I think this is a very interesting article. As someone who has been a research scientist for about 45 years now, I would say that the problem is not with the scientific method, but with how we scientists apply it. We scientists are all too human, and have the usual human failings. It is not easy to avoid the pitfalls when doing research. It is easy to make blunders, or to fool oneself. This is especially true when a scientist enters a new field, in which he/she does not have experience. The physicist Edward Teller, when introduced as an "expert" in something, used to say that an expert is a person, who, by his own painful experience, has found out all the mistakes it is possible to make in a single, limited field, and by that criterion, he said that he would acknowledge only that he was "becoming" an expert.
Having a community of scientists competing with each other and working on the same issues can be helpful in arriving at the truth. But even then, the whole community can miss an important point or be convinced by an influential group or individual. And we all have egos, which can cause us to fall in love with our hypothesis and ignore data that don't support it. And the problems become worse when big money is involved, such as in pharmaceutical testing, because, unfortunately, some people have reasons to distort the scientific process. Note how many drugs have had to be pulled after they have been used for a short time because they have caused people harm, which should have been revealed in the research and testing phases.
It really helps to have a body of theory to work with, so you can constantly test experimental results against theory. When they disagree, you know that at least one of them has to be wrong (maybe both!) But it gives you something else to work with. This has been possible in the physical sciences for a long time, and in the past few decades, it has become more possible in the biomedical sciences, also. It's amazing how many times in the PDR it will say that it is not known how a particular drug works. This means that there can be no comparison between theory and experiment.
It's not easy to do valid research. Research involves finding out things that no one has known before. It's a lot like groping around in the dark, without a flashlight. But when you do find something new that hasn't been known by anyone, it's a very gratifying experience.
I think most people in the general population are accustomed to using mature results of the scientific method, after the research has largely been done. In ME/CFS, we are engaged in trying to figure out how to drain the swamp while we are up to our ears in alligators. It would be much less frustrating for PWMEs/PWCs if the research had already been finished, but this is unfortunately not the case. I do think that the usual "pushing and shoving" that goes on in the process of doing scientific research is a real eye-opener to many PWMEs/PWCs, because it is the part that the general population doesn't always see. I notice that people are often drawn into "rooting" for one side or another in this process, and I can't blame them, but ultimately the issues are better decided by finding out what is truly going on in the part of the natural universe we are researching, rather than by a "vote."
I agree with Rich that the "pushing and shoving" that we see is something that normally the general public isn't aware of, and that it's quite a shock to get closer to the scientific process and discover how messy and political it can be. And I think a lot of people fall into the trap of thinking this is just about ME somehow, and doesn't apply in other areas of science as well - which leads to all kinds of paranoia and confusion.
Some quotes in this article that I really liked:
The bias was first identified by the statistician Theodore Sterling, in 1959, after he noticed that ninety-seven per cent of all published psychological studies with statistically significant data found the effect they were looking for. A “significant” result is defined as any data point that would be produced by chance less than five per cent of the time. This ubiquitous test was invented in 1922 by the English mathematician Ronald Fisher, who picked five per cent as the boundary line, somewhat arbitrarily, because it made pencil and slide-rule calculations easier.
Sterling saw that if ninety-seven per cent of psychology studies were proving their hypotheses, either psychologists were extraordinarily lucky or they published only the outcomes of successful experiments. In recent years, publication bias has mostly been seen as a problem for clinical trials, since pharmaceutical companies are less interested in publishing results that aren’t favorable. But it’s becoming increasingly clear that publication bias also produces major distortions in fields without large corporate incentives, such as psychology and ecology.
(Regardless of any corporate/financial incentives in relation to psychological research into ME, the point stands: these sort of distortions are widespread and natural, even in the absence of malice or conflict of interest).
I’ve learned the hard way to be exceedingly careful,” Schooler says. “Every researcher should have to spell out, in advance, how many subjects they’re going to use, and what exactly they’re testing, and what constitutes a sufficient level of proof. We have the tools to be much more transparent about our experiments.”
In a forthcoming paper, Schooler recommends the establishment of an open-source database, in which researchers are required to outline their planned investigations and document all their results. “I think this would provide a huge increase in access to scientific work and give us a much better way to judge the quality of an experiment,” Schooler says. “It would help us finally deal with all these issues that the decline effect is exposing.
Absolutely right, spot on as to how it should work - it's always so exciting to read somebody expounding these sort of ideas in print: it should be a requirement for publication that the details of the experiment were published publiclybefore the experiment takes place, and that the results must always then be published in full when the experiment is completed or aborted. Studies that don't satisfy these criteria should be inadmissible as scientific evidence. That way, experiments can't be performed 'speculatively' and their results published only if they suit the interests of the funders - as is common practice today.
Modern Science is in crisis. The findings of scientists don't command widespread respect and trust in the way they used to, because people are increasingly aware that the scientific process has become corrupted by corporate interests undermining academic freedom, a phenomenon which is probably only about 20-30 years old, in its modern form at least. Huge numbers of people who are rationalists and firm believers in the scientific method, have lost faith in the practical reality of modern scientific practice, and many good researchers have left the world of research in disgust.
At the same time, this corruption of academia is approaching this crisis point at a time when the internet is reaching a stage of maturity that offers unprecedented opportunities to revolutionise the practical application of the scientific method. The publication and peer review process are capable of radical reform, new paradigms can now be imagined - and all that is required is some recognition of the scale and seriousness of the problem, and the vision to imagine that science could take place in a better way.
Openness, transparency, and the democratisation of access to research findings, are the only ways I can see to resolve this crisis. The nature of my belief in science itself has never changed, but these simple principles are certainly the only things that can restore my own faith in the scientific process as it exists in practice today.
I don't think there is anything wrong with scientific method, per se, but clearly we need to keep the practice of it much more transparent and rigourous and honest. Which might also make it more efficient, I would suggest.