The Field (21 page)

The results with different individuals would vary (some would produce more heads than tails, even when they had concentrated on the exact opposite). Nevertheless, many operators had their own ‘signature’ outcome – Peter would tend to produce more heads than tails, and Paul vice versa.
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Results also tended to be unique to the individual operator, no matter what the machine. This indicated that the process was universal, not one occurring with only certain interactions or individuals.

In 1987, Roger Nelson of the PEAR team and Dean Radin, both doctors of psychology, combined all the REG experiments – more than 800 – that had been conducted up to that time.
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A pooling together of the results of the individual studies of sixty-eight investigators, including Schmidt and the PEAR team, showed that participants could affect the machine so that it gives the desired result about 51 per cent of the time, against an expected result of 50 per cent. These results were similar to those of two earlier reviews and an overview of many of the experiments performed on dice.
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Schmidt’s results remained the most dramatic with those studies that had leapt to 54 per cent.
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Although 51 or 54 per cent doesn’t sound like much of an effect, statistically speaking it’s a giant step. If you combine all the studies into what is called a ‘meta-analysis’, as Radin and Nelson did, the odds of this overall score occurring are a trillion to one.
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In their meta-analysis, Radin and Nelson even took account of the most frequent criticisms of the REG studies concerning procedures, data or equipment by setting up sixteen criteria by which to judge each experimenter’s overall data and then assigning each experiment a quality score.
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A more recent meta-analysis of the REG data from 1959 to 2000 showed a similar result.
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The US National Research Council also concluded that the REG trials could not be explained by chance.
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An effect size is a figure which reflects the actual size of change or outcome in a study. It is arrived at by factoring in such variables as the number of participants and the length of the test. In some drug studies, it is arrived at by dividing the number of people who have had a positive effect from the drug by the total number of participants in the trial. The overall effect size of the PEAR database was 0.2 per hour.
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Usually an effect size between 0.0 to 0.3 is considered small, a 0.3 to 0.6 effect size is medium and anything above that is considered large. The PEAR effect sizes are considered small and the overall REG studies, small to medium. However, these effect sizes are far larger than those of many drugs deemed to be highly successful in medicine.

Numerous studies have shown that propranolol and aspirin are highly successful in reducing heart attacks. Aspirin in particular has been hailed as a great white hope of heart disease prevention. Nevertheless, large studies have shown that the effect size of propranolol is 0.04 and aspirin is 0.03, respectively – or about ten times smaller than the effect sizes of the PEAR data. One method of determining the magnitude of effect sizes is to convert the figure to the number of persons surviving in a sample of 100 people. An effect size of 0.03 in a medical life-or-death situation would mean that three additional people out of one hundred survived, and an effect size of 0.3 would mean that an additional thirty of one hundred survived.
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To give some hypothetical idea of the magnitude of the difference, say that with a certain type of heart operation, thirty patients out of a hundred usually survive. Now, say that patients undergoing this operation are given a new drug with an effect size of 0.3 – close to the size of the hourly PEAR effect. Offering the drug on top of the operation would virtually double the survival rate. .3
An additional effect size of
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would turn a medical treatment that had been life-saving less than half the time into one that worked in the majority of cases
.
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Other investigators using REG machines discovered that it was not simply humans who had this influence over the physical world. Using a variation of Jahn’s REG machines, a French scientist named René Peoc’h also carried out an ingenious experiment with baby chicks. As soon as they were born, a moveable REG was ‘imprinted’ on them as their ‘mother’. The robot was then placed outside the chicks’ cage and allowed to move about freely, as Peoc’h tracked its path. After a time, the evidence was clear – the robot was moving toward the chicks more than it would do if it were wandering randomly. The desire of the chicks to be near their mother was an ‘inferred intention’ that appeared to be having an effect in drawing the machine nearer.
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Peoc’h carried out a similar study with baby rabbits. He placed a bright light on the moveable REG that the baby rabbits found abhorrent. When the data from the experiment were analyzed, it appeared that the rabbits were successfully willing the machine to stay away from them.

Jahn and Dunne began to formulate a theory. If reality resulted from some elaborate interaction of consciousness with its environment, then consciousness, like subatomic particles of matter, might also be based on a system of probabilities. One of the central tenets of quantum physics, first proposed by Louis de Broglie, is that subatomic entities can behave either as particles (precise things with a set location in space) or waves (diffuse and unbounded regions of influence which can flow through and interfere with other waves). They began to chew over the idea that consciousness had a similar duality. Each individual consciousness had its own ‘particulate’ separateness, but was also capable of ‘wave-like’ behavior, in which it could flow through any barriers or distance, to exchange information and interact with the physical world. At certain times, subatomic consciousness would get in resonance with – beat at the same frequency as – certain subatomic matter. In the model they began to assemble, consciousness ‘atoms’ combined with ordinary atoms – those, say, of the REG machine – and created a ‘consciousness molecule’ in which the whole was different from its component parts. The original atoms would each surrender their individual entities to a single larger, more complex entity. On the most basic level, their theory was saying, you and your REG machine develop coherence.
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Certainly some of their results seemed to favor this interpretation. Jahn and Dunne had wondered if the tiny effect they were observing with individuals would get any larger if two or more people tried to influence the machine in tandem. The PEAR lab ran a series of studies using pairs of people, in which each pair was to act in concert when attempting to influence the machines.

Of 256,500 trials, produced by fifteen pairs in forty-two experimental series, many pairs also produced a ‘signature’ result, which didn’t necessarily resemble the effect of either individual alone.
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Being of the same sex tended to have a very slight negative effect. These types of couples had a worse outcome than they achieved individually; with eight pairs of operators the results were the very opposite of what was intended. Couples of the opposite sex, all of whom knew each other, had a powerful complementary effect, producing more than three and a half times the effect of individuals. However, ‘bonded’ pairs, those couples in a relationship, had the most profound effect, which was nearly six times as strong as that of single operators.
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If these effects depended upon some sort of resonance between the two participating consciousnesses, it would make sense that stronger effects would occur among those people sharing identities, such as siblings, twins or couples in a relationship.
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Being close may create coherence. As two waves in phase amplified a signal, it may be that a bonded couple has an especially powerful resonance, which would enhance their joint effect on the machine.

A few years later, Dunne analyzed the database to see if results differed according to gender. When she divided results between men and women, she found that men on the whole were better at getting the machine to do what they wanted it do, although their overall effect was weaker than it was with women. Women, on the whole, had a stronger effect on the machine, but not necessarily in the direction they’d intended.
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After examining 270 databases produced by 135 operators in nine experiments between 1979 and 1993, Dunne found that men had equal success in making the machine do what they wanted, whether heads or tails (or HIs and LOs). Women, on the other hand, were successful in influencing the machine to record heads (HIs), but not tails (LOs). In fact, most of their attempts to get the machine to do tails failed. Although the machine would vary from chance, it would be in the very opposite direction of what they’d intended.
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At times, women produced better results when they weren’t concentrating strictly on the machine, but were doing other things as well, whereas strict concentration seemed important for men’s success.
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This may provide some subatomic evidence that women are better at multitasking than men, while men are better at concentrated focus. It may well be that in microscopic ways men have a more direct impact on their world, while women’s effects are more profound.

Then something happened which forced Jahn and Dunne to reconsider their hypothesis about the nature of the effects they were observing. In 1992, PEAR had banded together with the University of Giessen and the Freiberg Institute to create the Mind – Machine Consortium. The consortium’s first task was to replicate the original PEAR data, which everyone assumed would proceed as a matter of course. Once the results of all three laboratories were examined, however, they looked, at first glance, a failure – little better than the 50 – 50 odds which occur by chance alone.
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When writing up the results, Jahn and Dunne noticed some odd distortions in the data. Something interesting had occurred in the secondary variables. In statistical graphs, you can show not only what your average ought to be but also how far the deviations from it ought to spread from your mean. With the Mind – Machine data, the mean was right where it would be with a chance result, but not much else was. The size of the variation was too big, and the shape of the bell curve was disproportionate. Overall, the distribution was far more skewed than it would be if it were just a chance result. Something strange was going on.

When Jahn and Dunne looked a little closer at the data, the most obvious problem had to do with feedback. Up until that time they’d operated on the assumption that providing immediate feedback – telling the operators how they were doing in influencing the machine – and making an attractive display or a machine that people could really engage with would crucially help to produce good results. This would hook the operator into the process and help them to get in ‘resonance’ with the device. For the mental world to interact with the physical world, they’d thought, the interface – an attractive display – was crucial in breaching that divide.

However, in the Consortium data, they realized that the operators were doing just as well – or sometimes better – when they had no feedback.

One of their other studies, called ArtREG, had also failed to get significant overall results.
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They decided to examine that study a bit more closely in light of the Mind – Machine Consortium results. They’d used engaging images on a computer, which randomly switched back and forth – in one case a Navajo sand painting switched with Anubis, the ancient Egyptian judge of the dead. The idea was for their operators to will the machine to show more of one than the other. The PEAR team had assumed once again that an attractive image would act as a carrot – you’d be ‘rewarded’ for your intention by seeing more of the image you preferred.

Once they’d examined the data of the study in terms of yield by picture, those images which had produced the most successful outcomes all fell into a similar category: the archetypal, the ritualistic or the religiously iconographic. This was the domain of dreams, the unexpressed or unarticulated – images that, by their very design, were intended to engage the unconscious.

If that were true, the intention was coming from deep in the unconscious mind, and this may have been the cause of the effects. Jahn and Dunne realized what was wrong with their assumptions. Using devices to make the participant function on a conscious level might be acting as a barrier. Instead of increasing conscious awareness among their operators, they should be diminishing it.
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This realization caused them to refine their ideas about how the effects they’d observed in their labs might occur. Jahn liked to call it his ‘work in progress’. It appeared that the unconscious mind somehow had the capability of communicating with the subtangible physical world – the quantum world of all possibility. This marriage of unformed mind and matter would then assemble itself into something tangible in the manifest world.
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