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Real science is not without it's problems but, in general, nothing comes close to it for producing trustworthy and useful results.

There is plenty of pseudoscience masquerading as science unfortunately. A good book to read on this is Carl Sagan's "The Demon-Haunted World: Science as a Candle in the Dark". A significant portion of the book is devoted to what Sagan calls a "Baloney detection kit" that he thinks everyone should have. If more people could accurately distinguish science from pseudoscience, the world might be a better place.

My personal pick for pseudoscience that is routinely given credence by the general public is nutritional studies. Any study that says an oddly specific food (e.g. blueberries) is a "superfood" is probably baloney. Producers of that food probably got together and funded a study that, surprise, says what they produce is good to eat! Why aren't other berries just as good? What about berries vs other fruit? What is in blueberries that is not present in other berries?

The thing about nutritional studies is that they're so hard to do properly that virtually nobody does. If you wanted to find out which foods are genuinely healthy you'd need a large sample size of people willing to have their diets and activities micro-managed in a way that would make most people rebel. You could probably do a decent study if you had enough money, but nobody is willing to foot the bill. The only people with skin in the game (e.g. blueberry producers) have no interest in a study that puts blueberries fairly in their place amongst a plethora of other foods.

My crazy prediction is that, sometime in the next century or two, we're actually going to become interested enough in optimizing healthy bodies that governments will start funding real scientific studies on nutrition, exercise, etc.. The crap that's out there today is going to be seen as utter quackery, albeit with some nuggets of truth mixed in almost by random chance.




Knowing what is science and what is pseudoscience is a science itself. To take a trivial example, consider the climate change topic. Read a couple randomly chosen papers and if you’re unlucky, you might come out of it thinking global warming isn’t real. (Remember, papers like that do exist and although they are a minority, random number generation doesn’t know about that.) How do you know if the papers you read are a representative sample? How do you know the papers that are published are a representative sample? It boils down to some disturbing epistemological conclusions. You can use metastudies, but then the metastudies could have the same problem, or worse, might not exist. (In my experience they usually don’t.)


References to climate change are going to become something like an index fossil for papers written in the current decade. A paper might seem to have no connection to climate science at all, but if the authors can grasp for some tenuous link that lets them put "climate change" in their abstract, they will.

Say you're a researcher fifty years in the future who is doing a literature review. When a paper about anti-hydrogen trapping works in a reference to climate change, you won't even need to look at the date of the paper to know, roughly, when it was written.


>How do you know if the papers you read are a representative sample? How do you know the papers that are published are a representative sample?

You don't. You use the sources you've seen to make the best analysis you can, fully prepared to drop it if with further evidence.


That’s the very reason you can’t “trust the science” in general though. Science is a good tool for knowledge when there has been a repetition of studies, but when all you have is a few, you’re kind of screwed. You can’t claim to know even a basic thing without being an expert in the field these days as a result. A large part of this though is down to lack of discoverability of similar studies which I think can be helped.




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