How about providing large open source data sets (vetted and screened) to scientists, researchers, mathematicians and economists that can be used to crowd source correlation and causation analysis of politically contentious issues? Zika and birth defects, environmental links to autism or peanut allergy, race / gender / class and income mobility, etc… My favorite would be carbon emissions and climate change. As a skeptic my main issue is that the ‘hockey stick’ graph interpretation always seems like bad math and a faulty trend argument. But as a practical person, I realize that missing the signals could be devastating. As a cynic I realize that the political argument is tantamount to insulting someones religion. Why not use open source data (some data sets un-altered as a control, other data sets manipulated [switching signs on temp / emissions or randomized completely] to run a meta-experiment to tease out political and analytical bias in the researchers’ algorithms) to start settling on the underlying mathematics of correlation and causation in the climate change discussion? suggested a method for this in an article and tested the approach with the correlation of race to ‘red card’ in football. Climate change is just as contentious, why not use the power of Jigswaw to help use the power of meta to get closer to the truth?

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