As a non-scientist but one who takes their work seriously, I am still often in denial is because so much of the work in statistical validation seems to be tryin

As a non-scientist but one who takes their work seriously, I am still often in denial is because so much of the work in statistical validation seems to be trying to compress a multidimensional model to fit on a one dimensional scale that, even using accepted/established methods, always gives you a very flat understanding of the topic at hand. Even those working most closely with the data sometimes seem somehow unable to present anything beyond the oversimplified model, but are dying to even take further than one dimensional and draw a line so they have a false dichotomy so they can paint things black and white. This is practiced on both sides making results inherently useless despite scientific techniques and credentials of the researchers. And so, for example, neither side in the climate change debate provides the public with anything remotely resembling a model they can develop faith in by subjecting it to reasonable scrutiny or trying to decide whether it smells right based upon ongoing critical analysis.