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On 2017-12-06 18:28, Louis Proyect via Marxism wrote:
The problem is with cancer, however. Trying to find an environmental smoking gun is virtually impossible. Cancer clusters are just one example.
Well the sad thing is that I probably agree totally with Louis in regards to the policy issues regarding nuclear power (more than I would with David) and other environmental dangers expressed in the remainder of his post, below. But that has nothing to do with my point: knowledge gained empirically (and confidence in that knowledge) can be obtained using the scientific method, not through simply compiling what Louis admits is "circumstantial evidence," and what you learn (or don't learn) is a separate matter from what action you propose in relation to that knowledge (or lack thereof). Although our practical concerns are the same, I'm afraid Louis doesn't appreciate the use of statistical inference in establishing scientific conclusions, which is the only way he could say that doing so is "virtually impossible."
Statistics is an exact science (well, actually mathematics) concerning inexact phenomena (which is almost everything in reality). And by "statistics" I don't mean numbers that are measured or thrown around (aka "raw statistics") but the science whereby empirical measurements of random phenomena can lead to (or fail to lead to!) conclusions concerning the underlying system. Yes, there are many ways that statistics, even without making any errors in the math, can be intentionally misused or innocently misapplied, resulting in invalid conclusions. That goes for anything. But statistics has a bad reputation, because rather than the science of statistical inference, a propagandist will throw out numbers to non-statisticians and expect them to come to conclusions in their minds matching the intentions of the propagandist. But that is not how statistics is used in scientific research.
People might imagine that scientists make measurements and then perform calculations based on those numbers. But that's only half the story. Often you'll spend as much or more time not on those numbers but on analyzing the errors in your measurements and the resulting strength of your conclusions. For instance, I may measure a 2 degree increase in temperature when I add X to a solution of Y. That might mean that the reaction between X and Y generates that much heat. But before I could say that, and certainly before I could publish it, I would have to ask how precise my thermometers are. It could be that my thermometers are so crumby that either of their readings has an expected (rms) error of 1 degree. Then I could hardly reach any such conclusion; even if there had been no heat generated in the reaction there is an 8% a priori probability of measuring a temperature increase as large as 2 degrees just due to the measurement error of my thermometers. On the other hand, even if those were the best thermometers I could obtain, I could repeat the experiment 50 times (making 100 measurements using the crumby thermometers). If the average measured temperature increase found from them is 1.32 degrees then I could conclude with extremely high confidence (in other words, I would stake my life on it) that there is an actual temperature increase. I could go further and claim 95% confidence limits for the actual temperature increase being between 1.26 and 1.37 degrees. Having a 95% confidence means that using this proper procedure I would have successfully bracketed the actual value with a probability of .95. These statistical conclusions are all exact numbers based on sound mathematics but concern an underlying process that itself is never known with absolute precision. That is totally different than me casually saying "I measured this big number and it really looks convincing, doesn't it...."
So I'm sorry, but you very much can determine that radiation exposure leads to cancer without ever knowing that any single case of cancer was due to radiation. From a mathematical point of view you could do that best with a controlled experiment where 100 people are exposed to radiation and comparing them to a test group of 100 who weren't. Of course that experiment is unethical (but has been done with animals) so you have to collect epidemiological statistics and these are more subject to confounding factors. The cancer rate increased from 3.3% to 4.1% after the nuclear reactor was installed. For a community of several thousand, that would be a statistically significant increase. But there was also a chemical plant opened during the same period. And the ability to detect cancer was improved. So you compare with a second community also affected by the chemical plant but further from the nuclear plant. But then someone points out that the affected community had offered a tax break to cancer patients who move there. So maybe you aggregate such results from 100 similar nuclear plants. In other words, you can take steps to avoid the confounding effects and increase the significance of your measurements, and eventually you do reach conclusions. Because of all the potential unknowns affecting epidemiological data compared to a controlled experiment, there might be more uncertainty regarding your conclusions. But there are plenty of such studies which have properly linked ionizing radiation to cancer rates. Unfortunately this wasn't one of them.
- Jeff Put yourself in the position of a breast cancer victim living
near a nuclear power plant. You are shit out of luck. Even if the data indicates higher than usual contamination, how can you establish it led to thyroid or breast cancer? The same thing is true of pesticides and herbicides. How can you establish that Monsanto is guilty of jeopardizing our health by selling products that after leaching into the soil cause bladder cancer, was the case with Sandra Steingraber? You can certainly prove that drinking a fifth of whiskey every day can cause cirrhosis of the liver but what kind of experiment can prove that living near Indian Point causes thyroid cancer? It is only "circumstantial evidence". Meanwhile, the best course of action is to overthrow the capitalist system and build a society based mostly on alternative energy sources. Even if the evidence is only circumstantial, that's no reason to risk the health of the human race.
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