewing (ARV) process. In Protocol 1, ARV was used to predict investments and to generate funds. Three viewers made weekly predictions on Sunday about an image they would be shown on Friday. Two images were selected to represent different states of a stock (value increase or value decrease), and a judge reviewed the images and the viewers’ information. Based on the judge’s evaluation, a coordinator informed an investor whether to invest for the stock to rise or fall during the weekly session. Though the sessions lost funds due to a complication in the investment process, this was not the focus of the study. A second judge (Protocol 2) and a mock investment instrument (Protocol 3) were included, blinded to all study participants. The second judge (J2) performed at a significantly less accurate level than the first judge (p .80). Both judges performed significantly differently on the target investment than on a control investment. Although this is a pilot study with a small sample size and a limited number of sessions, conclusions are that the selection of a judge, even a very experienced judge, can have a significant effect on the success of an ARV project and that judges’ decisions are more affected by the target investments than by a comparable control investment. Future ARV projects are advised to qualify judges for accuracy just as they qualify viewers for accuracy. Keywords: associative remote viewing; ARV

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