Theory, and Practice
I'll see your science and raise you.
I half-jokingly posted that, looking back, perhaps a better name for this blog/site/stack would be “models of the world”, because that encompassed both the gaming and art/media side of my writing, as well as the more philosophical side.
In this I’m going to leave aside questions of noetic knowledge, or of phenomena for which we only have (often unreliable) witnesses, despite the fact that in many cases, especially when it comes to weather phenomena such as rogue waves, all we had were witness reports that were disbelieved for years or decades. There are after all stranger things on earth than exist in our understanding of the world, even when we restrict ourselves to the material and easily quantifiable.
The difference between theory and practice
Science is a number of things, including “what scientists do”, our accumulated understanding of how the world works, and the practice of proposing theories and validating them. In the end, I think one of the best ways to differentiate between science and engineering is the old saw about the difference between theory and practice. Science is the theory - the model of how we believe the world works - that hopefully explains how what we have already seen behaves and in many cases, if a reasonably useful model1, can be used to predict behavior and then test for it.
Engineering is putting stuff together in a way that works, repeatably. It operates off of derived tables for pressure, temperature and stresses, as well as knowledge that doing certain processes to certain materials yields certain results. We have been reliably doing engineering of things like gunpowder and concrete to make rockets and bridges for hundreds and thousands of years developed through trial and error without ever having knowledge of the “why”, only that it works. Repeatably.
The difference between science and engineering is exactly that - the difference between theory and practice. In the end, if practice does not bear out the theory, it is the theory that must bend. For those who still hold to the scientific method, it’s baked into science as well.
In the end, I don’t care what “science says” if the science is theoretical. I apply the same distrust to incentives to any field for which there isn’t hard data, especially when what little hard data exists is hidden away because “trust us.” In a day and age where we have a replication crisis even in supposedly hard sciences, if it cannot be or has not been consistently replicated, I don’t care. If your model works fine in one regime, but fails in another, you need at least one different model, and to accept the one you’re using has limits.
And yes, that means that imperfect models are fine, as long as their limitations are understood. By way of example, one way to teach electric circuits to mechanics, and piping and pressure to electricians, is to equate the two. Is it a perfect model? No, certainly not at the equation level. But, pressure and voltage, resistance, etc., do map well enough that it’s easier for someone who knows one to understand the other than to teach someone from scratch. Far easier.
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No models are 100 percent accurate, but some are more useful than others.