How to Interpret Research on Global Climate Change (GCC)

Rob, I spent about 3 hours on global climate change (GCC) yesterday.  That’s really a drop in the bucket for what is necessary for true understanding.  It also made my head hurt because it requires mathematical and statistical skills I don’t normally use for that long of a stretch.  🙂

Let me start by pointing out that nearly all research is deeply flawed to such a point that the conclusions are not warranted.  The Cochrane Collaboration is a recognized arbiter in the field of medicine and they reject 98% of published medical research even in the best journals.  I’ve written a book chapter about common measurement interpretation errors that even top researchers make (Dent, 2005).  If you are interested, you can read it here.  A simple example of such errors is pay equity between men and women.  It is plastered all over the media that women only make 81 cents compared to the dollar for men.  However, if you control for years of experience and hours worked per week, the gap essentially disappears.  In fact, if anything, women under age 30 make more than men under 30 now. 

An example of such a variable that must be controlled for in GCC is the intensity of the sun.  The sun’s intensity reached a 10,000 year peak in the 1980s and 1990s.   Any reporting of temperatures, or models, that do not control for the intensity of the sun cannot purport to say anything important about human-caused GCC.  If there was a GCC Cochrane Collaboration, they would rightfully disregard all such studies. 


Dent, E. B. (2005). The observation, inquiry, and measurement challenges surfaced by complexity theory.  In K. Richardson (Ed.), Managing the Complex: Philosophy, Theory and Practice. Greenwich, CT: Information Age Publishers.


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