A good example of a recent failure, within the mainstream scientific community, is the “Ego Depletion Effect”. Basically, it’s a behavior wished into existence by bad data analysis (called P-hacking) that tricked the entire Psychology academic complex for several years. Replication studies were eventually done, and they revealed the EDE wasn’t real. This was so alarming that the researchers tried to replicate a randomized sample of studies, and found that 80% of them couldn’t be replicated. Similar issues exist in physiology, cosmology, and theoretical physics, just to name a few. An example from the field of physics is that researchers are obsessed with building particle colliders when there are equally as promising alternatives (yet that have less financial gain) like modified gravity theories. If you study the underlying issues, and how they aggregated into a consensus, you would see a similar behavior in climate science as well. The researchers don’t have a fundamental understanding of statistics (or other relevant math concepts) and make very basic mistakes when interpreting data. A common error is not understanding chaos theory and how it applies to computer simulations (which is very relevant to cosmology, physics, and climate science). Funding bias is a huge issue as well. Popularity bias is very common as well: an easy example is that anthropologists used war to explain evidence more frequently during the Cold War, ergo their interpretation of evidence was biased by the news. Climate science is perhaps the most popularity-biased and funding-biased and error-biased field that I have ever personally witnessed, and that’s saying a lot when the field of psychology exists.
A good example of a recent failure, within the mainstream scientific community, is the “Ego Depletion Effect”. Basically, it’s a behavior wished into existence by bad data analysis (called P-hacking) that tricked the entire Psychology academic complex for several years. Replication studies were eventually done, and they revealed the EDE wasn’t real. This was so alarming that the researchers tried to replicate a randomized sample of studies, and found that 80% of them couldn’t be replicated. Similar issues exist in physiology, cosmology, and theoretical physics, just to name a few. An example from the field of physics is that researchers are obsessed with building particle colliders when there are equally as promising alternatives (yet that have less financial gain) like modified gravity theories. If you study the underlying issues, and how they aggregated into a consensus, you would see a similar behavior in climate science as well. The researchers don’t have a fundamental understanding of statistics (or other relevant math concepts) and make very basic mistakes when interpreting data. A common error is not understanding chaos theory and how it applies to computer simulations (which is very relevant to cosmology, physics, and climate science). Funding bias is a huge issue as well. Popularity bias is very common as well: an easy example is that anthropologists used war to explain evidence more frequently during the Cold War, ergo their interpretation of evidence was biased by the news. Climate science is perhaps the most popularity-biased and funding-biased and error-biased field that I have ever personally witnessed, and that’s saying a lot when the field of psychology exists.