There’s a nickname for Missouri, the “Show Me State”. It is a label attributed to Representative Willard Van Diver. It connotes a certain self-deprecating stubbornness and devotion to simple common sense. A recent post highlighted by Andrew Montford at Bishop Hill illustrates how this is applicable to climate skepticism.
The Chemist in Langley has another post on type 1 and type 2 errors, which is just as good as his last one. I found this quote particularly perspicacious:
A colleague at work describes the difference as roughly the “trust me crowd” versus the “show me crowd”. The trust me crowd can show that some anthropogenic climate change has happened in the past and that models suggest that future conditions are going to get worse. They produce their documentation via the peer reviewed press and in doing so address all the touchstones of the scientific method. Having met the high bar of “good science” they anticipate that their word will be taken as good.
The show me crowd looks at the “good science” and points out that many historical predictions of doom and gloom (that previously met the test of good science) have been shown to be overheated or just plain wrong. They also point out that the best models have not done a very good job with respect to the “pause”. Given this they ask for a demonstration that the next prediction is going to be better than the last one. This does not mean that they deny the reality of anthropogenic global warming. Rather they are not comfortable with cataclysmic predictions and calls for immediate action prior to a demonstration that those predictions can be supported with something approaching real data.
Here is the first article from “A Chemist in Langley”:
…the vast majority of the warmist community have a worldview that stresses Type I [false positive] error avoidance while most skeptics work in a community that stresses Type II [false negative] error avoidance. Skeptics look at the global climate models and note that the models have a real difficulty in making accurate predictions. To explain, global climate models are complex computer programs filled with calculations based on science’s best understanding of climate processes (geochemistry, global circulation patterns etc) with best guesses used to address holes in the knowledge base.