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How do you use a small set of scientific studies to prove one is better? Studies are reductionist, which is a very powerful and useful perspective...but not as useful when you have to measure a dynamic living system that can be optimized along maybe 100 dimensions or more? Worse, what is the funding source of these studies, and what incentives are tied to it?

So you have many different types of soils, and that will produce variations. You have different histories on those soils, you can measure for a dozen minerals, but what about those tiny trace minerals? Top soil optimization...nutrient run-off that creates fungal blooms in the ocean killing life in the ocean, price per pound to produce produce, shelf life of produce, how it looks, is the taste in fashion ----- so take those dimensions that you can measure things on --- and then multiply that by the number of different veggies and fruits and all their different types (eg. how many different apples are there??)

It's too massive problem space to solve with a few studies...and the financial incentives and ideological thinking further muddies the waters.




You do this with a proper understanding of statistical power, and you report "no conclusion" when you don't have studies of adequate power. This is not actually a terribly difficult problem with a proper understanding of Bayesian statistics, it just doesn't lead to good headlines, because a lot of the time the answer is "the study couldn't really provide an answer."


I'm not saying you're wrong but doesn't that inherently favour the side claiming "there is no problem because you can't prove there's a problem." Until by the time someone can prove there's a problem we already have a generation with lead poisoning or a collapsed ecosystem or whatever it may be.




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