Bell curve
The story about EMF health risks told by cell-phone and power-company experts is implicitly based on the myth that the body is composed of spatial and temporal parts which are independently governed by external laws. This linear dissociation is a good founding explanation for effects characterized by measurements that fit a bell-shaped curve, like the effect of gravity on the swinging of a pendulum, but the myth is seriously misleading when used to explain nonlinear systems like human beings exposed to cell-phone EMFs.
The assumptions and models that collectively constitute the myth which organizes and facilitates the EMF-health debate strongly favor the perspective of the cell-phone and power companies. Typically, company experts assume that any real biological response in someone exposed to an EMF must be exactly reproducible. Neither the experts nor the companies invented the idea of exact reproducibility. Rather it emerged naturally from the work of Newton and others who followed his lead regarding how we should conceptualize observations to understand why they occurred. What the companies did was hire experts who convinced the WHO, NIH, FDA, and FCC that the exact-reproducibility criterion applied to EMF-related disease. It doesn’t, and the inevitable result of forcing use of the criterion is the false-negative conclusion that cell-phone and powerline EMFs do not create health risks.
I’ll explain, but bear with me. The explanation is simple but has profound consequences regarding how we conceptualize the impact of science in the everyday world, and accepting explanations that entail the need to change ingrained cognitive structures is naturally difficult.
By definition, science is the area of human activity that seeks to provide rational explanations for observations. Phenomena that can reliably be identified as effects produced by specific causes are one area where explanations were successfully devised. Reproducibility is the imprimatur of successful causal explanation because reproducibility is a sign for the reliability of a rationally identified causal connection. But what must be reproduced?
Almost always, company experts assume that the requisite reproducible observation is the numerical value of the response variable chosen for measurement. If a putative effect is +50 units, reproducibility is taken to mean that +50 units must be observed when the putative cause is reapplied or, allowing for the stochastic variability that produces the familiar bell-shaped curve for repeated measurements in linear systems, a value that is usually close to +50 units. The experts assume that there always exists a bell curve whose peak is truth. In this perspective, observations of 0 units or −50 units count as evidence against a causal link, and observations of −50, 0, and +50 in three independent trials would be averaged and interpreted as strong evidence against the reliability of the claim that the putative cause was actually a cause.
The error committed by the company experts stems from the fact that only systems governed by linear laws necessarily yield data that fits a bell-shaped curve. Essentially all man-made systems are governed by such laws. That’s why things like cell phones, airplanes, and computers are so predictable and dependable. Systems governed by nonlinear laws, in contrast, generate observations that do not necessarily fit a bell-shaped curve. Nonlinear systems are fully capable of lawfully yielding observations of −50, 0, and +50 in three successive independent trials. Forced use of averaging in this instance results in a strong and wrong inference against the existence of an effect. Weather is a good example of a nonlinear system, as are almost all behaviors of living systems. Some uncertainty and unpredictability is the rule in nonlinear systems, and that’s how we can recognize them—they are anything made of atoms that exhibits behavior which is at least partially uncertain or unpredictable. The biological effects of environmental EMFs are outstanding examples of specific nonlinear processes. The use of averaging emasculates our ability to understand nonlinear biological phenomena such as the physiological effects of EMFs, which are fully deterministic processes governed by nonlinear laws (nonlinear differential equations) and consequently do not necessarily yield bell-shaped data distributions.
The assumption of the universal application of averaging wasn’t invented by the cell-phone and power companies, but they became proficient in using it to avoid legal responsibility for the damages caused by their EMFs, and we can see why their strategy was so successful. Incorporation of linearity into the cognitive structure of science has a deep psychological significance for us because of the stunning success it produced in physics. When we disassociated our experiences into conceptual cardboard-like processes called mechanisms that obeyed the law of averaging, we achieved an understanding of inanimate nature that produced intense satisfaction. The excitement we felt when we saw nature obey a simple law like gravity led to the feeling that all observations could similarly be accounted for by simple linear laws, even bio-behaviors. But the truth is that bio-behavior is more complex than gravity. It is not open to us to extend our exhilaration-producing myth to living systems. We cannot make them obey laws simply because that makes us feel good. We must take living systems the way God gave them to us, in their stark complexity. That’s what science is—rationally explaining what we see.
The application of averaging to living systems is among the most seriously misleading forms of conduct in science. It’s not necessarily intentional, like fabrication or falsification, but its consequences can be as devastating. Why would an expert commit the mistake of forcing force use of averaging on a nonlinear system, considering the essential mismatch that would be created between the analytical method and the system’s dynamical activity? There are the four kinds of mistaken experts: toadies, casuists, lovers, and alchemists (see Going Somewhere). Where do they come from? Not from under rocks or out of thin air, but from the same stock that gives rise to experts who maintain respect for the scientific method. In each instance of a mistaken expert I suppose there was a crisis where the expert made the wrong choice but nevertheless was rewarded with a publication in a prestigious journal, special attention in the media, a promotion, or some financial benefit. Thereafter, it became progressively easier to put true science in the background. Any kind of a mistaken expert can be useful to the power and cell-phone companies, but toadies are the best servants.
When an investigator purporting to study the health risks of EMFs designs experiments under the assumption that the relationship is linear, then you should realize that the investigator has almost no chance of seeing, like a man who pops out his eyes. EMF health risks must be viewed from this perspective of nonlinearity. Otherwise the chronic error of the power and cell-phone companies—the false negative result—will continue to occur, with all the harm that the error entails.
For a description of analytical methods appropriate for detecting nonlinear EMF effects on human brain electrical activity, click here.


http://andrewamarino.com/blog/?p=178