Oreskes thinks so.
When applied to evaluating environmental hazards, the fear of gullibility can lead us to understate threats. It places the burden of proof on the victim rather than, for example, on the manufacturer of a harmful product. The consequence is that we may fail to protect people who are really getting hurt.
And what if we aren’t dumb? What if we have evidence to support a cause-and-effect relationship? Let’s say you know how a particular chemical is harmful; for example, that it has been shown to interfere with cell function in laboratory mice. Then it might be reasonable to accept a lower statistical threshold when examining effects in people, because you already have reason to believe that the observed effect is not just chance.
This is what the United States government argued in the case of secondhand smoke. Since bystanders inhaled the same chemicals as smokers, and those chemicals were known to be carcinogenic, it stood to reason that secondhand smoke would be carcinogenic, too. That is why the Environmental Protection Agency accepted a (slightly) lower burden of proof: 90 percent instead of 95 percent.
I think that the underlying point is valid but the statistical argument is a bit muddled. Statistical significance of what?
Science often reaches conclusions where statistics is uninformative. Suppose a guy shows up in the emergency room with various symptoms. The hospital makes its best guess as to what is going on. They have only a single sample. No statistics are possible. But the treatment is still based in science.