The trend since the 1950s has been that policy-relevant science has become increasingly resistant to falsification testing, because it tends to address scientific questions of integrated complexity.
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The science that informs public debate increasingly can not use experiments to adjudicate disagreements, and instead must rely on dueling models. We wouldn’t purposely expose randomly selected groups of people to lead paint, and couldn’t build parallel full-size replicas of earth and pump differing levels of CO2 into them.
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Serious scientists in fields dominated by integrated complexity are constantly trying to develop methods for testing hypotheses, but the absence of decisive experiments makes it much easier for groupthink to take hold. A much larger proportion of scientists self-identify as liberal than conservative, so when scientific questions of integrated complexity impinge on important political questions, the opportunities for unconscious bias are pretty obvious. Hasty conservative political pushback (e.g., “global warming is a hoax”) naturally creates further alienation between these politicians and scientists. The scientists then find political allies who have political reasons for accepting their conclusions; consequently, many conservatives come to see these scientists as pseudo-objective partisans. This sets up a vicious cycle. Unfortunately, that’s where we find ourselves now in far too many areas.
I think he's right. Further, the fact is that not all science is created equal. For example, the social sciences generally don't have, and likely never will have, the same grounding in repeatable experiment that physics and chemistry have. There are exceptions of course. Is Sociology really any more scientific than Economics is? Unfortunately, much of political policy is based on these softer-sciences. Unfortunately, much of climate science seems pretty soft. I suspect that the general public understands this, and that much of its skepticism stems from this understanding.
Ann says: As for social science studies, they are often statistics generated. Do a poll, research demographics, etc. But few studies actually include a professional statistician as one of the people setting up the study. This was the problem with the famous Mann Hockey Stick graph that really set off the global warming scare. It was a badly designed statistical analysis, that a highly-trained statistician would have caught.
Of course, then you have flagrant invention of data, such as the famous study of gun ownership in Revolutionary War times by Michael Bellisles. He claimed there were few guns back then, but conveniently, claimed that much of his original sources were destroyed in a flood. When people tried to replicate his data, the couldn't. It took several years before his study was roundly accepted to be a fake.
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